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OmniLottie/lottie/objects/convert_lottie_512.py
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import torch
import re
import json
from typing import Union, List, Dict, Tuple, Optional, Any
import difflib
from .test2_0518 import *
import numpy as np
#from test_0819 import *
class LottieTensor:
# Command type constants (添加新的命令常量)
tokenizer = None
CMD_ANIMATION = 0
CMD_LAYER = 1
CMD_TRANSFORM = 2
CMD_POSITION = 3
CMD_KEYFRAME = 4
CMD_POSITION_END = 5
CMD_SCALE = 6
CMD_SCALE_END = 7
CMD_ROTATION = 8
CMD_OPACITY = 9
CMD_OPACITY_END = 10
CMD_ANCHOR = 11
CMD_GROUP = 12
CMD_GROUP_END = 13
CMD_TRANSFORM_SHAPE = 14
CMD_PATH = 15
CMD_PATH_END = 16
CMD_POINT = 17
CMD_FILL = 18
CMD_GRADIENT_FILL = 19
CMD_GRADIENT_FILL_END = 20
CMD_START_POINT = 21
CMD_END_POINT = 22
CMD_GRADIENT_TYPE = 23
CMD_HIGHLIGHT_LENGTH = 24
CMD_HIGHLIGHT_ANGLE = 25
CMD_TRANSFORM_END = 26
CMD_LAYER_END = 27
CMD_PAD = 28
CMD_EOS = 29
CMD_SOS = 30
CMD_RECT = 31
CMD_RECT_END = 32
CMD_SIZE = 33
CMD_ROUNDED = 34
CMD_ELLIPSE = 35
CMD_ELLIPSE_END = 36
CMD_STROKE = 37
CMD_SKEW = 38
CMD_SKEW_AXIS = 39
CMD_ASSET = 40
CMD_ASSET_END = 41
CMD_PARENT = 42
CMD_NULL_LAYER = 43
CMD_NULL_LAYER_END = 44
CMD_PRECOMP_LAYER = 45
CMD_PRECOMP_LAYER_END = 46
CMD_REFERENCE_ID = 47
CMD_DIMENSIONS = 48
CMD_ROTATION_END = 49
CMD_STAR = 50
CMD_STAR_END = 51
CMD_INNER_RADIUS = 52
CMD_OUTER_RADIUS = 53
CMD_INNER_ROUNDNESS = 54
CMD_OUTER_ROUNDNESS = 55
CMD_POINTS = 56
CMD_STAR_ROTATION = 57
CMD_TRIM = 58
CMD_TRIM_END = 59
CMD_START = 60
CMD_END = 61
CMD_OFFSET = 62
CMD_MULTIPLE = 63
CMD_REPEATER = 64
CMD_REPEATER_END = 65
CMD_COPIES = 66
CMD_REPEATER_OFFSET = 67
CMD_COMPOSITE = 68
CMD_REPEATER_TRANSFORM = 69
CMD_REPEATER_TRANSFORM_END = 70
CMD_GRADIENT_STROKE = 71
CMD_GRADIENT_STROKE_END = 72
CMD_WIDTH = 73
CMD_LINE_CAP = 74
CMD_LINE_JOIN = 75
CMD_MITER_LIMIT = 76
CMD_MERGE = 77
CMD_MERGE_END = 78
CMD_MERGE_MODE = 79
CMD_ROUNDED_CORNERS = 80
CMD_ROUNDED_CORNERS_END = 81
CMD_RADIUS = 82
CMD_TWIST = 83
CMD_TWIST_END = 84
CMD_ANGLE = 85
CMD_CENTER = 86
CMD_BEZIER = 87
CMD_BEZIER_END = 88
CMD_TEXT_LAYER = 89
CMD_TEXT_LAYER_END = 90
CMD_TEXT_DATA = 91
CMD_TEXT_DATA_END = 92
CMD_DOCUMENT = 93
CMD_SOLID_LAYER = 94
CMD_SOLID_LAYER_END = 95
CMD_POSITION_X = 96
CMD_POSITION_Y = 97
CMD_POSITION_Z = 98
CMD_POSITION_X_END = 99
CMD_POSITION_Y_END = 100
CMD_POSITION_Z_END = 101
CMD_SCALE_X = 102
CMD_SCALE_Y = 103
CMD_SCALE_Z = 104
CMD_SCALE_X_END = 105
CMD_SCALE_Y_END = 106
CMD_SCALE_Z_END = 107
CMD_ROTATION_X = 108
CMD_ROTATION_Y = 109
CMD_ROTATION_Z = 110
CMD_ROTATION_X_END = 111
CMD_ROTATION_Y_END = 112
CMD_ROTATION_Z_END = 113
CMD_EFFECTS = 114
CMD_EFFECTS_END = 115
CMD_EFFECT = 116
CMD_EFFECT_END = 117
CMD_HAS_MASK = 118
CMD_MASKS_PROPERTIES = 119
CMD_CT = 120
CMD_EF = 121
CMD_TT = 122
CMD_TP = 123
CMD_TD = 124
CMD_HD = 125
CMD_CL = 126
CMD_LN = 127
CMD_AO = 128
CMD_ANCHOR_END = 129
CMD_OPACITY_FILL = 130
CMD_FILL_RULE = 131
CMD_COLOR_DIM = 132
CMD_DDD = 133
CMD_MARKERS = 134
CMD_PROPS = 135
CMD_ORIGINAL_COLORS = 136
CMD_COLOR_POINTS = 137
CMD_COLORS = 138
CMD_ML2 = 139
CMD_ML2_IX = 140
CMD_OFFSET_IX = 141
CMD_TR_P_IX = 142
CMD_TR_A_IX = 143
CMD_TR_SCALE = 144
CMD_TR_S_IX = 145
CMD_TR_R_IX = 146
CMD_TR_SO_IX = 147
CMD_TR_EO_IX = 148
CMD_KEYFRAME_END = 149
CMD_POSITION_EXPR = 150
CMD_SCALE_EXPR = 151
CMD_ROTATION_EXPR = 152
CMD_WIDTH_KEYFRAME = 153 # 新增
CMD_WIDTH_ANIMATED_END = 154 # 新增
CMD_FONTS = 155
CMD_FONTS_END = 156
CMD_FONT = 157
CMD_CHARS = 158
CMD_CHARS_END = 159
CMD_CHAR = 160
CMD_CHAR_END = 161
CMD_CHAR_SHAPES = 162
CMD_CHAR_SHAPES_END = 163
CMD_TEXT_KEYFRAMES = 164
CMD_TEXT_KEYFRAMES_END = 165
CMD_TEXT_KEYFRAME = 166
CMD_TEXT_DOC = 167
CMD_TEXT_DOC_END = 168
CMD_FONT_SIZE = 169
CMD_FONT_FAMILY = 170
CMD_TEXT = 171
CMD_CA = 172
CMD_JUSTIFY = 173
CMD_TRACKING = 174
CMD_LINE_HEIGHT = 175
CMD_LETTER_SPACING = 176
CMD_FILL_COLOR = 177
CMD_MORE_OPTIONS = 178
CMD_MORE_OPTIONS_END = 179
CMD_G = 180
CMD_ALIGNMENT = 181
CMD_ALIGNMENT_K = 182
CMD_ALIGNMENT_IX = 183
CMD_DROPDOWN = 184
CMD_IGNORED = 185
CMD_SLIDER = 186
CMD_COLOR = 187
CMD_OPACITY_ANIMATED = 188
CMD_OPACITY_KEYFRAME = 189
CMD_MASKS_PROPERTIES_END = 190
CMD_MASK = 191
CMD_MASK_END = 192
CMD_MASK_PT = 193
CMD_MASK_PT_END = 194
CMD_MASK_PT_K = 195
CMD_MASK_PT_K_END = 196
CMD_MASK_PT_K_I = 197
CMD_MASK_PT_K_O = 198
CMD_MASK_PT_K_V = 199
CMD_MASK_O = 200
CMD_MASK_X = 201
CMD_TM = 202
CMD_TM_END = 203
CMD_MASK_PT_K_ARRAY = 204
CMD_MASK_PT_K_ARRAY_END = 205
CMD_MASK_PT_KEYFRAME = 206
CMD_MASK_PT_KEYFRAME_END = 207
CMD_MASK_PT_KF_I = 208
CMD_MASK_PT_KF_O = 209
CMD_MASK_PT_KF_S = 210
CMD_MASK_PT_KF_S_END = 211
CMD_MASK_PT_KF_SHAPE = 212
CMD_MASK_PT_KF_SHAPE_END = 213
CMD_MASK_PT_KF_SHAPE_I = 214
CMD_MASK_PT_KF_SHAPE_O = 215
CMD_MASK_PT_KF_SHAPE_V = 216
CMD_VALUE = 217
CMD_VALUE_END = 218
CMD_TR_POSITION = 219
CMD_TR_ANCHOR = 220
CMD_TR_ROTATION = 221
CMD_TR_START_OPACITY = 222
CMD_TR_END_OPACITY = 223
CMD_ZIG_ZAG = 224
CMD_ZIG_ZAG_END = 225
CMD_FREQUENCY = 226
CMD_AMPLITUDE = 227
CMD_POINT_TYPE = 228
CMD_ANIMATORS = 229
CMD_ANIMATORS_END = 230
CMD_ANIMATOR = 231
CMD_ANIMATOR_END = 232
CMD_RANGE_SELECTOR = 233
CMD_RANGE_SELECTOR_END = 234
CMD_RANGE_START = 235
CMD_RANGE_START_END = 236
CMD_RANGE_START_KEYFRAME = 237
CMD_AMOUNT = 238
CMD_MAX_EASE = 239
CMD_MIN_EASE = 240
CMD_ANIMATOR_PROPERTIES = 241
CMD_ANIMATOR_PROPERTIES_END = 242
CMD_OPACITY_ANIMATED_END = 243
CMD_MASK_PT_K_C = 244
CMD_RANGE_END = 245
CMD_RANGE_END_END = 246
CMD_RANGE_END_KEYFRAME = 247
CMD_END_END = 248
CMD_START_END = 249
CMD_OFFSET_END = 250
CMD_POINTS_STAR = 251
CMD_RANGE_OFFSET = 252
CMD_RANGE_OFFSET_END = 253
CMD_RANGE_OFFSET_KEYFRAME = 254
CMD_S_M = 255
CMD_OPACITY_ANIMATORS = 256
CMD_SCALE_ANIMATORS = 257
CMD_SCALE_ANIMATORS_END = 258
CMD_ROTATION_ANIMATORS = 259
CMD_ROTATION_ANIMATORS_END = 260
CMD_POSITION_ANIMATORS = 261
CMD_POSITION_ANIMATORS_END = 262
CMD_TRACKING_ANIMATORS = 263
CMD_OPACITY_ANIMATORS_END = 264
CMD_COLOR_KEYFRAME = 265 # Add this constant
CMD_COLOR_ANIMATED_END = 266
CMD_DASHES = 267
CMD_DASHES_END = 268
CMD_DASH = 269
CMD_DASH_OFFSET = 270
CMD_LAYER_EFFECT = 271
CMD_NO_VALUE = 272
CMD_WIDTH_ANIMATED = 273 # Add this if it doesn't exist
CMD_SIZE_END = 274
CMD_RECT_SIZE = 275 # Add this new constant
CMD_ELLIPSE_SIZE = 276
CMD_RECT_ROUNDED = 277 # Add this new constant for animated rect_rounded
CMD_RECT_ROUNDED_END = 278
CMD_DASH_ANIMATED = 279 # New constant
CMD_DASH_KEYFRAME = 280 # New constant
CMD_DASH_ANIMATED_END = 281 # New constant
# Command names mapped to their numeric constants
COMMANDS = [
"animation", # 0
"layer", # 1
"transform", # 2
"position", # 3
"keyframe", # 4
"/position", # 5
"scale", # 6
"/scale", # 7
"rotation", # 8
"opacity", # 9
"/opacity", # 10
"anchor", # 11
"group", # 12
"/group", # 13
'"TransformShape"', # 14
"path", # 15
"/path", # 16
"point", # 17
"fill", # 18
"gradient_fill", # 19
"/gradient_fill", # 20
"start_point", # 21
"end_point", # 22
"gradient_type", # 23
"highlight_length", # 24
"highlight_angle", # 25
"/transform", # 26
"/layer", # 27
"PAD", # 28
"EOS", # 29
"SOS", # 30
"rect", # 31
"/rect", # 32
"size", # 33
"rounded", # 34
"ellipse", # 35
"/ellipse", # 36
"stroke", # 37
"skew", # 38
"skew_axis", # 39
"asset", # 40
"/asset", # 41
"parent", # 42
"null_layer", # 43
"/null_layer", # 44
"precomp_layer", # 45
"/precomp_layer", # 46
"reference_id", # 47
"dimensions", # 48
"/rotation", # 49
"star", # 50
"/star", # 51
"inner_radius", # 52
"outer_radius", # 53
"inner_roundness", # 54
"outer_roundness", # 55
"points", # 56
"star_rotation", # 57
"trim", # 58
"/trim", # 59
"start", # 60
"end", # 61
"offset", # 62
"multiple", # 63
"repeater", # 64
"/repeater", # 65
"copies", # 66
"repeater_offset", # 67
"composite", # 68
"repeater_transform", # 69
"/repeater_transform", # 70
"gradient_stroke", # 71
"/gradient_stroke", # 72
"width", # 73
"line_cap", # 74
"line_join", # 75
"miter_limit", # 76
"merge", # 77
"/merge", # 78
"merge_mode", # 79
"rounded_corners", # 80
"/rounded_corners", # 81
"radius", # 82
"twist", # 83
"/twist", # 84
"angle", # 85
"center", # 86
"bezier", # 87
"/bezier", # 88
"text_layer", # 89
"/text_layer", # 90
"text_data", # 91
"/text_data", # 92
"document", # 93
"solid_layer", # 94
"/solid_layer", # 95
"position_x", # 96
"position_y", # 97
"position_z", # 98
"/position_x", # 99
"/position_y", # 100
"/position_z", # 101
"scale_x", # 102
"scale_y", # 103
"scale_z", # 104
"/scale_x", # 105
"/scale_y", # 106
"/scale_z", # 107
"rotation_x", # 108
"rotation_y", # 109
"rotation_z", # 110
"/rotation_x", # 111
"/rotation_y", # 112
"/rotation_z", # 113
"effects", # 114
"/effects", # 115
"effect", # 116
"/effect", # 117
"hasMask", # 118
"masksProperties", # 119
"ct", # 120
"ef", # 121
"tt", # 122
"tp", # 123
"td", # 124
"hd", # 125
"cl", # 126
"ln", # 127
"ao", # 128
"/anchor", # 129
"opacity_fill", # 130
"fill_rule", # 131
"color_dim", # 132
"ddd", # 133
"markers", # 134
"props", # 135
"original_colors", # 136
"color_points", # 137
"colors", # 138
"ml2", # 139
"ml2_ix", # 140
"offset_ix", # 141
"tr_p_ix", # 142
"tr_a_ix", # 143
"tr_scale", # 144
"tr_s_ix", # 145
"tr_r_ix", # 146
"tr_so_ix", # 147
"tr_eo_ix", # 148
"/keyframe", # 149
"position_expr", # 150
"scale_expr", # 151
"rotation_expr", # 152
"width_keyframe", # 153 # 新增
"/width_animated", # 154 # 新增
"fonts", # 155
"/fonts", # 156
"font", # 157
"chars", # 158
"/chars", # 159
"char", # 160
"/char", #161
"char_shapes", # 162
"/char_shapes", # 163
"text_keyframes", # 164
"/text_keyframes", # 165
"text_keyframe", # 166
"text_doc", # 167
"/text_doc", # 168
"font_size", # 169
"font_family", # 170
"text", # 171
"ca", # 172
"justify", # 173
"tracking_animators", # 174
"line_height", # 175
"letter_spacing", # 176
"fill_color", # 177
"more_options", # 178
"/more_options", # 179
"g", # 180
"alignment", # 181
"alignment_k", # 182
"alignment_ix", # 183
"dropdown", # 184
"ignored", # 185
"slider", # 186
"color", # 187
"opacity_animated", # 188
"opacity_keyframe", # 189
"/masksProperties", # 190
"mask", # 191
"/mask", # 192
"mask_pt", # 193
"/mask_pt", # 194
"mask_pt_k", # 195
"/mask_pt_k", # 196
"mask_pt_k_i", # 197
"mask_pt_k_o", # 198
"mask_pt_k_v", # 199
"mask_o", # 200
"mask_x", # 201
"tm", # 202
"/tm", # 203
"mask_pt_k_array", # 204
"/mask_pt_k_array", # 205
"mask_pt_keyframe", # 206
"/mask_pt_keyframe", # 207
"mask_pt_kf_i", # 208
"mask_pt_kf_o", # 209
"mask_pt_kf_s", # 210
"/mask_pt_kf_s", # 211
"mask_pt_kf_shape", # 212
"/mask_pt_kf_shape", # 213
"mask_pt_kf_shape_i", # 214
"mask_pt_kf_shape_o", # 215
"mask_pt_kf_shape_v", # 216
"value", # 217
"/value", # 218
"tr_position", # 219
"tr_anchor", # 220
"tr_rotation", # 221
"tr_start_opacity", # 222
"tr_end_opacity", # 223
"zig_zag", # 224
"/zig_zag", # 225
"frequency", # 226
"amplitude", # 227
"point_type", # 228
"animators", # 229
"/animators", # 230
"animator", # 231
"/animator", # 232
"range_selector", # 233
"/range_selector", # 234
"range_start", # 235
"/range_start", # 236
"range_start_keyframe", # 237
"amount", # 238
"max_ease", # 239
"min_ease", # 240
"animator_properties", # 241
"/animator_properties", # 242
"/opacity_animated", # 243
"mask_pt_k_c", #244
"range_end", # 245
"/range_end", # 246
"range_end_keyframe", # 247
"/end", #248
"/start" , # 249
"/offset" , # 250
"points_star", #251
"range_offset", # 252
"/range_offset", # 253
"range_offset_keyframe", # 254
"s_m", # 255
"opacity_animators", # 256
"scale_animators", # 257
"/scale_animators", # 258
"rotation_animators", # 259
"/rotation_animators", # 260
"position_animators", # 261
"/position_animators", # 262
"tracking_animators", # 263
"/opacity_animators", #264
"color_keyframe", # 265
"/color_animated", #266
"dashes", # 267
"/dashes", # 268
"dash", # 269
"dash_offset", # 270
"layer_effect", # 271
"no_value", #272
"width_animated" , #273
"/size", #274
"rect_size", # 275 # Add this new command
"ellipse_size", # 276
"rect_rounded", # 277
"/rounded", #278
"dash_animated", # 279 # Add this
"dash_keyframe", # 280 # Add this
"/dash_animated", # 281 # Add this
]
# Command to index mapping
COMMAND_TO_IDX = {cmd: idx for idx, cmd in enumerate(COMMANDS)}
_OFFSET_CACHE = {}
# Parameter indices for each command type (添加新的Index定义)
class Index:
# Animation parameters
class Animation:
FR = 0
IP = 1
OP = 2
W = 3
H = 4
DDD = 5
class Layer:
INDEX = 0
IN_POINT = 1
OUT_POINT = 2
START_TIME = 3
DDD = 4
HD = 5
HAS_MASK = 6
AO = 7
TT = 8
TP = 9
TD = 10
CT = 11
CP = 12
class Value:
VALUE = 0
class Transform:
ANIMATED = 0
X = 1
Y = 2
Z = 3
class Keyframe:
T = 0
S1 = 1
S2 = 2
S3 = 3
I_X = 4 # 第一个值，或单值情况
I_Y = 5 # 第一个值，或单值情况
O_X = 6 # 第一个值，或单值情况
O_Y = 7 # 第一个值，或单值情况
TO1 = 8
TO2 = 9
TO3 = 10
TI1 = 11
TI2 = 12
TI3 = 13
# Multi-dimensional easing (for scale, position, anchor)
I_X2 = 14
I_X3 = 15
I_Y2 = 16
I_Y3 = 17
O_X2 = 18
O_X3 = 19
O_Y2 = 20
O_Y3 = 21
H_FLAG = 22
E1 = 23
E2 = 24
E3 = 25
class Tm:
A = 0
#IX = 1
class WidthKeyframe: # 新增
T = 0
S = 1
I_X = 2
I_Y = 3
O_X = 4
O_Y = 5
class Path:
IX = 0
IND = 1
KS_IX = 2
CLOSED = 3
HD = 4
ANIMATED = 5
class Point:
X = 0
Y = 1
IN_X = 2
IN_Y = 3
OUT_X = 4
OUT_Y = 5
class Fill:
R = 0
G = 1
B = 2
COLOR_DIM = 3
HAS_C_A = 4
HAS_C_IX = 5
C_IX = 6
BM = 7
FILL_RULE = 8
OPACITY = 9
COLOR_ANIMATED = 10 # New
OPACITY_ANIMATED = 11 # New
HAS_O_A = 12 # New
HAS_O_IX = 13 # New
O_IX = 14 # New
class TransformShape:
POSITION_X = 0
POSITION_Y = 1
SCALE_X = 2
SCALE_Y = 3
ROTATION = 4
OPACITY = 5
ANCHOR_X = 6
ANCHOR_Y = 7
SKEW = 8
SKEW_AXIS = 9
HD = 10
class Stroke:
R = 0
G = 1
B = 2
COLOR_DIM = 3
HAS_C_A = 4
HAS_C_IX = 5
C_IX = 6
BM = 7
LC = 8
LJ = 9
ML = 10
#WIDTH = 11
#OPACITY = 12
WIDTH_ANIMATED = 11 # 新增
COLOR_ANIMATED = 12 # Add this
A = 13 # Add alpha channel support
class Bezier:
CLOSED = 0
class Group:
IX = 0
CIX = 1
BM = 2
HD = 3
NP = 4
class Star:
D = 0
SY = 1
class StarValue: # 新增用于 star 的子命令
VALUE = 0
class Trim:
IX = 0
START = 1
END = 2
OFFSET = 3
MULTIPLE = 4
class TrimValue:
VALUE = 0
ANIMATED = 1
IX = 2
class Repeater:
IX = 0
COPIES = 1
REPEATER_OFFSET = 2
COMPOSITE = 3
TR_P_IX = 4
TR_A_IX = 5
TR_SCALE = 6
TR_S_IX = 7
TR_R_IX = 8
TR_SO_IX = 9
TR_EO_IX = 10
class Asset:
#ID = 0
FR = 0
ID_TOKEN_0 = 1
ID_TOKEN_1 = 2
ID_TOKEN_2 = 3
ID_TOKEN_3 = 4
ID_TOKEN_4 = 5
ID_TOKEN_5 = 6
ID_TOKEN_6 = 7
ID_TOKEN_7 = 8
ID_TOKEN_8 = 9
ID_TOKEN_9 = 10
ID_TOKEN_COUNT = 11 # Store count of tokens
class Rect:
HD = 0
D = 1
POSITION_X = 2
POSITION_Y = 3
SIZE_X = 4
SIZE_Y = 5
ROUNDED = 6
IX = 7
class Ellipse:
POSITION_X = 0
POSITION_Y = 1
SIZE_X = 2
SIZE_Y = 3
class SingleValue:
VALUE = 0
IX = 1
ANIMATED = 2
class TwoValues:
VALUE1 = 0
VALUE2 = 1
IX = 2
class ThreeValues:
VALUE1 = 0
VALUE2 = 1
VALUE3 = 2
class NullLayer:
INDEX = 0
IN_POINT = 1
OUT_POINT = 2
START_TIME = 3
CT = 4
#DDD = 5
HD = 5
HAS_MASK = 6
AO = 7
TT = 8
TP = 9
TD = 10
CP = 11
class PrecompLayer:
INDEX = 0
IN_POINT = 1
OUT_POINT = 2
START_TIME = 3
W = 4
H = 5
CT = 6 # 添加CT参数
HAS_MASK = 7
AO = 8
TT = 9
TP = 10
TD = 11
DDD =12
HD = 13
CP = 14
class SolidLayer:
INDEX = 0
IN_POINT = 1
OUT_POINT = 2
START_TIME = 3
WIDTH = 4
HEIGHT = 5
HAS_MASK = 6
COLOR_R = 7
COLOR_G = 8
COLOR_B = 9
COLOR_A = 10
class Parent:
PARENT_INDEX= 0
class ReferenceId: # 新增
ID_TOKEN_0 = 0
ID_TOKEN_1 = 1
ID_TOKEN_2 = 2
ID_TOKEN_3 = 3
ID_TOKEN_4 = 4
ID_TOKEN_5 = 5
ID_TOKEN_6 = 6
ID_TOKEN_7 = 7
ID_TOKEN_8 = 8
ID_TOKEN_9 = 9
ID_TOKEN_COUNT = 10 # Store count of tokens
class Dimensions: # 新增
WIDTH = 0
HEIGHT = 1
class Font:
ASCENT = 0
FAMILY_TOKEN_0 = 1
FAMILY_TOKEN_1 = 2
FAMILY_TOKEN_2 = 3
FAMILY_TOKEN_3 = 4
FAMILY_TOKEN_4 = 5
FAMILY_TOKEN_5 = 6
FAMILY_TOKEN_6 = 7
FAMILY_TOKEN_7 = 8
FAMILY_TOKEN_8 = 9
FAMILY_TOKEN_9 = 10
FAMILY_TOKEN_COUNT = 11
# Reserve slots for style tokens
STYLE_TOKEN_0 = 12
STYLE_TOKEN_1 = 13
STYLE_TOKEN_2 = 14
STYLE_TOKEN_3 = 15
STYLE_TOKEN_4 = 16
STYLE_TOKEN_5 = 17
STYLE_TOKEN_6 = 18
STYLE_TOKEN_7 = 19
STYLE_TOKEN_8 = 20
STYLE_TOKEN_9 = 21
STYLE_TOKEN_COUNT = 22
class Char:
SIZE = 0
W = 1
CH_TOKEN_0 = 2
CH_TOKEN_1 = 3
CH_TOKEN_2 = 4
CH_TOKEN_3 = 5
CH_TOKEN_4 = 6
CH_TOKEN_5 = 7
CH_TOKEN_6 = 8
CH_TOKEN_7 = 9
CH_TOKEN_8 = 10
CH_TOKEN_9 = 11
CH_TOKEN_COUNT = 12
# Reserve slots for style tokens
STYLE_TOKEN_0 = 13
STYLE_TOKEN_1 = 14
STYLE_TOKEN_2 = 15
STYLE_TOKEN_3 = 16
STYLE_TOKEN_4 = 17
STYLE_TOKEN_5 = 18
STYLE_TOKEN_6 = 19
STYLE_TOKEN_7 = 20
STYLE_TOKEN_8 = 21
STYLE_TOKEN_9 = 22
STYLE_TOKEN_COUNT = 23
# Reserve slots for family tokens
FAMILY_TOKEN_0 = 24
FAMILY_TOKEN_1 = 25
FAMILY_TOKEN_2 = 26
FAMILY_TOKEN_3 = 27
FAMILY_TOKEN_4 = 28
FAMILY_TOKEN_5 = 29
FAMILY_TOKEN_6 = 30
FAMILY_TOKEN_7 = 31
FAMILY_TOKEN_8 = 32
FAMILY_TOKEN_9 = 33
FAMILY_TOKEN_COUNT = 34
class TextLayer:
INDEX = 0
IN_POINT = 1
OUT_POINT = 2
START_TIME = 3
HAS_MASK = 4 # 新增
class TextKeyframe:
T = 0
STROKE_WIDTH = 1
OFFSET = 2
WRAP_POSITION_X = 3
WRAP_POSITION_Y = 4
WRAP_SIZE_X = 5
WRAP_SIZE_Y = 6
# Add numeric fields instead of string storage
FONT_SIZE = 7
CA = 8
JUSTIFY = 9
TRACKING = 10
LINE_HEIGHT = 11
LETTER_SPACING = 12
FILL_COLOR_R = 13
FILL_COLOR_G = 14
FILL_COLOR_B = 15
STROKE_COLOR_R = 16
STROKE_COLOR_G = 17
STROKE_COLOR_B = 18
HAS_STROKE_COLOR = 19 # Flag to indicate if stroke_color exists
FONT_FAMILY_TOKENS_START = 20 # Store up to 10 tokens for font_family
TEXT_TOKENS_START = 30 # Store up to 15 tokens for text
FONT_FAMILY_TOKEN_COUNT = 45 # Store the count of font_family tokens
TEXT_TOKEN_COUNT = 46 # Store the count of text tokens
class MoreOptions:
G = 0
ALIGNMENT_A = 1
ALIGNMENT_K1 = 2
ALIGNMENT_K2 = 3
ALIGNMENT_IX = 4
class OriginalColors:
# Support up to 18 color values
COLOR_0 = 0
COLOR_1 = 1
COLOR_2 = 2
COLOR_3 = 3
COLOR_4 = 4
COLOR_5 = 5
COLOR_6 = 6
COLOR_7 = 7
COLOR_8 = 8
COLOR_9 = 9
COLOR_10 = 10
COLOR_11 = 11
COLOR_12 = 12
COLOR_13 = 13
COLOR_14 = 14
COLOR_15 = 15
COLOR_16 = 16
COLOR_17 = 17
COLOR_18 = 18 # Added
COLOR_19 = 19 # Added
COLOR_20 = 20 # Added
COLOR_21 = 21 # Added
COLOR_22 = 22 # Added
COLOR_23 = 23 # Added
COLOR_24 = 24 # Added
COLOR_25 = 25 # Added
COLOR_26 = 26 # Added
COLOR_27 = 27 # Added
COLOR_28 = 28 # Added
COLOR_29 = 29 # Added
COLOR_30 = 30 # Added
COLOR_31 = 31 # Added
COLOR_32 = 32 # Added
COLOR_33 = 33 # Added
COLOR_34 = 34 # Added
COLOR_35 = 35 # Added
COLOR_36 = 36 # Added
COLOR_37 = 37 # Added
COLOR_38 = 38 # Added
COLOR_39 = 39 # Added
COLOR_40 = 40 # Added
COLOR_41 = 41 # Added
COLOR_42 = 42 # Added
COLOR_43 = 43 # Added
COLOR_44 = 44 # Added
COLOR_45 = 45 # Added
COLOR_46 = 46 # Added
COUNT = 47 # Store the count of colors
class FontSize:
SIZE = 0
class Text:
TEXT_TOKEN_0 = 0
TEXT_TOKEN_1 = 1
TEXT_TOKEN_2 = 2
TEXT_TOKEN_3 = 3
TEXT_TOKEN_4 = 4
TEXT_TOKEN_5 = 5
TEXT_TOKEN_6 = 6
TEXT_TOKEN_7 = 7
TEXT_TOKEN_8 = 8
TEXT_TOKEN_9 = 9
TEXT_TOKEN_COUNT = 10
class Ca:
VALUE = 0
class Justify:
VALUE = 0
class Tracking:
VALUE = 0
class LineHeight:
VALUE = 0
class LetterSpacing:
VALUE = 0
class FillColor:
R = 0
G = 1
B = 2
class G:
VALUE = 0
class Alignment:
A = 0
class AlignmentK:
VALUE1 = 0
VALUE2 = 1
class AlignmentIx:
VALUE = 0
class GradientFill:
OPACITY = 0
FILL_RULE = 1
START_POINT_X = 2
START_POINT_Y = 3
END_POINT_X = 4
END_POINT_Y = 5
GRADIENT_TYPE = 6
HIGHLIGHT_LENGTH = 7
HIGHLIGHT_ANGLE = 8
COLOR_POINTS = 9
# Original colors (up to 12 values for RGBA * 3 color stops)
ORIGINAL_COLOR_0 = 10
ORIGINAL_COLOR_1 = 11
ORIGINAL_COLOR_2 = 12
ORIGINAL_COLOR_3 = 13
ORIGINAL_COLOR_4 = 14
ORIGINAL_COLOR_5 = 15
ORIGINAL_COLOR_6 = 16
ORIGINAL_COLOR_7 = 17
ORIGINAL_COLOR_8 = 18
ORIGINAL_COLOR_9 = 19
ORIGINAL_COLOR_10 = 20
ORIGINAL_COLOR_11 = 21
ORIGINAL_COLOR_12 = 22 # Added
ORIGINAL_COLOR_13 = 23 # Added
ORIGINAL_COLOR_14 = 24 # Added
ORIGINAL_COLOR_15 = 25 # Added
ORIGINAL_COLOR_16 = 26 # Added
ORIGINAL_COLOR_17 = 27 # Added
ORIGINAL_COLOR_18 = 28 # Added
ORIGINAL_COLOR_19 = 29 # Added
ORIGINAL_COLOR_20 = 30 # Added
ORIGINAL_COLOR_21 = 31 # Added
ORIGINAL_COLOR_22 = 32 # Added
ORIGINAL_COLOR_23 = 33 # Added
class GradientStroke:
OPACITY = 0
WIDTH = 1
LINE_CAP = 2
LINE_JOIN = 3
MITER_LIMIT = 4
ML2 = 5
ML2_IX = 6
START_POINT_X = 7
START_POINT_Y = 8
END_POINT_X = 9
END_POINT_Y = 10
GRADIENT_TYPE = 11
HIGHLIGHT_LENGTH = 12
HIGHLIGHT_ANGLE = 13
COLOR_POINTS = 14
# Original colors (up to 18 values for RGBA * 4.5 color stops)
ORIGINAL_COLOR_0 = 15
ORIGINAL_COLOR_1 = 16
ORIGINAL_COLOR_2 = 17
ORIGINAL_COLOR_3 = 18
ORIGINAL_COLOR_4 = 19
ORIGINAL_COLOR_5 = 20
ORIGINAL_COLOR_6 = 21
ORIGINAL_COLOR_7 = 22
ORIGINAL_COLOR_8 = 23
ORIGINAL_COLOR_9 = 24
ORIGINAL_COLOR_10 = 25
ORIGINAL_COLOR_11 = 26
ORIGINAL_COLOR_12 = 27
ORIGINAL_COLOR_13 = 28
ORIGINAL_COLOR_14 = 29
ORIGINAL_COLOR_15 = 30
ORIGINAL_COLOR_16 = 31
ORIGINAL_COLOR_17 = 32
ORIGINAL_COLOR_18 = 33 # Added
ORIGINAL_COLOR_19 = 34 # Added
ORIGINAL_COLOR_20 = 35 # Added
ORIGINAL_COLOR_21 = 36 # Added
ORIGINAL_COLOR_22 = 37 # Added
ORIGINAL_COLOR_23 = 38 # Added
class StartPointCmd:
X = 0
Y = 1
class EndPointCmd:
X = 0
Y = 1
class OriginalColorsCmd:
COLOR_1 = 0
COLOR_2 = 1
COLOR_3 = 2
COLOR_4 = 3
COLOR_5 = 4
COLOR_6 = 5
COLOR_7 = 6
COLOR_8 = 7
COLOR_9 = 8
COLOR_10 = 9
COLOR_11 = 10
COLOR_12 = 11
class ColorPoints:
VALUE = 0
class Effect:
TYPE = 0
INDEX = 1
NP = 2
ENABLED = 3
class LayerEffect: # Add new Index class
INDEX = 0
VALUE = 1
class Dropdown:
INDEX = 0
VALUE = 1
class NO_VALUE:
INDEX = 0
VALUE = 1
class Ignored:
INDEX = 0
VALUE = 1
class Slider:
INDEX = 0
VALUE = 1
class Color:
NAME_INDEX = 0 # Using NAME_INDEX to avoid confusion with INDEX
INDEX = 1
R = 2
G = 3
B = 4
class Merge:
# merge命令的name会存储在string_params中
pass
class MergeMode:
MODE = 0
class Mask:
INDEX = 0
INV = 1
MODE = 2 # mode will be stored as string
# nm will be stored in string_params
class MaskPt:
A = 0
IX = 1
class MaskPtK:
C = 0 # closed
class MaskPtKValues: # For i, o, v
V1 = 0
V2 = 1
V3 = 2
V4 = 3
V5 = 4
V6 = 5
V7 = 6
V8 = 7
V9 = 8
V10 = 9
V11 = 10
V12 = 11
V13 = 12
V14 = 13
V15 = 14
V16 = 15
V17 = 16
V18 = 17
V19 = 18
V20 = 19
COUNT = 20
class MaskO: # For mask_o
A = 0
K = 1
IX = 2
class MaskX: # For mask_x
A = 0
K = 1
IX = 2
class MaskPtKeyframe:
INDEX = 0
T = 1
class MaskPtKfI:
X = 0
Y = 1
class MaskPtKfO:
X = 0
Y = 1
class MaskPtKfShape:
INDEX = 0
C = 1 # closed
class MaskPtKfShapeValues: # For shape_i, shape_o, shape_v
V1 = 0
V2 = 1
V3 = 2
V4 = 3
V5 = 4
V6 = 5
V7 = 6
V8 = 7
V9 = 8
V10 = 9
V11 = 10
V12 = 11
V13 = 12
V14 = 13
V15 = 14
V16 = 15
V17 = 16
V18 = 17
V19 = 18
V20 = 19
COUNT = 20 # Add this to store the count
class TrPosition:
X = 0
Y = 1
class TrAnchor:
X = 0
Y = 1
class TrRotation:
VALUE = 0
class TrStartOpacity:
VALUE = 0
class TrEndOpacity:
VALUE = 0
class ZigZag:
NAME_INDEX = 0 # Will store in string_params
IX = 1
class Frequency:
VALUE = 0
class Amplitude:
VALUE = 0
class PointType:
VALUE = 0
class Animator:
# nm will be stored in string_params
pass
class RangeSelector:
T = 0
R = 1
B = 2
SH = 3
RN = 4
class RangeStart:
A = 0
class RangeStartKeyframe:
T = 0
S = 1
I_X = 2
I_Y = 3
O_X = 4
O_Y = 5
class Amount:
A = 0
K = 1
IX = 2
class MaxEase:
A = 0
K = 1
IX = 2
class MinEase:
A = 0
K = 1
IX = 2
class Radius:
VALUE = 0
class RangeEnd:
A = 0
class RangeEndKeyframe:
T = 0
S = 1
I_X = 2
I_Y = 3
O_X = 4
O_Y = 5
#class RangeOffset:
# A = 0
class RangeOffsetKeyframe:
T = 0
S = 1
I_X = 2
I_Y = 3
O_X = 4
O_Y = 5
class SM:
A = 0
K = 1
IX = 2
class OpacityAnimators:
A = 0
K = 1
IX = 2
class ScaleAnimators:
A = 0
K_X = 1
K_Y = 2
K_Z = 3
IX = 4
class RotationAnimators:
A = 0
K = 1
IX = 2
class PositionAnimators:
A = 0
K_X = 1
K_Y = 2
K_Z = 3
IX = 4
class TrackingAnimators:
A = 0
K = 1
IX = 2
class Dashes:
# Container command, no parameters
pass
class Dash:
TYPE = 0 # Store type as numeric (0 for "d", 1 for "g", 2 for "o")
LENGTH = 1 # dash length
V_IX = 2 # v_ix parameter
class DashAnimated:
TYPE = 0 # Store type as numeric
V_IX = 1 # v_ix parameter
class DashKeyframe:
T = 0
S = 1
I_X = 2
I_Y = 3
O_X = 4
O_Y = 5
class DashOffset:
O = 0 # offset value
# Parameter dimension (fixed length for all commands)
PARAM_DIM = 50
PAD_VAL = -2001
def __init__(self, commands, params, seq_len=None, PAD_VAL=-2001, flattened_data=None):
"""Initialize LottieTensor"""
self.PAD_VAL = PAD_VAL
self.commands = commands.reshape(-1, 1).long()
self.params = params.float()
self.seq_len = torch.tensor(len(commands)) if seq_len is None else seq_len
self.sos_token = torch.tensor([LottieTensor.CMD_SOS]).unsqueeze(-1).long()
self.eos_token = self.pad_token = torch.tensor([LottieTensor.CMD_EOS]).unsqueeze(-1).long()
# Store original string values
self.string_params = {}
@staticmethod
def _parse_easing_value(value_str: str) -> int:
"""Helper function to parse easing values and return as int"""
if not value_str:
return 0
# Handle quoted format "0.833 0.833 0.833"
if value_str.startswith('"') and value_str.endswith('"'):
value_str = value_str[1:-1]
# Handle space-separated (take first value)
parts = value_str.split()
if parts:
try:
return round(float(parts[0]))
except ValueError:
return 0
# Try to parse as plain number
try:
return round(float(value_str))
except ValueError:
return 0
@staticmethod
def _parse_multi_easing_values(value_str: str) -> List[int]:
"""Parse multi-dimensional easing values like '0.3 0.3 0.3' and return as int list"""
values = [0, 0, 0]
if not value_str:
return values
# Handle quoted format "0.3 0.3 0.3"
if value_str.startswith('"') and value_str.endswith('"'):
value_str = value_str[1:-1]
# Parse space-separated values
parts = value_str.split()
for i, part in enumerate(parts[:3]):
try:
values[i] = round(float(part))
except ValueError:
values[i] = 0
# If only one value provided, use it for all dimensions
if len(parts) == 1 and parts[0]:
try:
val = round(float(parts[0]))
values = [val, val, val]
except ValueError:
pass
return values
@staticmethod
def from_sequence(sequence: str) -> 'LottieTensor':
"""Convert a string sequence to LottieTensor"""
raw_lines = [line.strip() for line in sequence.strip().split('\n') if line.strip()]
# Process each line and extract all commands
lines = []
for raw_line in raw_lines:
# Find all commands in the line (commands are enclosed in parentheses)
import re
commands_in_line = re.findall(r'\([^)]+\)', raw_line)
lines.extend(commands_in_line)
commands = []
params_list = []
string_params = {}
current_context = None
for idx, line in enumerate(lines):
if not (line.startswith('(') and line.endswith(')')):
continue
# Extract command name and attributes
content = line[1:-1].strip()
# Handle end tags
if content.startswith('/'):
cmd = content
if cmd in LottieTensor.COMMAND_TO_IDX:
commands.append(LottieTensor.COMMAND_TO_IDX[cmd])
params_list.append([LottieTensor.PAD_VAL] * LottieTensor.PARAM_DIM)
# Reset context for certain end tags
if cmd in ["/position", "/scale", "/opacity", "/rotation", "/keyframe", "/anchor", "/path", "/width_animated",
"/position_x", "/position_y", "/position_z", "/tm", "/range_start", "/range_end", "/animator_properties",
"/start", "/end", "/offset", "/color_animated", "/rounded"]:
current_context = None
continue
# Parse command and attributes
parts = content.split(' ', 1)
cmd = parts[0]
# Handle quoted commands
if cmd.startswith('"') and cmd.endswith('"'):
cmd = cmd
attrs_str = parts[1] if len(parts) > 1 else ""
# Update context - modified to track path animation, width animation, and individual position components
if cmd in ["position", "scale", "opacity", "rotation", "anchor"]:
current_context = cmd
elif cmd in ["position_x", "position_y", "position_z"]:
# Check if animated
if "animated" in attrs_str and "true" in attrs_str.lower():
current_context = cmd
elif cmd == "path" and "animated" in attrs_str:
current_context = "path"
elif cmd == "width_keyframe":
current_context = "width"
elif cmd == "start" and "animated" in attrs_str and "true" in attrs_str.lower():
current_context = "trim_start"
elif cmd == "end" and "animated" in attrs_str and "true" in attrs_str.lower():
current_context = "trim_end"
elif cmd == "offset" and "animated" in attrs_str and "true" in attrs_str.lower():
current_context = "trim_offset"
elif cmd == "mask_x":
# Check if animated (a=1)
mask_x_attrs = LottieTensor._parse_attributes(attrs_str)
if float(mask_x_attrs.get("a", 0)) > 0.5:
current_context = "mask_x"
elif cmd == "scale_animators":
# Check if animated
scale_animators_attrs = LottieTensor._parse_attributes(attrs_str)
if float(scale_animators_attrs.get("a", 0)) > 0.5:
current_context = "scale_animators"
elif cmd == "rotation_animators":
# Check if animated
rotation_animators_attrs = LottieTensor._parse_attributes(attrs_str)
if float(rotation_animators_attrs.get("a", 0)) > 0.5:
current_context = "rotation_animators"
elif cmd == "opacity_animators":
# Check if animated
opacity_animators_attrs = LottieTensor._parse_attributes(attrs_str)
if float(opacity_animators_attrs.get("a", 0)) > 0.5:
current_context = "opacity_animators"
elif cmd == "position_animators":
# Check if animated
position_animators_attrs = LottieTensor._parse_attributes(attrs_str)
if float(position_animators_attrs.get("a", 0)) > 0.5:
current_context = "position_animators"
elif cmd == "tracking_animators":
# Check if animated
tracking_animators_attrs = LottieTensor._parse_attributes(attrs_str)
if float(tracking_animators_attrs.get("a", 0)) > 0.5:
current_context = "tracking_animators"
elif cmd == "rect_rounded" and "animated" in attrs_str and "true" in attrs_str.lower():
current_context = "rect_rounded"
if cmd not in LottieTensor.COMMAND_TO_IDX:
continue
cmd_idx = LottieTensor.COMMAND_TO_IDX[cmd]
cmd_key = f"{len(commands)}" # Use command index as key
commands.append(cmd_idx)
# Initialize parameters
params = [LottieTensor.PAD_VAL] * LottieTensor.PARAM_DIM
attrs = LottieTensor._parse_attributes(attrs_str)
# Parse parameters based on command type
if cmd_idx == LottieTensor.CMD_ANIMATION:
# Store original string values
#string_params[f"{cmd_key}_v"] = attrs.get("v", "5.12.1")
#string_params[f"{cmd_key}_nm"] = attrs.get("nm", "Comp 1")
#string_params[f"{cmd_key}_markers"] = attrs.get("markers", "[]")
#string_params[f"{cmd_key}_props"] = attrs.get("props", "{}")
params[LottieTensor.Index.Animation.FR] = round(float(attrs.get("fr", 60)))
params[LottieTensor.Index.Animation.IP] = round(float(attrs.get("ip", 0)))
params[LottieTensor.Index.Animation.OP] = round(float(attrs.get("op", 150)))
params[LottieTensor.Index.Animation.W] = round(float(attrs.get("w", 512)))
params[LottieTensor.Index.Animation.H] = round(float(attrs.get("h", 512)))
params[LottieTensor.Index.Animation.DDD] = int(attrs.get("ddd", 0))
#eos token
#print("params", params)
elif cmd_idx == LottieTensor.CMD_LAYER:
# Store layer name and string attributes
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Layer")
# 必需的属性
#params[LottieTensor.Index.Layer.INDEX] = float(attrs.get("index", 0))
params[LottieTensor.Index.Layer.INDEX] = LottieTensor._index_clamp_value(round(float(attrs.get("index", "0")))) # index 0-100
#params[LottieTensor.Index.Layer.IN_POINT] = float(attrs.get("in_point", 0))
#params[LottieTensor.Index.Layer.OUT_POINT] = float(attrs.get("out_point", 60))
params[LottieTensor.Index.Layer.IN_POINT] = LottieTensor._clamp_value(round(float(attrs.get("in_point", 0)))) #ip -2000-2000
params[LottieTensor.Index.Layer.OUT_POINT] = LottieTensor._clamp_value(round(float(attrs.get("out_point", 60)))) #op -2000-2000
params[LottieTensor.Index.Layer.START_TIME] = LottieTensor._clamp_value(round(float(attrs.get("start_time", 0)))) #st -2000-2000
# 可选属性 - 只在存在时解析，不设置默认值
if "ddd" in attrs:
params[LottieTensor.Index.Layer.DDD] = float(attrs.get("ddd")) #0-1
if "hd" in attrs:
params[LottieTensor.Index.Layer.HD] = 1.0 if attrs.get("hd").lower() == "true" else 0.0 # 0-1
if "cp" in attrs:
params[LottieTensor.Index.Layer.CP] = 1.0 if attrs.get("cp").lower() == "true" else 0.0 # 0-1
if "hasMask" in attrs:
params[LottieTensor.Index.Layer.HAS_MASK] = 1.0 if attrs.get("hasMask").lower() == "true" else 0.0 # 0-1
if "ao" in attrs:
params[LottieTensor.Index.Layer.AO] = int(attrs.get("ao")) # 0-1
if "tt" in attrs:
params[LottieTensor.Index.Layer.TT] = int(attrs.get("tt")) # 0-4
if "tp" in attrs:
params[LottieTensor.Index.Layer.TP] = int(attrs.get("tp")) #0-100以内
if "td" in attrs:
params[LottieTensor.Index.Layer.TD] = int(attrs.get("td")) #0-1
if "ct" in attrs:
params[LottieTensor.Index.Layer.CT] = int(attrs.get("ct")) #0-1
elif cmd_idx == LottieTensor.CMD_NULL_LAYER:
# Store layer name and string attributes
#string_params[f"{cmd_key}_name"] = attrs.get("name", "null_layer")
#params[LottieTensor.Index.NullLayer.INDEX] = int(attrs.get("index", 0))
params[LottieTensor.Index.NullLayer.INDEX] = LottieTensor._index_clamp_value(round(float(attrs.get("index", 0))))
#params[LottieTensor.Index.NullLayer.IN_POINT] = float(attrs.get("in_point", 0))
#params[LottieTensor.Index.NullLayer.OUT_POINT] = float(attrs.get("out_point", 60))
params[LottieTensor.Index.NullLayer.IN_POINT] = LottieTensor._clamp_value(round(float(attrs.get("in_point", 0))))
params[LottieTensor.Index.NullLayer.OUT_POINT] = LottieTensor._clamp_value(round(float(attrs.get("out_point", 60))))
params[LottieTensor.Index.NullLayer.START_TIME] = LottieTensor._clamp_value(round(float(attrs.get("start_time", 0))))
if "hd" in attrs:
params[LottieTensor.Index.PrecompLayer.HD] = 1.0 if attrs.get("hd").lower() == "true" else 0.0
if "cp" in attrs:
params[LottieTensor.Index.PrecompLayer.CP] = 1.0 if attrs.get("cp").lower() == "true" else 0.0
if "hasMask" in attrs:
params[LottieTensor.Index.PrecompLayer.HAS_MASK] = 1.0 if attrs.get("hasMask").lower() == "true" else 0.0
if "ao" in attrs:
params[LottieTensor.Index.PrecompLayer.AO] = int(attrs.get("ao"))
if "tt" in attrs:
params[LottieTensor.Index.PrecompLayer.TT] = int(attrs.get("tt"))
if "tp" in attrs:
params[LottieTensor.Index.PrecompLayer.TP] = int(attrs.get("tp"))
if "td" in attrs:
params[LottieTensor.Index.PrecompLayer.TD] = int(attrs.get("td"))
elif cmd_idx == LottieTensor.CMD_PRECOMP_LAYER:
# Parse name more carefully to handle names with spaces
name = attrs.get("name", "precomp_layer")
# If name wasn't properly captured (e.g., due to spaces), try regex
if name == "precomp_layer" or not name:
# Look for name="..." pattern in the original attrs_str
import re
name_match = re.search(r'name="([^"]*)"', attrs_str)
if name_match:
name = name_match.group(1)
else:
# Try without quotes
name_match = re.search(r'name=([^\s]+)', attrs_str)
if name_match:
name = name_match.group(1)
else:
name = "precomp_layer"
#string_params[f"{cmd_key}_name"] = name
# Parse numeric parameters
#params[LottieTensor.Index.PrecompLayer.INDEX] = float(attrs.get("index", 0))
params[LottieTensor.Index.PrecompLayer.INDEX] = LottieTensor._index_clamp_value(round(float(attrs.get("index", 0))))
#params[LottieTensor.Index.PrecompLayer.IN_POINT] = float(attrs.get("in_point", 0))
#params[LottieTensor.Index.PrecompLayer.OUT_POINT] = float(attrs.get("out_point", 120))
params[LottieTensor.Index.PrecompLayer.IN_POINT] = LottieTensor._clamp_value(round(float(attrs.get("in_point", 0))))
params[LottieTensor.Index.PrecompLayer.OUT_POINT] = LottieTensor._clamp_value(round(float(attrs.get("out_point", 120))))
params[LottieTensor.Index.PrecompLayer.START_TIME] = LottieTensor._clamp_value(round(float(attrs.get("start_time", 0))))
# 可选属性 - 只在存在时解析，不设置默认值
if "h" in attrs:
params[LottieTensor.Index.PrecompLayer.H] = round(float(attrs.get("h"))) #0-2000
if "w" in attrs:
params[LottieTensor.Index.PrecompLayer.W] = round(float(attrs.get("w"))) #0-2000
if "ddd" in attrs:
params[LottieTensor.Index.PrecompLayer.DDD] = int(attrs.get("ddd")) #0-1
if "hd" in attrs:
params[LottieTensor.Index.PrecompLayer.HD] = 1.0 if attrs.get("hd").lower() == "true" else 0.0 #0-1
if "cp" in attrs:
params[LottieTensor.Index.PrecompLayer.CP] = 1.0 if attrs.get("cp").lower() == "true" else 0.0 #0-1
if "hasMask" in attrs:
params[LottieTensor.Index.PrecompLayer.HAS_MASK] = 1.0 if attrs.get("hasMask").lower() == "true" else 0.0 #0-1
if "ao" in attrs:
params[LottieTensor.Index.PrecompLayer.AO] = int(attrs.get("ao")) #0-1
if "tt" in attrs:
params[LottieTensor.Index.PrecompLayer.TT] = int(attrs.get("tt"))
if "tp" in attrs:
params[LottieTensor.Index.PrecompLayer.TP] = int(attrs.get("tp"))
if "td" in attrs:
params[LottieTensor.Index.PrecompLayer.TD] = int(attrs.get("td"))
if "ct" in attrs:
params[LottieTensor.Index.PrecompLayer.CT] = int(attrs.get("ct"))
elif cmd_idx == LottieTensor.CMD_TEXT_LAYER:
# 存储name
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Text Layer")
#params[LottieTensor.Index.TextLayer.INDEX] = float(attrs.get("index", 0))
params[LottieTensor.Index.TextLayer.INDEX] = LottieTensor._index_clamp_value(round(float(attrs.get("index", 0))))
#params[LottieTensor.Index.TextLayer.IN_POINT] = float(attrs.get("in_point", 0))
#params[LottieTensor.Index.TextLayer.OUT_POINT] = float(attrs.get("out_point", 60))
params[LottieTensor.Index.TextLayer.IN_POINT] = LottieTensor._clamp_value(round(float(attrs.get("in_point", 0))))
params[LottieTensor.Index.TextLayer.OUT_POINT] = LottieTensor._clamp_value(round(float(attrs.get("out_point", 60))))
params[LottieTensor.Index.TextLayer.START_TIME] = LottieTensor._clamp_value(round(float(attrs.get("start_time", 0))))
params[LottieTensor.Index.TextLayer.HAS_MASK] = 1.0 if attrs.get("hasMask", "false").lower() == "true" else 0.0 # 新增
elif cmd_idx == LottieTensor.CMD_SOLID_LAYER:
# Store string attributes
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Solid Layer")
#string_params[f"{cmd_key}_color"] = attrs.get("color", "#000000")
hex_color = attrs.get("color", "#00000000")
# Remove '#' if present
hex_color = hex_color.lstrip('#')
# Convert to RGB
r = int(hex_color[0:2], 16) if len(hex_color) >= 2 else 0
g = int(hex_color[2:4], 16) if len(hex_color) >= 4 else 0
b = int(hex_color[4:6], 16) if len(hex_color) >= 6 else 0
a = int(hex_color[6:8], 16) if len(hex_color) >= 8 else 0
# Store RGB values as separate parameters
params[LottieTensor.Index.SolidLayer.COLOR_R] = round(float(r))
params[LottieTensor.Index.SolidLayer.COLOR_G] = round(float(g))
params[LottieTensor.Index.SolidLayer.COLOR_B] = round(float(b))
params[LottieTensor.Index.SolidLayer.COLOR_A] = round(float(a)) #这里的color都是0-255吧
#params[LottieTensor.Index.SolidLayer.INDEX] = float(attrs.get("index", 0))
params[LottieTensor.Index.SolidLayer.INDEX] = LottieTensor._index_clamp_value(round(float(attrs.get("index", 0))))
#params[LottieTensor.Index.SolidLayer.IN_POINT] = float(attrs.get("in_point", 0))
#params[LottieTensor.Index.SolidLayer.OUT_POINT] = float(attrs.get("out_point", 60))
params[LottieTensor.Index.SolidLayer.IN_POINT] = LottieTensor._clamp_value(round(float(attrs.get("in_point", 0))))
params[LottieTensor.Index.SolidLayer.OUT_POINT] = LottieTensor._clamp_value(round(float(attrs.get("out_point", 60))))
params[LottieTensor.Index.SolidLayer.START_TIME] = LottieTensor._clamp_value(round(float(attrs.get("start_time", 0))))
params[LottieTensor.Index.SolidLayer.WIDTH] = LottieTensor._clamp_value(round(float(attrs.get("width", 512))))
params[LottieTensor.Index.SolidLayer.HEIGHT] = LottieTensor._clamp_value(round(float(attrs.get("height", 512))))
params[LottieTensor.Index.SolidLayer.HAS_MASK] = 1.0 if attrs.get("hasMask", "false").lower() == "true" else 0.0
elif cmd_idx in [LottieTensor.CMD_FONTS, LottieTensor.CMD_FONTS_END, LottieTensor.CMD_CHARS, LottieTensor.CMD_CHARS_END, LottieTensor.CMD_CHAR_SHAPES, LottieTensor.CMD_CHAR_SHAPES_END, LottieTensor.CMD_TEXT_KEYFRAMES, LottieTensor.CMD_MORE_OPTIONS, LottieTensor.CMD_OPACITY_ANIMATED_END, LottieTensor.CMD_END_END, LottieTensor.CMD_START_END, LottieTensor.CMD_OFFSET_END, LottieTensor.CMD_OPACITY_ANIMATORS_END]:
pass
elif cmd_idx == LottieTensor.CMD_TEXT_KEYFRAME:
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
# Parse all attributes from text_keyframe
params[LottieTensor.Index.TextKeyframe.T] = LottieTensor._clamp_value(round(float(attrs.get("t", 0))))
# Parse stroke_width as a numeric parameter
stroke_width_str = attrs.get("stroke_width", "0")
try:
params[LottieTensor.Index.TextKeyframe.STROKE_WIDTH] = round(float(stroke_width_str))
except ValueError:
params[LottieTensor.Index.TextKeyframe.STROKE_WIDTH] = 0
# Parse offset as a boolean (1.0 for true, 0.0 for false)
offset_str = attrs.get("offset", "false")
params[LottieTensor.Index.TextKeyframe.OFFSET] = 1 if offset_str.lower() == "true" else 0.0
# Parse wrap_position array (新增)
wrap_position_str = attrs.get("wrap_position", "")
if wrap_position_str:
if wrap_position_str.startswith("[") and wrap_position_str.endswith("]"):
wrap_position_str = wrap_position_str[1:-1]
pos_parts = wrap_position_str.split(",")
if len(pos_parts) >= 2:
try:
params[LottieTensor.Index.TextKeyframe.WRAP_POSITION_X] = round(float(pos_parts[0].strip()))
params[LottieTensor.Index.TextKeyframe.WRAP_POSITION_Y] = round(float(pos_parts[1].strip()))
except ValueError:
pass
# Parse wrap_size array (新增)
wrap_size_str = attrs.get("wrap_size", "")
if wrap_size_str:
if wrap_size_str.startswith("[") and wrap_size_str.endswith("]"):
wrap_size_str = wrap_size_str[1:-1]
size_parts = wrap_size_str.split(",")
if len(size_parts) >= 2:
try:
params[LottieTensor.Index.TextKeyframe.WRAP_SIZE_X] = round(float(size_parts[0].strip()))
params[LottieTensor.Index.TextKeyframe.WRAP_SIZE_Y] = round(float(size_parts[1].strip()))
except ValueError:
pass
# Store all text_keyframe attributes in string_params
#string_params[f"{cmd_key}_font_size"] = attrs.get("font_size", "12")
#string_params[f"{cmd_key}_font_family"] = attrs.get("font_family", "")
#string_params[f"{cmd_key}_text"] = attrs.get("text", "")
#string_params[f"{cmd_key}_ca"] = attrs.get("ca", "1")
#string_params[f"{cmd_key}_justify"] = attrs.get("justify", "0")
#string_params[f"{cmd_key}_tracking"] = attrs.get("tracking", "0")
#string_params[f"{cmd_key}_line_height"] = attrs.get("line_height", "0")
#string_params[f"{cmd_key}_letter_spacing"] = attrs.get("letter_spacing", "0")
params[LottieTensor.Index.TextKeyframe.FONT_SIZE] = round(float(attrs.get("font_size", 12)))
params[LottieTensor.Index.TextKeyframe.CA] = int(attrs.get("ca", 1))
params[LottieTensor.Index.TextKeyframe.JUSTIFY] = int(attrs.get("justify", 0))
params[LottieTensor.Index.TextKeyframe.TRACKING] = int(float(attrs.get("tracking", 0)))
params[LottieTensor.Index.TextKeyframe.LINE_HEIGHT] = round(float(attrs.get("line_height", 0)))
params[LottieTensor.Index.TextKeyframe.LETTER_SPACING] = int(float(attrs.get("letter_spacing", 0)))
font_family = attrs.get("font_family", "")
if font_family:
font_family_tokens = LottieTensor.tokenizer.encode(font_family, add_special_tokens=False)
# Store up to 10 tokens
for i, token in enumerate(font_family_tokens[:10]):
params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START + i] = int(token)
params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT] = int(len(font_family_tokens[:10]))
else:
params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT] = 0
# Tokenize text
text = attrs.get("text", "")
if text:
text_tokens = LottieTensor.tokenizer.encode(text, add_special_tokens=False)
# Store up to 15 tokens
for i, token in enumerate(text_tokens[:15]):
params[LottieTensor.Index.TextKeyframe.TEXT_TOKENS_START + i] = int(token)
params[LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT] = int(len(text_tokens[:15]))
else:
params[LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT] = 0
# Parse fill_color array
fill_color_str = attrs.get("fill_color", "[0,0,0]")
if fill_color_str.startswith("[") and fill_color_str.endswith("]"):
fill_color_str = fill_color_str[1:-1]
color_parts = fill_color_str.split(",")
#string_params[f"{cmd_key}_fill_color"] = ",".join([p.strip() for p in color_parts])
if len(color_parts) >= 3:
params[LottieTensor.Index.TextKeyframe.FILL_COLOR_R] = round(float(color_parts[0].strip()) * 255)
params[LottieTensor.Index.TextKeyframe.FILL_COLOR_G] = round(float(color_parts[1].strip()) * 255)
params[LottieTensor.Index.TextKeyframe.FILL_COLOR_B] = round(float(color_parts[2].strip()) * 255)
# Parse stroke_color array (if present)
stroke_color_str = attrs.get("stroke_color", "")
if stroke_color_str:
if stroke_color_str.startswith("[") and stroke_color_str.endswith("]"):
stroke_color_str = stroke_color_str[1:-1]
color_parts = stroke_color_str.split(",")
if len(color_parts) >= 3:
params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_R] = round(float(color_parts[0].strip()) * 255)
params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_G] = round(float(color_parts[1].strip()) * 255)
params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_B] = round(float(color_parts[2].strip()) * 255)
else:
params[LottieTensor.Index.TextKeyframe.HAS_STROKE_COLOR] = 0
elif cmd_idx == LottieTensor.CMD_MORE_OPTIONS:
# Parse the entire more_options line
parts_list = attrs_str.split()
i = 0
while i < len(parts_list):
if parts_list[i] == "g" and i + 1 < len(parts_list):
params[LottieTensor.Index.MoreOptions.G] = round(float(parts_list[i + 1])) #1-4
i += 2
elif parts_list[i] == "alignment" and i + 1 < len(parts_list):
if parts_list[i + 1].startswith("a="):
params[LottieTensor.Index.MoreOptions.ALIGNMENT_A] = round(float(parts_list[i + 1].split("=")[1]))
i += 2
else:
i += 1
elif parts_list[i] == "alignment_k" and i + 2 < len(parts_list):
params[LottieTensor.Index.MoreOptions.ALIGNMENT_K1] = round(float(parts_list[i + 1]))
params[LottieTensor.Index.MoreOptions.ALIGNMENT_K2] = round(float(parts_list[i + 2]))
i += 3
elif parts_list[i] == "alignment_ix" and i + 1 < len(parts_list):
params[LottieTensor.Index.MoreOptions.ALIGNMENT_IX] = round(float(parts_list[i + 1]))
i += 2
else:
i += 1
elif cmd_idx == LottieTensor.CMD_REFERENCE_ID:
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
# Extract reference_id from attrs_str
ref_id_match = re.search(r'"([^"]*)"', attrs_str)
if ref_id_match:
reference_id = ref_id_match.group(1)
else:
# Try without quotes
parts = attrs_str.strip().split()
if parts:
reference_id = parts[0]
else:
reference_id = "comp_0"
# Tokenize reference_id
id_tokens = LottieTensor.tokenizer.encode(reference_id, add_special_tokens=False)[:10] # Limit to 10 tokens
for i, token_id in enumerate(id_tokens):
if i < 10:
params[LottieTensor.Index.ReferenceId.ID_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT] = int(len(id_tokens))
elif cmd_idx == LottieTensor.CMD_DIMENSIONS:
# 处理dimensions命令
params[LottieTensor.Index.Dimensions.WIDTH] = round(float(attrs.get("width", 512))) #0-2000
params[LottieTensor.Index.Dimensions.HEIGHT] = round(float(attrs.get("height", 512))) #0-2000
# 3. Modify the stroke parsing in from_sequence method:
elif cmd_idx == LottieTensor.CMD_STROKE:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Stroke")
# Check if color is animated
color_animated = attrs.get("color_animated", "false").lower() == "true"
params[LottieTensor.Index.Stroke.COLOR_ANIMATED] = 1.0 if color_animated else 0.0 # 0-1
if not color_animated:
# Parse static color and convert from 0-1 to 0-255 range
params[LottieTensor.Index.Stroke.R] = round(float(attrs.get("r", 0)) * 255) # 0-1 → 0-255
params[LottieTensor.Index.Stroke.G] = round(float(attrs.get("g", 0)) * 255) # 0-1 → 0-255
params[LottieTensor.Index.Stroke.B] = round(float(attrs.get("b", 0)) * 255) # 0-1 → 0-255
params[LottieTensor.Index.Stroke.A] = round(float(attrs.get("a", 1)) * 255) # 0-1 → 0-255
params[LottieTensor.Index.Stroke.COLOR_DIM] = int(attrs.get("color_dim", 4)) #3-4
params[LottieTensor.Index.Stroke.HAS_C_A] = 1.0 if attrs.get("has_c_a", "").lower() == "true" else 0.0 #0-1
params[LottieTensor.Index.Stroke.HAS_C_IX] = 1.0 if attrs.get("has_c_ix", "").lower() == "true" else 0.0 #0-1
params[LottieTensor.Index.Stroke.C_IX] = int(attrs.get("c_ix", 3)) #2-4
params[LottieTensor.Index.Stroke.BM] = int(attrs.get("bm", 0)) #0-1
params[LottieTensor.Index.Stroke.LC] = int(attrs.get("lc", 1)) #1-3
params[LottieTensor.Index.Stroke.LJ] = int(attrs.get("lj", 1)) #1-3
params[LottieTensor.Index.Stroke.ML] = int(float((attrs.get("ml", "4")))) #0-50
# Handle width or width_animated
if "width_animated" in attrs and attrs.get("width_animated", "").lower() == "true":
params[LottieTensor.Index.Stroke.WIDTH_ANIMATED] = 1.0
current_context = "width"
# ADD THIS: Append width_animated command after stroke
params_list.append(params)
commands.append(LottieTensor.CMD_WIDTH_ANIMATED) # Note: need to define this constant
params_list.append([LottieTensor.PAD_VAL] * LottieTensor.PARAM_DIM)
params = [LottieTensor.PAD_VAL] * LottieTensor.PARAM_DIM # Reset for next command
else:
params[LottieTensor.Index.Stroke.WIDTH_ANIMATED] = 0.0
# Set context for color keyframes if animated
if color_animated:
current_context = "stroke_color"
# 4. Add parsing for color_keyframe command: keframe的s和i_x, i_y, o_x, o_y是不能越界的，越界需要去除
elif cmd_idx == LottieTensor.CMD_COLOR_KEYFRAME:
# Parse color keyframe parameters
params[LottieTensor.Index.Keyframe.T] = round(float(attrs.get("t", 0))) #-2000-2000
params[LottieTensor.Index.Keyframe.S1] = round(float(attrs.get("r", 0)) * 255) # Use S1 for R
params[LottieTensor.Index.Keyframe.S2] = round(float(attrs.get("g", 0)) * 255) # Use S2 for G
params[LottieTensor.Index.Keyframe.S3] = round(float(attrs.get("b", 0)) * 255) # Use S3 for B
params[LottieTensor.Index.Keyframe.E1] = round(float(attrs.get("a", 1)) * 255) # Use E1 for A
# Parse easing parameters
params[LottieTensor.Index.Keyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.Keyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.Keyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.Keyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_OPACITY_ANIMATED:
# Check if animated
if attrs.get("true", "false").lower() == "true" or "true" in attrs_str.lower():
current_context = "opacity_animated"
elif cmd_idx == LottieTensor.CMD_OPACITY_KEYFRAME:
# Parse opacity keyframe parameters
params[LottieTensor.Index.Keyframe.T] = round(float(attrs.get("t", 0)))
# Parse s parameter if present
if "s" in attrs:
s_str = attrs.get("s", "0").strip('"')
params[LottieTensor.Index.Keyframe.S1] = round(float(s_str))
# Parse easing parameters if present
if "i_x" in attrs or "i_y" in attrs or "o_x" in attrs or "o_y" in attrs:
params[LottieTensor.Index.Keyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.Keyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.Keyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.Keyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_WIDTH_KEYFRAME:
params[LottieTensor.Index.WidthKeyframe.T] = round(float(attrs.get("t", 0)))
# 处理s参数 - 改成乘以10
if "s" in attrs:
s_str = attrs.get("s", "0").strip('"')
try:
s_val = round(float(s_str) * 10)
s_val = max(0, min(10000, s_val)) # 裁剪
params[LottieTensor.Index.WidthKeyframe.S] = s_val
except ValueError:
params[LottieTensor.Index.WidthKeyframe.S] = 0.0
# easing参数保持不变
params[LottieTensor.Index.WidthKeyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.WidthKeyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.WidthKeyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.WidthKeyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_POSITION:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
elif attrs.get("separated", "").lower() == "true":
# Handle separated position (for 3D layers)
params[LottieTensor.Index.Transform.ANIMATED] = 2.0 # Use 2.0 to indicate separated
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse position values
pos_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
pos_parts.append(part)
except ValueError:
pass
if len(pos_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(pos_parts[0]))
if len(pos_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(pos_parts[1]))
if len(pos_parts) >= 3:
params[LottieTensor.Index.Transform.Z] = round(float(pos_parts[2]))
elif cmd_idx in [LottieTensor.CMD_POSITION_X, LottieTensor.CMD_POSITION_Y, LottieTensor.CMD_POSITION_Z]:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1
current_context = cmd # Set context to the specific component
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0
# Parse the value
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Transform.X] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_SCALE:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse scale values
scale_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
scale_parts.append(part)
except ValueError:
pass
if len(scale_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(scale_parts[0]))
if len(scale_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(scale_parts[1]))
if len(scale_parts) >= 3:
params[LottieTensor.Index.Transform.Z] = round(float(scale_parts[2]))
elif cmd_idx == LottieTensor.CMD_ROTATION:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse rotation value
rot_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
rot_parts.append(part)
except ValueError:
pass
if rot_parts:
val = round(float(rot_parts[0]))
# 添加裁剪：将 rotation 限制在 -720 到 720 范围内
val = max(-720, min(720, val % 360 if abs(val) > 720 else val))
params[LottieTensor.Index.Transform.X] = val
elif cmd_idx == LottieTensor.CMD_OPACITY:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse opacity value
op_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
op_parts.append(part)
except ValueError:
pass
if op_parts:
params[LottieTensor.Index.Transform.X] = round(float(op_parts[0]))
elif cmd_idx == LottieTensor.CMD_ANCHOR:
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse anchor values
anchor_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
anchor_parts.append(part)
except ValueError:
pass
if len(anchor_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(anchor_parts[0]))
if len(anchor_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(anchor_parts[1]))
if len(anchor_parts) >= 3:
params[LottieTensor.Index.Transform.Z] = round(float(anchor_parts[2]))
elif cmd_idx == LottieTensor.CMD_TM:
params[LottieTensor.Index.Tm.A] = int(attrs.get("a", 1))
#params[LottieTensor.Index.Tm.IX] = float(attrs.get("ix", 2))
# Check if animated
a_value = int(attrs.get("a", 1))
if a_value > 0.5:
current_context = "tm" # Set context for keyframes
else:
current_context = "tm_static" # Different context for static value
# Don't set special context for a=0, let value command be parsed normally
# Add value command parsing
elif cmd_idx == LottieTensor.CMD_VALUE:
# Parse the numeric value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Value.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_SKEW:
# Handle standalone skew command
# Parse the numeric value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
else:
params[LottieTensor.Index.SingleValue.VALUE] = 0
elif cmd_idx == LottieTensor.CMD_SKEW_AXIS:
# Handle standalone skew_axis command
# Parse the numeric value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
else:
params[LottieTensor.Index.SingleValue.VALUE] = 0
elif cmd_idx == LottieTensor.CMD_KEYFRAME:
params[LottieTensor.Index.Keyframe.T] = round(float(attrs.get("t", 0)))
# Check for h parameter (hold keyframe) - for ALL contexts, not just tm
h_value = attrs.get("h", "0")
is_hold = h_value == "1" or h_value.lower() == "true"
# Store h parameter flag using dedicated H_FLAG slot
if is_hold:
params[LottieTensor.Index.Keyframe.H_FLAG] = 1.0 # Using H_FLAG to store h flag
# Parse s parameter based on context - check if s exists
if "s" in attrs:
s_str = attrs.get("s", "0").strip('"')
s_parts = s_str.split()
if current_context in ["rotation", "opacity", "position_x", "position_y", "position_z", "tm", "width",
"trim_start", "trim_end", "trim_offset", "mask_x", "rotation_animators", "opacity_animators", "tracking_animators", "rect_rounded"]: # Added trim contexts
# For single-value properties, only use S1
if s_parts:
params[LottieTensor.Index.Keyframe.S1] = round(float(s_parts[0]))
elif current_context in ["position", "scale", "anchor", "scale_animators", "position_animators", "size"]:
# For position/scale/anchor, use x,y,z values
for i, part in enumerate(s_parts[:3]):
params[LottieTensor.Index.Keyframe.S1 + i] = round(float(part))
elif current_context == "path":
# Path keyframes don't have s parameter
pass
else:
# Default case
for i, part in enumerate(s_parts[:3]):
params[LottieTensor.Index.Keyframe.S1 + i] = round(float(part))
# Parse e parameter based on context - ADD THIS FOR TRIM CONTEXTS
if "e" in attrs:
e_str = attrs.get("e", "0").strip('"')
# Remove brackets if present
if e_str.startswith("[") and e_str.endswith("]"):
e_str = e_str[1:-1]
e_parts = e_str.split(',')
if current_context in ["trim_start", "trim_end", "trim_offset"]:
# For trim contexts, e is a single value
if e_parts:
params[LottieTensor.Index.Keyframe.E1] = round(float(e_parts[0].strip()))
elif current_context == "rotation":
# For rotation, e is a single value
if e_parts:
params[LottieTensor.Index.Keyframe.E1] = round(float(e_parts[0].strip()))
elif current_context == "scale":
# For scale, e has three values
for i, part in enumerate(e_parts[:3]):
params[LottieTensor.Index.Keyframe.E1 + i] = round(float(part.strip()))
# Add other contexts as needed
# Only parse easing parameters if not a hold keyframe
if not is_hold:
# Parse easing parameters based on context
if current_context in ["anchor", "size"]:
# For multi-dimensional properties, parse multiple easing values
i_x_values = LottieTensor._parse_multi_easing_values(attrs.get("i_x", "0"))
i_y_values = LottieTensor._parse_multi_easing_values(attrs.get("i_y", "0"))
o_x_values = LottieTensor._parse_multi_easing_values(attrs.get("o_x", "0"))
o_y_values = LottieTensor._parse_multi_easing_values(attrs.get("o_y", "0"))
# Store all three values - MULTIPLY BY 100 AND ROUND
params[LottieTensor.Index.Keyframe.I_X] = round(i_x_values[0] * 100)
params[LottieTensor.Index.Keyframe.I_X2] = round(i_x_values[1] * 100)
params[LottieTensor.Index.Keyframe.I_X3] = round(i_x_values[2] * 100)
params[LottieTensor.Index.Keyframe.I_Y] = round(i_y_values[0] * 100)
params[LottieTensor.Index.Keyframe.I_Y2] = round(i_y_values[1] * 100)
params[LottieTensor.Index.Keyframe.I_Y3] = round(i_y_values[2] * 100)
params[LottieTensor.Index.Keyframe.O_X] = round(o_x_values[0] * 100)
params[LottieTensor.Index.Keyframe.O_X2] = round(o_x_values[1] * 100)
params[LottieTensor.Index.Keyframe.O_X3] = round(o_x_values[2] * 100)
params[LottieTensor.Index.Keyframe.O_Y] = round(o_y_values[0] * 100)
params[LottieTensor.Index.Keyframe.O_Y2] = round(o_y_values[1] * 100)
params[LottieTensor.Index.Keyframe.O_Y3] = round(o_y_values[2] * 100)
else:
# For single-dimensional properties, parse single easing values - MULTIPLY BY 100 AND ROUND
params[LottieTensor.Index.Keyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0")) * 100))
params[LottieTensor.Index.Keyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0")) * 100))
params[LottieTensor.Index.Keyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0")) * 100))
params[LottieTensor.Index.Keyframe.O_Y] =round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0")) * 100))
# Parse to/ti parameters (always use TO1-TO3 and TI1-TI3 for their actual values)
to_str = attrs.get("to", "")
ti_str = attrs.get("ti", "")
if to_str:
to_values = LottieTensor._extract_array_values(to_str, 3)
for i in range(3):
params[LottieTensor.Index.Keyframe.TO1 + i] = to_values[i]
if ti_str:
ti_values = LottieTensor._extract_array_values(ti_str, 3)
for i in range(3):
params[LottieTensor.Index.Keyframe.TI1 + i] = ti_values[i]
# Parse e parameter based on context
if "e" in attrs:
e_str = attrs.get("e", "0").strip('"')
# Remove brackets if present
if e_str.startswith("[") and e_str.endswith("]"):
e_str = e_str[1:-1]
e_parts = e_str.split(',')
if current_context == "rotation":
# For rotation, e is a single value
if e_parts:
params[LottieTensor.Index.Keyframe.E1] = round(float(e_parts[0].strip()))
elif current_context == "scale":
# For scale, e has three values
for i, part in enumerate(e_parts[:3]):
params[LottieTensor.Index.Keyframe.E1 + i] = round(float(part.strip()))
# Add other contexts as needed
elif cmd_idx == LottieTensor.CMD_GROUP:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Group")
#string_params[f"{cmd_key}_mn"] = attrs.get("mn", "ADBE Vector Group")
params[LottieTensor.Index.Group.IX] = int(attrs.get("ix", 1)) #0-1000
params[LottieTensor.Index.Group.CIX] = int(attrs.get("cix", 2)) #1-10
params[LottieTensor.Index.Group.BM] = int(attrs.get("bm", 0)) #0-1
params[LottieTensor.Index.Group.HD] = 1.0 if attrs.get("hd", "false").lower() == "true" else 0.0 #0-1
params[LottieTensor.Index.Group.NP] = int(attrs.get("np", 0)) # 0-1000
elif cmd_idx == LottieTensor.CMD_PATH:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Path")
#string_params[f"{cmd_key}_mn"] = attrs.get("mn", "ADBE Vector Path") # Add mn
params[LottieTensor.Index.Path.IX] = int(attrs.get("ix", 1)) # 0-1000
params[LottieTensor.Index.Path.IND] = int(attrs.get("ind", 0))
params[LottieTensor.Index.Path.KS_IX] = int(attrs.get("ks_ix", 2))# 2-2
params[LottieTensor.Index.Path.CLOSED] = 1.0 if attrs.get("closed", "true").lower() == "true" else 0.0
params[LottieTensor.Index.Path.HD] = 1.0 if attrs.get("hd", "false").lower() == "true" else 0.0 # Add HD
# Track if path is animated
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Path.ANIMATED] = 1.0
current_context = "path"
else:
params[LottieTensor.Index.Path.ANIMATED] = 0.0
elif cmd_idx == LottieTensor.CMD_POINT:
params[LottieTensor.Index.Point.X] = round(float(attrs.get("x", 0)))
params[LottieTensor.Index.Point.Y] = round(float(attrs.get("y", 0)))
params[LottieTensor.Index.Point.IN_X] = round(float(attrs.get("in_x", 0)))
params[LottieTensor.Index.Point.IN_Y] = round(float(attrs.get("in_y", 0)))
params[LottieTensor.Index.Point.OUT_X] = round(float(attrs.get("out_x", 0)))
params[LottieTensor.Index.Point.OUT_Y] = round(float(attrs.get("out_y", 0)))
elif cmd_idx == LottieTensor.CMD_FILL:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Fill")
# Check if color is animated
color_animated = attrs.get("color_animated", "false").lower() == "true"
params[LottieTensor.Index.Fill.COLOR_ANIMATED] = 1.0 if color_animated else 0.0
# Check if opacity is animated
opacity_animated = attrs.get("opacity_animated", "false").lower() == "true"
params[LottieTensor.Index.Fill.OPACITY_ANIMATED] = 1.0 if opacity_animated else 0.0
# Parse color keyframes if animated
if color_animated:
c_kf_count = int(attrs.get("c_kf_count", 0))
color_keyframes = []
for i in range(c_kf_count):
kf = {
't': round(float(attrs.get(f"c_kf_{i}_t", 0))),
'r': round(float(attrs.get(f"c_kf_{i}_r", 0))*255),
'g': round(float(attrs.get(f"c_kf_{i}_g", 0))*255),
'b': round(float(attrs.get(f"c_kf_{i}_b", 0))*255),
# Add easing parameters for color keyframes (multiply by 100 and round)
'i_x': round(float(attrs.get(f"c_kf_{i}_i_x", 0)) * 100),
'i_y': round(float(attrs.get(f"c_kf_{i}_i_y", 0)) * 100),
'o_x': round(float(attrs.get(f"c_kf_{i}_o_x", 0)) * 100),
'o_y': round(float(attrs.get(f"c_kf_{i}_o_y", 0)) * 100)
}
color_keyframes.append(kf)
# Store in string_params as JSON
#string_params[f"{cmd_key}_color_keyframes"] = json.dumps(color_keyframes)
else:
# Parse static color
params[LottieTensor.Index.Fill.R] = round(float(attrs.get("r", 0))*255)
params[LottieTensor.Index.Fill.G] = round(float(attrs.get("g", 0))*255)
params[LottieTensor.Index.Fill.B] = round(float(attrs.get("b", 0))*255)
# Parse opacity keyframes if animated
if opacity_animated:
o_kf_count = int(attrs.get("o_kf_count", 0))
opacity_keyframes = []
for i in range(o_kf_count):
kf = {
't': round(float(attrs.get(f"o_kf_{i}_t", 0))),
's': round(float(attrs.get(f"o_kf_{i}_s", 100))),
'i_x': round(float(attrs.get(f"o_kf_{i}_i_x", 0)) * 100),
'i_y': round(float(attrs.get(f"o_kf_{i}_i_y", 0)) * 100),
'o_x': round(float(attrs.get(f"o_kf_{i}_o_x", 0)) * 100),
'o_y': round(float(attrs.get(f"o_kf_{i}_o_y", 0)) * 100)
}
opacity_keyframes.append(kf)
# Store in string_params as JSON
#string_params[f"{cmd_key}_opacity_keyframes"] = json.dumps(opacity_keyframes)
else:
# Parse static opacity
params[LottieTensor.Index.Fill.OPACITY] = round(float(attrs.get("opacity", 100)))
# Parse other parameters
params[LottieTensor.Index.Fill.COLOR_DIM] = int(attrs.get("color_dim", 3))
params[LottieTensor.Index.Fill.HAS_C_A] = 1.0 if attrs.get("has_c_a", "").lower() == "true" else 0.0
params[LottieTensor.Index.Fill.HAS_C_IX] = 1.0 if attrs.get("has_c_ix", "").lower() == "true" else 0.0
params[LottieTensor.Index.Fill.C_IX] = int(attrs.get("c_ix", 4))
params[LottieTensor.Index.Fill.BM] = int(attrs.get("bm", 0))
params[LottieTensor.Index.Fill.FILL_RULE] = int(attrs.get("fill_rule", 1))
params[LottieTensor.Index.Fill.HAS_O_A] = 1.0 if attrs.get("has_o_a", "").lower() == "true" else 0.0
params[LottieTensor.Index.Fill.HAS_O_IX] = 1.0 if attrs.get("has_o_ix", "").lower() == "true" else 0.0
params[LottieTensor.Index.Fill.O_IX] = int(attrs.get("o_ix", 5))
elif cmd_idx == LottieTensor.CMD_BEZIER:
# Parse the closed attribute from input
closed_str = attrs.get("closed", "true")
params[LottieTensor.Index.Bezier.CLOSED] = 1.0 if closed_str.lower() == "true" else 0.0
#elif cmd_idx == LottieTensor.CMD_ELLIPSE:
#name = string_params.get(f"{cmd_key}_name", "Ellipse Path 1")
#lines.append(f'({cmd} name="{name}")')
elif cmd_idx in [LottieTensor.CMD_POSITION, LottieTensor.CMD_SIZE]:
if cmd == "size":
# Check if size is animated
if attrs.get("animated", "").lower() == "true":
# Don't parse values when animated
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
current_context = "size" # Set context for size keyframes
else:
# Explicitly set ANIMATED to 0.0 for static size
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Parse two values for static size
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(value_parts[1]))
else:
# Handle position as before
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TwoValues.VALUE1] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.TwoValues.VALUE2] = round(float(value_parts[1]))
elif cmd_idx == LottieTensor.CMD_RECT:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Rectangle Path 1")
params[LottieTensor.Index.Rect.HD] = 1.0 if attrs.get("hd", "false").lower() == "true" else 0.0
params[LottieTensor.Index.Rect.D] = int(attrs.get("d", 1))
elif cmd_idx == LottieTensor.CMD_ROUNDED:
# Parse rounded value and ix
rounded_val = round(float(attrs.get("rounded", attrs_str.split()[0] if attrs_str.split() else "0")))
params[LottieTensor.Index.SingleValue.VALUE] = rounded_val
params[LottieTensor.Index.SingleValue.IX] = int(attrs.get("ix", 4))
# ADD THIS NEW SECTION:
elif cmd_idx == LottieTensor.CMD_RECT_ROUNDED:
# Check if animated
if "animated" in attrs and attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.SingleValue.ANIMATED] = 1.0
current_context = "rect_rounded" # Set context for keyframes
else:
params[LottieTensor.Index.SingleValue.ANIMATED] = 0.0
# Parse the value if not animated
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_TRIM:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Trim Paths 1")
params[LottieTensor.Index.Trim.IX] = int(attrs.get("ix", 1))
elif cmd_idx == LottieTensor.CMD_END:
# Handle trim sub-commands
# Check if animated
if "animated" in attrs and attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.SingleValue.ANIMATED] = 1.0
current_context = "trim_end" # Set context for keyframes
# Don't parse value when animated=true
else:
params[LottieTensor.Index.SingleValue.ANIMATED] = 0.0
# Parse the value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_START:
# Handle trim sub-commands
# Check if animated
if "animated" in attrs and attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.SingleValue.ANIMATED] = 1.0
current_context = "trim_start" # Set context for keyframes
# Don't parse value when animated=true
else:
params[LottieTensor.Index.SingleValue.ANIMATED] = 0.0
# Parse the value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_OFFSET:
# Handle trim sub-commands
# Check if animated
if "animated" in attrs and attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.SingleValue.ANIMATED] = 1.0
current_context = "trim_offset" # Set context for keyframes
# Don't parse value when animated=true
else:
params[LottieTensor.Index.SingleValue.ANIMATED] = 0.0
# Parse the value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_MULTIPLE:
# Parse multiple value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_REPEATER:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Repeater 1")
params[LottieTensor.Index.Repeater.IX] = int(attrs.get("ix", 1))
elif cmd_idx == LottieTensor.CMD_COPIES:
# Parse copies value and ix
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
params[LottieTensor.Index.SingleValue.IX] = int(attrs.get("ix", 1))
elif cmd_idx == LottieTensor.CMD_REPEATER_OFFSET:
# Parse repeater_offset value and ix
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
params[LottieTensor.Index.SingleValue.IX] = int(attrs.get("ix", 2))
elif cmd_idx == LottieTensor.CMD_COMPOSITE:
# Parse composite value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_TR_SCALE:
# Parse tr_scale values
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TwoValues.VALUE1] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.TwoValues.VALUE2] = round(float(value_parts[1]))
elif cmd_idx in [LottieTensor.CMD_TR_P_IX, LottieTensor.CMD_TR_A_IX, LottieTensor.CMD_TR_S_IX,
LottieTensor.CMD_TR_R_IX, LottieTensor.CMD_TR_SO_IX, LottieTensor.CMD_TR_EO_IX]:
# Parse single index value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_TRANSFORM_SHAPE:
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Transform")
# Parse hd attribute
params[LottieTensor.Index.TransformShape.HD] = 1.0 if attrs.get("hd", "false").lower() == "true" else 0.0
# Parse position
position_str = attrs.get("position", "0 0").strip('"')
pos_parts = position_str.split()
if len(pos_parts) >= 1:
params[LottieTensor.Index.TransformShape.POSITION_X] = round(float(pos_parts[0]))
if len(pos_parts) >= 2:
params[LottieTensor.Index.TransformShape.POSITION_Y] = round(float(pos_parts[1]))
# Parse scale
scale_str = attrs.get("scale", "100 100").strip('"')
scale_parts = scale_str.split()
if len(scale_parts) >= 1:
params[LottieTensor.Index.TransformShape.SCALE_X] = round(float(scale_parts[0]))
if len(scale_parts) >= 2:
params[LottieTensor.Index.TransformShape.SCALE_Y] = round(float(scale_parts[1]))
# Parse rotation
rotation_str = attrs.get("rotation", "0").strip('"')
params[LottieTensor.Index.TransformShape.ROTATION] = round(float(rotation_str))
# Parse opacity
opacity_str = attrs.get("opacity", "100").strip('"')
params[LottieTensor.Index.TransformShape.OPACITY] = round(float(opacity_str))
# Parse anchor
anchor_str = attrs.get("anchor", "0 0").strip('"')
anchor_parts = anchor_str.split()
if len(anchor_parts) >= 1:
params[LottieTensor.Index.TransformShape.ANCHOR_X] = round(float(anchor_parts[0]))
if len(anchor_parts) >= 2:
params[LottieTensor.Index.TransformShape.ANCHOR_Y] = round(float(anchor_parts[1]))
# Parse skew (only if present)
if "skew" in attrs:
skew_str = attrs.get("skew", "0").strip('"')
params[LottieTensor.Index.TransformShape.SKEW] = round(float(skew_str))
# Parse skew_axis (only if present)
if "skew_axis" in attrs:
skew_axis_str = attrs.get("skew_axis", "0").strip('"')
params[LottieTensor.Index.TransformShape.SKEW_AXIS] = round(float(skew_axis_str))
elif cmd_idx == LottieTensor.CMD_PARENT:
# Parse parent index
parent_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
parent_parts.append(part)
except ValueError:
pass
if parent_parts:
params[LottieTensor.Index.Parent.PARENT_INDEX] = round(float(parent_parts[0]))
elif cmd_idx == LottieTensor.CMD_ASSET:
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
asset_id = attrs.get("id", "comp_0")
id_tokens = LottieTensor.tokenizer.encode(asset_id, add_special_tokens=False)[:10] # Limit to 10 tokens
for i, token_id in enumerate(id_tokens):
if i < 10:
params[LottieTensor.Index.Asset.ID_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Asset.ID_TOKEN_COUNT] = int(len(id_tokens))
#string_params[f"{cmd_key}_id"] = attrs.get("id", "comp_0")
#string_params[f"{cmd_key}_nm"] = attrs.get("nm", "asset")
params[LottieTensor.Index.Asset.FR] = round(float(attrs.get("fr", 30)))
elif cmd_idx == LottieTensor.CMD_FONT:
# 存储字符串参数
#string_params[f"{cmd_key}_family"] = attrs.get("family", "")
#string_params[f"{cmd_key}_style"] = attrs.get("style", "")
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
# 编码family和style
family = attrs.get("family", "")
style = attrs.get("style", "")
family_tokens = LottieTensor.tokenizer.encode(family, add_special_tokens=False)[:10]
style_tokens = LottieTensor.tokenizer.encode(style, add_special_tokens=False)[:10]
params[LottieTensor.Index.Font.ASCENT] = round(float(attrs.get("ascent", 75)))
for i, token_id in enumerate(family_tokens):
if i < 10:
params[LottieTensor.Index.Font.FAMILY_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Font.FAMILY_TOKEN_COUNT] = int(len(family_tokens))
# Store style tokens
for i, token_id in enumerate(style_tokens):
if i < 10:
params[LottieTensor.Index.Font.STYLE_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Font.STYLE_TOKEN_COUNT] = int(len(style_tokens))
elif cmd_idx == LottieTensor.CMD_CHAR:
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
# 特殊处理 ch 属性，因为可能包含特殊字符如 ")"
ch_match = re.search(r'ch="([^"]*)"', attrs_str)
ch = ch_match.group(1) if ch_match else attrs.get("ch", "")
# 解析其他属性时，需要先移除 ch 属性以避免干扰
temp_attrs_str = attrs_str
if ch_match:
temp_attrs_str = attrs_str[:ch_match.start()] + attrs_str[ch_match.end():]
# 重新解析其他属性
temp_attrs = LottieTensor._parse_attributes(temp_attrs_str)
style = temp_attrs.get("style", "")
family = temp_attrs.get("family", "")
# Encode strings
ch_tokens = LottieTensor.tokenizer.encode(ch, add_special_tokens=False)[:10]
style_tokens = LottieTensor.tokenizer.encode(style, add_special_tokens=False)[:10]
family_tokens = LottieTensor.tokenizer.encode(family, add_special_tokens=False)[:10]
params[LottieTensor.Index.Char.SIZE] = round(float(temp_attrs.get("size", 100)))
params[LottieTensor.Index.Char.W] = round(float(temp_attrs.get("w", 0)))
# Store ch tokens
for i, token_id in enumerate(ch_tokens):
if i < 10:
params[LottieTensor.Index.Char.CH_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Char.CH_TOKEN_COUNT] = int(len(ch_tokens))
# Store style tokens
for i, token_id in enumerate(style_tokens):
if i < 10:
params[LottieTensor.Index.Char.STYLE_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Char.STYLE_TOKEN_COUNT] = int(len(style_tokens))
# Store family tokens
for i, token_id in enumerate(family_tokens):
if i < 10:
params[LottieTensor.Index.Char.FAMILY_TOKEN_0 + i] = int(token_id)
params[LottieTensor.Index.Char.FAMILY_TOKEN_COUNT] = int(len(family_tokens))
elif cmd_idx == LottieTensor.CMD_FONT_SIZE:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.FontSize.SIZE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_FONT_FAMILY:
# 提取引号内的字体族名称
family_match = re.search(r'"([^"]*)"', attrs_str)
if family_match:
string_params[f"{cmd_key}_family"] = family_match.group(1)
elif cmd_idx == LottieTensor.CMD_TEXT:
# 提取引号内的文本
text_match = re.search(r'"([^"]*)"', attrs_str)
if text_match:
string_params[f"{cmd_key}_text"] = text_match.group(1)
elif cmd_idx == LottieTensor.CMD_CA:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Ca.VALUE] = int(value_parts[0])
elif cmd_idx == LottieTensor.CMD_JUSTIFY:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Justify.VALUE] = int(value_parts[0])
elif cmd_idx == LottieTensor.CMD_TRACKING:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Tracking.VALUE] = int(value_parts[0])
elif cmd_idx == LottieTensor.CMD_LINE_HEIGHT:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.LineHeight.VALUE] = int(value_parts[0])
elif cmd_idx == LottieTensor.CMD_LETTER_SPACING:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.LetterSpacing.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_FILL_COLOR:
# 提取RGB值
value_parts = []
for part in attrs_str.split():
try:
round((part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.FillColor.R] = round(float(value_parts[0]) * 255)
if len(value_parts) >= 2:
params[LottieTensor.Index.FillColor.G] = round(float(value_parts[1]) * 255)
if len(value_parts) >= 3:
params[LottieTensor.Index.FillColor.B] = round(float(value_parts[2]) * 255)
elif cmd_idx == LottieTensor.CMD_G:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.G.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_ALIGNMENT:
params[LottieTensor.Index.Alignment.A] = round(float(attrs.get("a", 0)))
elif cmd_idx == LottieTensor.CMD_ALIGNMENT_K:
# 提取两个数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.AlignmentK.VALUE1] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.AlignmentK.VALUE2] = round(float(value_parts[1]))
elif cmd_idx == LottieTensor.CMD_ALIGNMENT_IX:
# 提取数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.AlignmentIx.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_EFFECTS:
# effects容器命令，不需要参数
pass
elif cmd_idx == LottieTensor.CMD_EFFECT:
# Store string parameters
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
#string_params[f"{cmd_key}_match_name"] = attrs.get("match_name", "")
# Store numeric parameters
params[LottieTensor.Index.Effect.TYPE] = int(attrs.get("type", 0))
params[LottieTensor.Index.Effect.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.Effect.NP] = int(attrs.get("np", 0)) # Add NP
params[LottieTensor.Index.Effect.ENABLED] = round(float(attrs.get("enabled", 1))) # Add ENABLED
# Add CMD_LAYER_EFFECT parsing:
elif cmd_idx == LottieTensor.CMD_LAYER_EFFECT:
# Store string parameters
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
#string_params[f"{cmd_key}_match_name"] = attrs.get("match_name", "")
# Store numeric parameters
params[LottieTensor.Index.LayerEffect.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.LayerEffect.VALUE] = round(float(attrs.get("value", 0)))
elif cmd_idx == LottieTensor.CMD_DROPDOWN:
# 存储字符串参数
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
# 存储数值参数
params[LottieTensor.Index.Dropdown.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.Dropdown.VALUE] = round(float(attrs.get("value", 0)))
elif cmd_idx == LottieTensor.CMD_NO_VALUE:
# 存储字符串参数
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
# 存储数值参数
params[LottieTensor.Index.NO_VALUE.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.NO_VALUE.VALUE] = round(float(attrs.get("value", 0)))
elif cmd_idx == LottieTensor.CMD_IGNORED:
# 存储字符串参数
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
# 存储数值参数
params[LottieTensor.Index.Ignored.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.Ignored.VALUE] = round(float(attrs.get("value", 0)))
elif cmd_idx == LottieTensor.CMD_SLIDER:
# 存储字符串参数
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
# 存储数值参数
params[LottieTensor.Index.Slider.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.Slider.VALUE] = round(float(attrs.get("value", 0)))
elif cmd_idx == LottieTensor.CMD_GRADIENT_FILL:
# Store name only for gradient_fill command
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Gradient Fill 1")
# Set context for subsequent commands
current_context = "gradient_fill"
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "gradient_fill":
# Parse opacity value for gradient_fill context
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_FILL_RULE:
# Parse fill_rule value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_START_POINT:
# Parse start_point values
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TwoValues.VALUE1] = LottieTensor._clamp_value(round(float(value_parts[0])))
if len(value_parts) >= 2:
params[LottieTensor.Index.TwoValues.VALUE2] = LottieTensor._clamp_value(round(float(value_parts[1])))
elif cmd_idx == LottieTensor.CMD_END_POINT:
# Parse end_point values
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TwoValues.VALUE1] = LottieTensor._clamp_value(round(float(value_parts[0])))
if len(value_parts) >= 2:
params[LottieTensor.Index.TwoValues.VALUE2] = LottieTensor._clamp_value(round(float(value_parts[1])))
elif cmd_idx == LottieTensor.CMD_GRADIENT_TYPE:
# Parse gradient_type value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_STAR:
# 解析 star 命令的属性
#string_params[f"{cmd_key}_name"] = attrs.get("name", "None")
# 解析 d 和 sy 参数
params[LottieTensor.Index.Star.D] = round(float(attrs.get("d", 1)))
params[LottieTensor.Index.Star.SY] = round(float(attrs.get("sy", 1)))
# IX 参数如果存在的话
#params[LottieTensor.Index.Star.IX] = float(attrs.get("ix", 1))
# 3. 添加 inner_radius 等子命令的解析
elif cmd_idx == LottieTensor.CMD_INNER_RADIUS:
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_OUTER_RADIUS:
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_INNER_ROUNDNESS:
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_OUTER_ROUNDNESS:
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_POINTS_STAR: # 这应该是 points_star
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_STAR_ROTATION:
# 解析数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_HIGHLIGHT_LENGTH:
# Parse highlight_length value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_HIGHLIGHT_ANGLE:
# Parse highlight_angle value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_ORIGINAL_COLORS:
colors_match = re.search(r'\[([^\]]*)\]', attrs_str)
if colors_match:
colors_str = colors_match.group(1)
color_values = []
for color_part in colors_str.split(','):
try:
color_values.append(round(float(color_part.strip())*255))
except ValueError:
color_values.append(0)
# Store up to 24 color values (increased from 18)
for i, val in enumerate(color_values[:48]):
if i < 48: # Make sure we don't exceed our storage capacity
params[LottieTensor.Index.OriginalColors.COLOR_0 + i] = val
# Store count of colors
params[LottieTensor.Index.OriginalColors.COUNT] = int(len(color_values))
elif cmd_idx == LottieTensor.CMD_COLOR_POINTS:
# Parse color_points value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_GRADIENT_FILL_END:
# Reset context when gradient_fill ends
current_context = None
elif cmd_idx == LottieTensor.CMD_GRADIENT_STROKE:
# Store name only - similar to gradient_fill
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Gradient Stroke 1")
# Set context for subsequent commands
current_context = "gradient_stroke"
# Add handling for individual gradient_stroke sub-commands:
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "gradient_stroke":
# Parse opacity value for gradient_stroke context
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_WIDTH:
value_parts = []
for part in attrs_str.split():
try:
float(part) # 只检查是否是数字，不用round
value_parts.append(part)
except ValueError:
pass
if value_parts:
# 乘以100保留小数精度
value = round(float(value_parts[0]) * 10)
value = max(0, min(10000, value)) # 裁剪
params[LottieTensor.Index.SingleValue.VALUE] = value
elif cmd_idx == LottieTensor.CMD_LINE_CAP:
# Parse line_cap value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_LINE_JOIN:
# Parse line_join value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_MITER_LIMIT:
# Parse miter_limit value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_GRADIENT_STROKE_END:
# Reset context when gradient_stroke ends
current_context = None
elif cmd_idx == LottieTensor.CMD_COLOR:
# Store string parameters
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Color")
# Store numeric parameters
params[LottieTensor.Index.Color.INDEX] = round(float(attrs.get("index", 1)))
params[LottieTensor.Index.Color.R] = round(float(attrs.get("r", 0))*255)
params[LottieTensor.Index.Color.G] = round(float(attrs.get("g", 0))*255)
params[LottieTensor.Index.Color.B] = round(float(attrs.get("b", 0))*255)
#elif cmd_idx == LottieTensor.CMD_MERGE:
# 存储merge的name属性
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Merge Paths 1")
elif cmd_idx == LottieTensor.CMD_MERGE_MODE:
# 解析merge_mode的数值
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.MergeMode.MODE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_MASK:
# Store string attributes
#string_params[f"{cmd_key}_nm"] = attrs.get("nm", "Mask")
params[LottieTensor.Index.Mask.INDEX] = round(float(attrs.get("index", 0)))
params[LottieTensor.Index.Mask.INV] = 1.0 if attrs.get("inv", "false").lower() == "true" else 0.0
# Parse mode attribute
mode = attrs.get("mode", "a")
# Convert mode to numeric for storage
mode_map = {"a": 0, "s": 1, "i": 2, "n": 3}
mode_val = mode_map.get(mode, 0)
params[LottieTensor.Index.Mask.MODE] = round(float(mode_val))
elif cmd_idx == LottieTensor.CMD_MASK_PT:
params[LottieTensor.Index.MaskPt.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.MaskPt.IX] = int(attrs.get("ix", 1))
elif cmd_idx == LottieTensor.CMD_MASK_PT_K_C:
# Parse c (closed) attribute - handle both formats
if "true" in attrs_str.lower():
params[LottieTensor.Index.MaskPtK.C] = 1.0
elif "false" in attrs_str.lower():
params[LottieTensor.Index.MaskPtK.C] = 0.0
else:
# Try to parse from c= format if present
c_str = attrs.get("c", "true")
params[LottieTensor.Index.MaskPtK.C] = 1.0 if c_str.lower() == "true" else 0.0
elif cmd_idx in [LottieTensor.CMD_MASK_PT_K_I, LottieTensor.CMD_MASK_PT_K_O, LottieTensor.CMD_MASK_PT_K_V]:
# Parse all numeric values from the line
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
# Store up to 20 values (increased from 8)
for i in range(min(20, len(value_parts))):
if i < LottieTensor.PARAM_DIM: # Make sure we don't exceed param dimension
params[LottieTensor.Index.MaskPtKValues.V1 + i] = round(float(value_parts[i]))
# Store the count of values in string_params for reconstruction
params[LottieTensor.Index.MaskPtKValues.COUNT] = round(float(len(value_parts)))
elif cmd_idx == LottieTensor.CMD_MASK_O:
params[LottieTensor.Index.MaskO.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.MaskO.K] = round(float(attrs.get("k", 100)))
params[LottieTensor.Index.MaskO.IX] = int(attrs.get("ix", 3))
elif cmd_idx == LottieTensor.CMD_MASK_X:
params[LottieTensor.Index.MaskX.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.MaskX.K] = round(float(attrs.get("k", 0)))
params[LottieTensor.Index.MaskX.IX] = int(attrs.get("ix", 4))
# 添加这部分：检查是否是动画
if float(attrs.get("a", 0)) > 0.5:
current_context = "mask_x"
elif cmd_idx == LottieTensor.CMD_MASKS_PROPERTIES:
# Container command, no parameters needed
pass
elif cmd_idx in [LottieTensor.CMD_MASK_PT_K_ARRAY, LottieTensor.CMD_MASK_PT_K_ARRAY_END,
LottieTensor.CMD_MASK_PT_KF_S, LottieTensor.CMD_MASK_PT_KF_S_END,
LottieTensor.CMD_MASK_PT_KF_SHAPE_END, LottieTensor.CMD_MASK_PT_KEYFRAME_END]:
# Container commands, no parameters
pass
elif cmd_idx == LottieTensor.CMD_MASK_PT_KEYFRAME:
params[LottieTensor.Index.MaskPtKeyframe.INDEX] = int(attrs.get("index", 0))
params[LottieTensor.Index.MaskPtKeyframe.T] = round(float(attrs.get("t", 0)))
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_I:
params[LottieTensor.Index.MaskPtKfI.X] = round(float(attrs.get("x", 0)))
params[LottieTensor.Index.MaskPtKfI.Y] = round(float(attrs.get("y", 0)))
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_O:
params[LottieTensor.Index.MaskPtKfO.X] = round(float(attrs.get("x", 0)))
params[LottieTensor.Index.MaskPtKfO.Y] = round(float(attrs.get("y", 0)))
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_SHAPE:
params[LottieTensor.Index.MaskPtKfShape.INDEX] = int(attrs.get("index", 0))
c_str = attrs.get("c", "true")
params[LottieTensor.Index.MaskPtKfShape.C] = 1.0 if c_str.lower() == "true" else 0.0
elif cmd_idx in [LottieTensor.CMD_MASK_PT_KF_SHAPE_I, LottieTensor.CMD_MASK_PT_KF_SHAPE_O,
LottieTensor.CMD_MASK_PT_KF_SHAPE_V]:
# Parse all numeric values from the line
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
# Store up to 20 values (increased from 8)
for i in range(min(20, len(value_parts))):
if i < LottieTensor.PARAM_DIM: # Make sure we don't exceed param dimension
params[LottieTensor.Index.MaskPtKfShapeValues.V1 + i] = round(float(value_parts[i]))
# Store the count in params, NOT in string_params
params[LottieTensor.Index.MaskPtKfShapeValues.COUNT] = round(float(len(value_parts)))
elif cmd_idx == LottieTensor.CMD_TR_POSITION:
# Parse tr_position values
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TrPosition.X] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.TrPosition.Y] = round(float(value_parts[1]))
elif cmd_idx == LottieTensor.CMD_TR_ANCHOR:
# Parse tr_anchor values
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.TrAnchor.X] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.TrAnchor.Y] = round(float(value_parts[1]))
elif cmd_idx == LottieTensor.CMD_TR_ROTATION:
# Parse tr_rotation value
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.TrRotation.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_TR_START_OPACITY:
# Parse tr_start_opacity value
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.TrStartOpacity.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_TR_END_OPACITY:
# Parse tr_end_opacity value
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.TrEndOpacity.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_ZIG_ZAG:
# Store string parameters
#string_params[f"{cmd_key}_name"] = attrs.get("name", "Zig Zag 1")
# Store numeric parameters
params[LottieTensor.Index.ZigZag.IX] = int(attrs.get("ix", 2))
elif cmd_idx == LottieTensor.CMD_FREQUENCY:
# Parse frequency value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Frequency.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_AMPLITUDE:
# Parse amplitude value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Amplitude.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_POINT_TYPE:
# Parse point_type value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.PointType.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_ANIMATORS:
# Container command, no parameters
pass
#elif cmd_idx == LottieTensor.CMD_ANIMATOR:
# Store animator name
#string_params[f"{cmd_key}_nm"] = attrs.get("nm", "Animator 1")
elif cmd_idx == LottieTensor.CMD_RANGE_SELECTOR:
params[LottieTensor.Index.RangeSelector.T] = round(float(attrs.get("t", 0)))
params[LottieTensor.Index.RangeSelector.R] = round(float(attrs.get("r", 1)))
params[LottieTensor.Index.RangeSelector.B] = round(float(attrs.get("b", 1)))
params[LottieTensor.Index.RangeSelector.SH] = round(float(attrs.get("sh", 1))) #这里还需要check下
params[LottieTensor.Index.RangeSelector.RN] = round(float(attrs.get("rn", 0)))
elif cmd_idx == LottieTensor.CMD_RANGE_START:
params[LottieTensor.Index.RangeStart.A] = round(float(attrs.get("a", 0)))
# Check if animated
if float(attrs.get("a", 0)) > 0.5:
current_context = "range_start"
elif cmd_idx == LottieTensor.CMD_RANGE_START_KEYFRAME:
params[LottieTensor.Index.RangeStartKeyframe.T] = round(float(attrs.get("t", 0)))
params[LottieTensor.Index.RangeStartKeyframe.S] = round(float(attrs.get("s", 0)))
params[LottieTensor.Index.RangeStartKeyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.RangeStartKeyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.RangeStartKeyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.RangeStartKeyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_AMOUNT:
params[LottieTensor.Index.Amount.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.Amount.K] = round(float(attrs.get("k", 100)))
params[LottieTensor.Index.Amount.IX] = int(attrs.get("ix", 4))
elif cmd_idx == LottieTensor.CMD_MAX_EASE:
params[LottieTensor.Index.MaxEase.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.MaxEase.K] = round(float(attrs.get("k", 0)))
params[LottieTensor.Index.MaxEase.IX] = int(attrs.get("ix", 7))
elif cmd_idx == LottieTensor.CMD_MIN_EASE:
params[LottieTensor.Index.MinEase.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.MinEase.K] = round(float(attrs.get("k", 0)))
params[LottieTensor.Index.MinEase.IX] = int(attrs.get("ix", 8))
elif cmd_idx == LottieTensor.CMD_ANIMATOR_PROPERTIES:
# Container command, no parameters
current_context = "animator_properties" # Set context for opacity handling
pass
elif cmd_idx == LottieTensor.CMD_ANIMATOR_PROPERTIES_END:
current_context = None # Reset context
pass
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "animator_properties":
# Special handling for opacity within animator_properties
params[LottieTensor.Index.Amount.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.Amount.K] = round(float(attrs.get("k", 0)))
params[LottieTensor.Index.Amount.IX] = int(attrs.get("ix", 9))
elif cmd_idx == LottieTensor.CMD_RADIUS:
# Parse radius value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.Radius.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_RANGE_END:
params[LottieTensor.Index.RangeEnd.A] = round(float(attrs.get("a", 0)))
# Check if animated
if float(attrs.get("a", 0)) > 0.5:
current_context = "range_end"
elif cmd_idx == LottieTensor.CMD_RANGE_END_KEYFRAME:
params[LottieTensor.Index.RangeEndKeyframe.T] = round(float(attrs.get("t", 0)))
params[LottieTensor.Index.RangeEndKeyframe.S] = round(float(attrs.get("s", 0)))
params[LottieTensor.Index.RangeEndKeyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.RangeEndKeyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.RangeEndKeyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.RangeEndKeyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_POSITION and current_context == "animator_properties":
# Special handling for position within animator_properties
params[LottieTensor.Index.Amount.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.Amount.IX] = int(attrs.get("ix", 2))
# Parse k parameter which can be an array
k_str = attrs.get("k", "0")
if k_str.startswith("[") and k_str.endswith("]"):
# Parse array values
k_str = k_str[1:-1] # Remove brackets
k_parts = k_str.split(",")
if len(k_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(k_parts[0].strip()))
if len(k_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(k_parts[1].strip()))
if len(k_parts) >= 3:
params[LottieTensor.Index.Transform.Z] = round(float(k_parts[2].strip()))
else:
params[LottieTensor.Index.Amount.K] = round(float(k_str))
elif cmd_idx == LottieTensor.CMD_ML2:
# Parse ml2 value
value_parts = []
for part in attrs_str.split():
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if value_parts:
params[LottieTensor.Index.SingleValue.VALUE] = round(float(value_parts[0]))
elif cmd_idx == LottieTensor.CMD_RANGE_OFFSET_KEYFRAME:
params[LottieTensor.Index.RangeOffsetKeyframe.T] = round(float(attrs.get("t", 0)))
params[LottieTensor.Index.RangeOffsetKeyframe.S] = round(float(attrs.get("s", 0)))
params[LottieTensor.Index.RangeOffsetKeyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.RangeOffsetKeyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.RangeOffsetKeyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.RangeOffsetKeyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_S_M:
params[LottieTensor.Index.SM.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.SM.K] = round(float(attrs.get("k", 100)))
params[LottieTensor.Index.SM.IX] = int(attrs.get("ix", 6))
elif cmd_idx == LottieTensor.CMD_OPACITY_ANIMATORS:
params[LottieTensor.Index.OpacityAnimators.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.OpacityAnimators.IX] = int(attrs.get("ix", 9))
# If not animated (a=0), parse k value
if float(attrs.get("a", 0)) < 0.5:
params[LottieTensor.Index.OpacityAnimators.K] = round(float(attrs.get("k", 0)))
else:
# Set context for animated keyframes
current_context = "opacity_animators"
elif cmd_idx == LottieTensor.CMD_POSITION_ANIMATORS_END:
current_context = None
# 添加 CMD_POSITION_ANIMATORS 处理：
elif cmd_idx == LottieTensor.CMD_POSITION_ANIMATORS:
params[LottieTensor.Index.PositionAnimators.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.PositionAnimators.IX] = int(attrs.get("ix", 2))
# If not animated (a=0), parse k value
if float(attrs.get("a", 0)) < 0.5:
# Parse k value which could be a single value or array
k_str = attrs.get("k", "0")
if k_str.startswith("[") and k_str.endswith("]"):
# Parse array values
k_str = k_str[1:-1] # Remove brackets
k_parts = k_str.split(",")
if len(k_parts) >= 1:
params[LottieTensor.Index.PositionAnimators.K_X] = round(float(k_parts[0].strip()))
if len(k_parts) >= 2:
params[LottieTensor.Index.PositionAnimators.K_Y] = round(float(k_parts[1].strip()))
if len(k_parts) >= 3:
params[LottieTensor.Index.PositionAnimators.K_Z] = round(float(k_parts[2].strip()))
else:
# Single value - apply to all dimensions
try:
k_val = round(float(k_str))
params[LottieTensor.Index.PositionAnimators.K_X] = k_val
params[LottieTensor.Index.PositionAnimators.K_Y] = k_val
params[LottieTensor.Index.PositionAnimators.K_Z] = k_val
except ValueError:
# Default to 0 if parsing fails
params[LottieTensor.Index.PositionAnimators.K_X] = 0
params[LottieTensor.Index.PositionAnimators.K_Y] = 0
params[LottieTensor.Index.PositionAnimators.K_Z] = 0
else:
# Set context for animated keyframes
current_context = "position_animators"
# 添加 CMD_TRACKING_ANIMATORS 处理：
elif cmd_idx == LottieTensor.CMD_TRACKING_ANIMATORS:
params[LottieTensor.Index.TrackingAnimators.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.TrackingAnimators.K] = round(float(attrs.get("k", 0)))
params[LottieTensor.Index.TrackingAnimators.IX] = int(attrs.get("ix", 89))
# If animated, set context
if float(attrs.get("a", 0)) > 0.5:
current_context = "tracking_animators"
elif cmd_idx == LottieTensor.CMD_SCALE_ANIMATORS:
params[LottieTensor.Index.ScaleAnimators.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.ScaleAnimators.IX] = int(attrs.get("ix", 3))
# If not animated (a=0), parse k value
if float(attrs.get("a", 0)) < 0.5:
# Parse k value which could be a single value or array
k_str = attrs.get("k", "100")
if k_str.startswith("[") and k_str.endswith("]"):
# Parse array values
k_str = k_str[1:-1] # Remove brackets
k_parts = k_str.split(",")
if len(k_parts) >= 1:
params[LottieTensor.Index.ScaleAnimators.K_X] = round(float(k_parts[0].strip()))
if len(k_parts) >= 2:
params[LottieTensor.Index.ScaleAnimators.K_Y] = round(float(k_parts[1].strip()))
if len(k_parts) >= 3:
params[LottieTensor.Index.ScaleAnimators.K_Z] = round(float(k_parts[2].strip()))
else:
# Single value - apply to all dimensions
k_val = round(float(k_str))
params[LottieTensor.Index.ScaleAnimators.K_X] = k_val
params[LottieTensor.Index.ScaleAnimators.K_Y] = k_val
params[LottieTensor.Index.ScaleAnimators.K_Z] = k_val
else:
# Set context for animated keyframes
current_context = "scale_animators"
elif cmd_idx == LottieTensor.CMD_ROTATION_ANIMATORS:
params[LottieTensor.Index.RotationAnimators.A] = int(attrs.get("a", 0))
params[LottieTensor.Index.RotationAnimators.IX] = int(attrs.get("ix", 4))
# If not animated (a=0), parse k value
if float(attrs.get("a", 0)) < 0.5:
params[LottieTensor.Index.RotationAnimators.K] = int(attrs.get("k", 0))
else:
# Set context for animated keyframes
current_context = "rotation_animators"
elif cmd_idx == LottieTensor.CMD_SCALE_ANIMATORS_END:
current_context = None
elif cmd_idx == LottieTensor.CMD_ROTATION_ANIMATORS_END:
current_context = None
elif cmd_idx == LottieTensor.CMD_RANGE_OFFSET:
# Parse the 'a' attribute correctly
params[LottieTensor.Index.Amount.A] = int(attrs.get("a", 0))
# Check if animated
if float(attrs.get("a", 0)) > 0.5:
# Animated case - set context for keyframes
current_context = "range_offset"
else:
# Static case - also parse k and ix values
params[LottieTensor.Index.Amount.K] = int(attrs.get("k", 0))
params[LottieTensor.Index.Amount.IX] = int(attrs.get("ix", 3))
elif cmd_idx == LottieTensor.CMD_DASHES:
# Container command for dashes
# Parse the entire dashes string if present
dashes_str = attrs_str.strip()
if dashes_str:
string_params[f"{cmd_key}_dashes"] = dashes_str
elif cmd_idx == LottieTensor.CMD_DASH:
dash_type = attrs.get("type", "d")
type_map = {"d": 0, "g": 1, "o": 2}
params[LottieTensor.Index.Dash.TYPE] = int(type_map.get(dash_type, 0))
# 乘以100保留小数精度
length_val = round(float(attrs.get("length", 0)) * 10)
length_val = max(0, min(10000, length_val))
params[LottieTensor.Index.Dash.LENGTH] = length_val
params[LottieTensor.Index.Dash.V_IX] = int(attrs.get("v_ix", 1))
# Store name in string_params
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
elif cmd_idx == LottieTensor.CMD_DASH_ANIMATED:
# Parse dash_animated attributes
dash_type = attrs.get("type", "o")
# Convert type to numeric
type_map = {"d": 0, "g": 1, "o": 2}
params[LottieTensor.Index.DashAnimated.TYPE] = int(type_map.get(dash_type, 2))
# Parse v_ix
params[LottieTensor.Index.DashAnimated.V_IX] = int(attrs.get("v_ix", 7))
# Store name in string_params
#string_params[f"{cmd_key}_name"] = attrs.get("name", "")
# Set context for keyframes
current_context = "dash_animated"
elif cmd_idx == LottieTensor.CMD_DASH_KEYFRAME:
params[LottieTensor.Index.DashKeyframe.T] = round(float(attrs.get("t", 0)))
# 改成乘以10，并裁剪
s_val = round(float(attrs.get("s", 0)) * 10)
s_val = max(0, min(10000, s_val))
params[LottieTensor.Index.DashKeyframe.S] = s_val
# easing参数保持不变
params[LottieTensor.Index.DashKeyframe.I_X] = round(float(LottieTensor._parse_easing_value(attrs.get("i_x", "0"))*100))
params[LottieTensor.Index.DashKeyframe.I_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("i_y", "0"))*100))
params[LottieTensor.Index.DashKeyframe.O_X] = round(float(LottieTensor._parse_easing_value(attrs.get("o_x", "0"))*100))
params[LottieTensor.Index.DashKeyframe.O_Y] = round(float(LottieTensor._parse_easing_value(attrs.get("o_y", "0"))*100))
elif cmd_idx == LottieTensor.CMD_DASH_ANIMATED_END:
# Reset context
current_context = None
elif cmd_idx == LottieTensor.CMD_DASH_OFFSET:
value_parts = []
for part in attrs_str.split():
try:
float(part)
value_parts.append(part)
except ValueError:
pass
if value_parts:
# 改成乘以10，并裁剪
value = round(float(value_parts[0]) * 10)
value = max(0, min(10000, value))
params[LottieTensor.Index.DashOffset.O] = value
elif cmd_idx == LottieTensor.CMD_DASHES_END:
# End of dashes container
pass
elif cmd_idx == LottieTensor.CMD_SIZE_END:
# End of dashes container
pass
elif cmd_idx == LottieTensor.CMD_RECT_SIZE:
# 检查是否是动画
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
current_context = "size"
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(value_parts[1]))
elif cmd_idx == LottieTensor.CMD_ELLIPSE_SIZE:
# 检查是否是动画
if attrs.get("animated", "").lower() == "true":
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
current_context = "size" # 设置上下文用于关键帧
else:
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# 解析静态值
value_parts = []
for part in attrs_str.split():
if '=' not in part:
try:
round(float(part))
value_parts.append(part)
except ValueError:
pass
if len(value_parts) >= 1:
params[LottieTensor.Index.Transform.X] = round(float(value_parts[0]))
if len(value_parts) >= 2:
params[LottieTensor.Index.Transform.Y] = round(float(value_parts[1]))
params_list.append(params)
# Convert to tensors
commands_tensor = torch.tensor(commands).long()
params_tensor = torch.tensor(params_list).float()
lottie_tensor = LottieTensor(commands_tensor, params_tensor)
#lottie_tensor.string_params = string_params
return lottie_tensor
def from_sequence_v2(sequence_str)-> 'LottieTensor':
"""
Parse a sequence string back into a Lottie animation dictionary.
Properly handles nested group structures using a stack.
"""
lines = sequence_str.strip().split('\n')
animation = {
"v": "5.5.2",
"fr": 30,
"ip": 0,
"op": 60,
"w": 512,
"h": 512,
"nm": "Animation",
"ddd": 0,
"assets": [],
"layers": [],
"markers": [],
"props": {},
"fonts": None,
"chars": None
}
# Stack for tracking nested structures
# Each entry is (type, object, items_list)
stack = []
current_layer = None
current_transform = None
current_path = None
current_path_points = []
current_keyframes = []
current_context = None # 'position', 'scale', 'rotation', 'opacity', 'anchor'
def parse_attrs(attr_str):
"""Parse attribute string into dict"""
attrs = {}
if not attr_str:
return attrs
import re
# Handle quoted values
pattern = r'(\w+)=(?:"([^"]*)"|(\S+))'
for match in re.finditer(pattern, attr_str):
key = match.group(1)
value = match.group(2) if match.group(2) is not None else match.group(3)
attrs[key] = value
# Handle space-separated values without keys
parts = attr_str.split()
positional = []
for part in parts:
if '=' not in part:
try:
positional.append(float(part))
except ValueError:
pass
if positional:
attrs['_positional'] = positional
return attrs
def parse_command(line):
"""Parse a command line into (command, attrs_str)"""
line = line.strip()
if not line.startswith('(') or not line.endswith(')'):
return None, ""
content = line[1:-1].strip()
# Handle end tags
if content.startswith('/'):
return content, ""
# Handle quoted commands like "TransformShape"
if content.startswith('"'):
end_quote = content.find('"', 1)
if end_quote > 0:
cmd = content[:end_quote+1]
attrs = content[end_quote+1:].strip()
return cmd, attrs
# Regular command
parts = content.split(' ', 1)
cmd = parts[0]
attrs = parts[1] if len(parts) > 1 else ""
return cmd, attrs
def get_current_items_container():
"""Get the current container for adding items"""
if stack:
return stack[-1][2] # items list
elif current_layer:
return current_layer.get('shapes', [])
return None
def add_to_current_container(item):
"""Add item to current container"""
container = get_current_items_container()
if container is not None:
container.append(item)
for line in lines:
cmd, attrs_str = parse_command(line)
if cmd is None:
continue
attrs = parse_attrs(attrs_str)
# ========== Animation ==========
if cmd == 'animation':
animation['v'] = attrs.get('v', '5.5.2').strip('"')
animation['fr'] = float(attrs.get('fr', 30))
animation['ip'] = float(attrs.get('ip', 0))
animation['op'] = float(attrs.get('op', 60))
animation['w'] = float(attrs.get('w', 512))
animation['h'] = float(attrs.get('h', 512))
animation['ddd'] = int(attrs.get('ddd', 0))
# ========== Layer ==========
elif cmd == 'layer':
current_layer = {
'ddd': int(attrs.get('ddd', 0)),
'ind': int(float(attrs.get('index', 0))),
'ty': 4, # Shape layer
'nm': 'Layer',
'sr': 1,
'ks': {},
'ao': int(attrs.get('ao', 0)),
'shapes': [],
'ip': float(attrs.get('in_point', 0)),
'op': float(attrs.get('out_point', 60)),
'st': float(attrs.get('start_time', 0)),
'bm': 0
}
animation['layers'].append(current_layer)
stack.clear() # New layer, clear stack
elif cmd == '/layer':
current_layer = None
stack.clear()
# ========== Transform ==========
elif cmd == 'transform':
current_transform = {
'o': {'a': 0, 'k': 100, 'ix': 11},
'r': {'a': 0, 'k': 0, 'ix': 10},
'p': {'a': 0, 'k': [0, 0, 0], 'ix': 2},
'a': {'a': 0, 'k': [0, 0, 0], 'ix': 1},
's': {'a': 0, 'k': [100, 100, 100], 'ix': 6}
}
elif cmd == '/transform':
if current_layer and current_transform:
current_layer['ks'] = current_transform
current_transform = None
current_context = None
# ========== Transform properties ==========
elif cmd == 'position':
current_context = 'position'
current_keyframes = []
if 'animated' in attrs and attrs.get('animated', '').lower() == 'true':
if current_transform:
current_transform['p'] = {'a': 1, 'k': [], 'ix': 2}
else:
pos = attrs.get('_positional', [0, 0])
if current_transform:
current_transform['p'] = {'a': 0, 'k': pos + [0] if len(pos) == 2 else pos, 'ix': 2}
elif cmd == '/position':
if current_transform and current_keyframes:
current_transform['p'] = {'a': 1, 'k': current_keyframes, 'ix': 2}
current_context = None
current_keyframes = []
elif cmd == 'scale':
current_context = 'scale'
current_keyframes = []
if 'animated' in attrs and attrs.get('animated', '').lower() == 'true':
if current_transform:
current_transform['s'] = {'a': 1, 'k': [], 'ix': 6}
else:
scale = attrs.get('_positional', [100, 100, 100])
if current_transform:
current_transform['s'] = {'a': 0, 'k': scale, 'ix': 6}
elif cmd == '/scale':
if current_transform and current_keyframes:
current_transform['s'] = {'a': 1, 'k': current_keyframes, 'ix': 6}
current_context = None
current_keyframes = []
elif cmd == 'rotation':
current_context = 'rotation'
current_keyframes = []
if 'animated' in attrs and attrs.get('animated', '').lower() == 'true':
if current_transform:
current_transform['r'] = {'a': 1, 'k': [], 'ix': 10}
else:
rot = attrs.get('_positional', [0])
if current_transform:
current_transform['r'] = {'a': 0, 'k': rot[0] if rot else 0, 'ix': 10}
elif cmd == 'opacity':
current_context = 'opacity'
current_keyframes = []
if 'animated' in attrs and attrs.get('animated', '').lower() == 'true':
if current_transform:
current_transform['o'] = {'a': 1, 'k': [], 'ix': 11}
else:
op = attrs.get('_positional', [100])
if current_transform:
current_transform['o'] = {'a': 0, 'k': op[0] if op else 100, 'ix': 11}
elif cmd == '/opacity':
if current_transform and current_keyframes:
current_transform['o'] = {'a': 1, 'k': current_keyframes, 'ix': 11}
current_context = None
current_keyframes = []
elif cmd == 'anchor':
pos = attrs.get('_positional', [0, 0])
if current_transform:
current_transform['a'] = {'a': 0, 'k': pos + [0] if len(pos) == 2 else pos, 'ix': 1}
# ========== Keyframes ==========
elif cmd == 'keyframe':
t = float(attrs.get('t', 0))
# Parse s value
s_str = attrs.get('s', '0')
if s_str.startswith('"') and s_str.endswith('"'):
s_str = s_str[1:-1]
s_parts = s_str.split()
s_val = [float(x) for x in s_parts] if s_parts else [0]
keyframe = {'t': t, 's': s_val}
# Parse easing
i_x = float(attrs.get('i_x', 0))
i_y = float(attrs.get('i_y', 0))
o_x = float(attrs.get('o_x', 0))
o_y = float(attrs.get('o_y', 0))
if i_x != 0 or i_y != 0 or o_x != 0 or o_y != 0:
keyframe['i'] = {'x': [i_x], 'y': [i_y]}
keyframe['o'] = {'x': [o_x], 'y': [o_y]}
# Parse to/ti
if 'to' in attrs:
to_str = attrs['to'].strip('"[]')
to_parts = [float(x.strip()) for x in to_str.split(',') if x.strip()]
if to_parts:
keyframe['to'] = to_parts
if 'ti' in attrs:
ti_str = attrs['ti'].strip('"[]')
ti_parts = [float(x.strip()) for x in ti_str.split(',') if x.strip()]
if ti_parts:
keyframe['ti'] = ti_parts
current_keyframes.append(keyframe)
# ========== Group ==========
elif cmd == 'group':
group = {
'ty': 'gr',
'nm': 'Group',
'np': int(attrs.get('np', 0)),
'cix': int(attrs.get('cix', 2)),
'bm': int(attrs.get('bm', 0)),
'ix': int(attrs.get('ix', 1)),
'mn': 'ADBE Vector Group',
'hd': attrs.get('hd', 'false').lower() == 'true',
'it': [] # Items go here
}
# Add to current container
add_to_current_container(group)
# Push onto stack
stack.append(('group', group, group['it']))
elif cmd == '/group':
if stack and stack[-1][0] == 'group':
stack.pop()
# ========== Path ==========
elif cmd == 'path':
current_path = {
'ty': 'sh',
'nm': 'Path',
'mn': 'ADBE Vector Shape - Group',
'hd': attrs.get('hd', 'false').lower() == 'true',
'ix': int(attrs.get('ix', 1)),
'ind': int(attrs.get('ind', 0)),
'ks': {
'a': 0,
'k': {
'c': attrs.get('closed', 'true').lower() == 'true',
'v': [],
'i': [],
'o': []
},
'ix': int(attrs.get('ks_ix', 2))
}
}
current_path_points = []
elif cmd == '/path':
if current_path:
# Build bezier from points
bezier = current_path['ks']['k']
for pt in current_path_points:
bezier['v'].append([pt['x'], pt['y']])
bezier['i'].append([pt['in_x'], pt['in_y']])
bezier['o'].append([pt['out_x'], pt['out_y']])
add_to_current_container(current_path)
current_path = None
current_path_points = []
elif cmd == 'point':
pt = {
'x': float(attrs.get('x', 0)),
'y': float(attrs.get('y', 0)),
'in_x': float(attrs.get('in_x', 0)),
'in_y': float(attrs.get('in_y', 0)),
'out_x': float(attrs.get('out_x', 0)),
'out_y': float(attrs.get('out_y', 0))
}
current_path_points.append(pt)
# ========== Fill ==========
elif cmd == 'fill':
fill = {
'ty': 'fl',
'nm': 'Fill',
'mn': 'ADBE Vector Graphic - Fill',
'hd': False,
'c': {
'a': 0,
'k': [
float(attrs.get('r', 0.5)),
float(attrs.get('g', 0.5)),
float(attrs.get('b', 0.5)),
1
],
'ix': int(attrs.get('c_ix', 4))
},
'o': {
'a': 0,
'k': float(attrs.get('opacity', 100)),
'ix': int(attrs.get('o_ix', 5))
},
'r': int(attrs.get('fill_rule', 1)),
'bm': int(attrs.get('bm', 0))
}
add_to_current_container(fill)
# ========== Stroke ==========
elif cmd == 'stroke':
stroke = {
'ty': 'st',
'nm': 'Stroke',
'mn': 'ADBE Vector Graphic - Stroke',
'hd': False,
'c': {
'a': 0,
'k': [
float(attrs.get('r', 0)),
float(attrs.get('g', 0)),
float(attrs.get('b', 0)),
1
],
'ix': int(attrs.get('c_ix', 3))
},
'o': {
'a': 0,
'k': 100,
'ix': 4
},
'w': {
'a': 0,
'k': float(attrs.get('width', 2)),
'ix': 5
},
'lc': int(attrs.get('lc', 2)),
'lj': int(attrs.get('lj', 2)),
'ml': float(attrs.get('ml', 4)),
'bm': int(attrs.get('bm', 0))
}
add_to_current_container(stroke)
# ========== TransformShape (group transform) ==========
elif cmd == '"TransformShape"':
# Parse position
pos_str = attrs.get('position', '0 0').strip('"')
pos_parts = pos_str.split()
pos = [float(x) for x in pos_parts] if pos_parts else [0, 0]
# Parse scale
scale_str = attrs.get('scale', '100 100').strip('"')
scale_parts = scale_str.split()
scale = [float(x) for x in scale_parts] if scale_parts else [100, 100]
# Parse rotation
rot_str = attrs.get('rotation', '0').strip('"')
rot = float(rot_str)
# Parse opacity
op_str = attrs.get('opacity', '100').strip('"')
opacity = float(op_str)
# Parse anchor
anchor_str = attrs.get('anchor', '0 0').strip('"')
anchor_parts = anchor_str.split()
anchor = [float(x) for x in anchor_parts] if anchor_parts else [0, 0]
transform = {
'ty': 'tr',
'p': {'a': 0, 'k': pos, 'ix': 2},
'a': {'a': 0, 'k': anchor, 'ix': 1},
's': {'a': 0, 'k': scale, 'ix': 3},
'r': {'a': 0, 'k': rot, 'ix': 6},
'o': {'a': 0, 'k': opacity, 'ix': 7},
'sk': {'a': 0, 'k': 0, 'ix': 4},
'sa': {'a': 0, 'k': 0, 'ix': 5},
'nm': 'Transform'
}
# Parse skew if present
if 'skew' in attrs:
skew_str = attrs.get('skew', '0').strip('"')
transform['sk']['k'] = float(skew_str)
if 'skew_axis' in attrs:
sa_str = attrs.get('skew_axis', '0').strip('"')
transform['sa']['k'] = float(sa_str)
add_to_current_container(transform)
# ========== Rectangle ==========
elif cmd == 'rect':
rect = {
'ty': 'rc',
'nm': 'Rectangle',
'mn': 'ADBE Vector Shape - Rect',
'hd': attrs.get('hd', 'false').lower() == 'true',
'd': int(attrs.get('d', 1)),
'p': {'a': 0, 'k': [0, 0], 'ix': 3},
's': {'a': 0, 'k': [100, 100], 'ix': 2},
'r': {'a': 0, 'k': 0, 'ix': 4}
}
add_to_current_container(rect)
elif cmd == '/rect':
pass
# ========== Ellipse ==========
elif cmd == 'ellipse':
ellipse = {
'ty': 'el',
'nm': 'Ellipse',
'mn': 'ADBE Vector Shape - Ellipse',
'hd': False,
'd': 1,
'p': {'a': 0, 'k': [0, 0], 'ix': 3},
's': {'a': 0, 'k': [100, 100], 'ix': 2}
}
add_to_current_container(ellipse)
elif cmd == '/ellipse':
pass
return animation
@staticmethod
def _parse_attributes(attrs_str: str) -> Dict[str, str]:
"""Parse attribute string to dictionary - no change needed as it returns strings"""
attrs = {}
# First, handle special attributes with quotes that might contain special characters
# Handle ch attribute specially (for char command)
ch_match = re.search(r'ch="([^"]*)"', attrs_str)
if ch_match:
attrs['ch'] = ch_match.group(1)
# Remove the ch attribute from the string to avoid re-parsing
attrs_str = attrs_str[:ch_match.start()] + attrs_str[ch_match.end():]
# Handle name attribute specially if it contains quotes
name_match = re.search(r'name="([^"]*)"', attrs_str)
if name_match:
attrs['name'] = name_match.group(1)
# Remove the name attribute from the string to avoid re-parsing
attrs_str = attrs_str[:name_match.start()] + attrs_str[name_match.end():]
else:
# Try without quotes
name_match = re.search(r'name=([^\s]+)', attrs_str)
if name_match:
attrs['name'] = name_match.group(1)
attrs_str = attrs_str[:name_match.start()] + attrs_str[name_match.end():]
# Parse remaining attributes
# Pattern for key=value or key="value"
pattern = r'([^\s=]+)=(?:"([^"]*)"|([^\s]*))'
for match in re.finditer(pattern, attrs_str):
key, quoted_val, unquoted_val = match.groups()
if key not in ['name', 'ch']: # Skip if we already handled these
attrs[key] = quoted_val if quoted_val is not None else unquoted_val
return attrs
@staticmethod
def _extract_array_values(array_str: str, max_values: int) -> List[int]:
"""Extract values from array string and return as int list"""
values = [0] * max_values
if array_str:
# Handle quoted array
if array_str.startswith('"') and array_str.endswith('"'):
array_str = array_str[1:-1]
# Handle bracketed array
if array_str.startswith("[") and array_str.endswith("]"):
try:
array_str = array_str.strip('[]')
parts = array_str.split(',')
for i, part in enumerate(parts):
if i >= max_values:
break
values[i] = round(float(part.strip()))
except ValueError:
pass
# Handle space-separated values
else:
parts = array_str.split()
for i, part in enumerate(parts):
if i >= max_values:
break
try:
values[i] = round(float(part))
except ValueError:
pass
return values
@staticmethod
def _format_value(value, preserve_int=True):
"""Format value as integer with proper rounding"""
val = float(value)
# Handle special case for very small values
if abs(val) < 1e-10:
return 0
# Always round to integer
return val
def to_sequence(self) -> str:
"""Convert LottieTensor to sequence string"""
lines = []
current_context = None
string_params = getattr(self, 'string_params', {})
for i in range(self.seq_len.item()):
cmd_idx = int(self.commands[i].item())
# Skip padding and special tokens
if cmd_idx in [LottieTensor.CMD_PAD, LottieTensor.CMD_EOS, LottieTensor.CMD_SOS]:
continue
cmd = LottieTensor.COMMANDS[cmd_idx]
if not cmd: # Skip empty command entries
continue
cmd_key = f"{i}"
# Handle end tags
if cmd.startswith('/'):
lines.append(f"({cmd})")
# Reset context
if cmd in ["/position", "/scale", "/opacity", "/rotation", "/keyframe", "/anchor", "/path", "/width_animated",
"/range_start", "/range_end", "/range_offset", "/scale_animators", "/rotation_animators",
"/position_x", "/position_y", "/position_z", "/tm", "/start", "/end", "/offset", "/color_animated", "/size", "/rounded"]:
current_context = None
continue
# Update context
if cmd in ["position", "scale", "opacity", "rotation", "anchor"]:
current_context = cmd
elif cmd == "size":
# Check if size is animated
params = self.params[i].tolist()
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
current_context = "size"
elif cmd in ["ellipse_size", "rect_size"]:
# Check if size is animated
params = self.params[i].tolist()
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
current_context = "size"
elif cmd in ["position_x", "position_y", "position_z"]:
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
current_context = cmd
elif cmd == "path":
# Check if path is animated (would be stored in string_params)
if f"{cmd_key}_animated" in string_params:
current_context = "path"
elif cmd == "width_keyframe":
current_context = "width"
elif cmd == "start":
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
current_context = "trim_start"
elif cmd == "end":
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
current_context = "trim_end"
elif cmd == "offset":
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
current_context = "trim_offset"
elif cmd == "mask_x":
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.MaskX.A] > 0.5:
current_context = "mask_x"
elif cmd == "scale_animators":
params = self.params[i].tolist()
if params[LottieTensor.Index.ScaleAnimators.A] > 0.5:
current_context = "scale_animators"
elif cmd == "rotation_animators":
params = self.params[i].tolist()
if params[LottieTensor.Index.RotationAnimators.A] > 0.5:
current_context = "rotation_animators"
elif cmd == "opacity_animators":
params = self.params[i].tolist()
if params[LottieTensor.Index.OpacityAnimators.A] > 0.5:
current_context = "opacity_animators"
elif cmd == "position_animators":
params = self.params[i].tolist()
if params[LottieTensor.Index.PositionAnimators.A] > 0.5:
current_context = "position_animators"
elif cmd == "tracking_animators":
params = self.params[i].tolist()
if params[LottieTensor.Index.TrackingAnimators.A] > 0.5:
current_context = "tracking_animators"
elif cmd == "rect_rounded":
# Check if animated
params = self.params[i].tolist()
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
current_context = "rect_rounded"
elif cmd in ["ellipse_size", "rect_size"]:
# Check if ellipse/rect size is animated
params = self.params[i].tolist()
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
current_context = "size"
# Extract parameters
params = self.params[i].tolist()
# Format line based on command type
if cmd_idx == LottieTensor.CMD_ANIMATION:
# Use stored string values if available
#v = string_params.get(f"{cmd_key}_v", "5.12.1")
v = "5.12.1"
#nm = string_params.get(f"{cmd_key}_nm", "Comp 1")
#markers = string_params.get(f"{cmd_key}_markers", "[]")
#props = string_params.get(f"{cmd_key}_props", "{}")
fr = LottieTensor._format_value(params[LottieTensor.Index.Animation.FR])
ip = LottieTensor._format_value(params[LottieTensor.Index.Animation.IP])
op = LottieTensor._format_value(params[LottieTensor.Index.Animation.OP])
w = LottieTensor._format_value(params[LottieTensor.Index.Animation.W])
h = LottieTensor._format_value(params[LottieTensor.Index.Animation.H])
ddd = int(params[LottieTensor.Index.Animation.DDD])
lines.append(f'({cmd} v="{v}" fr={fr} ip={ip} op={op} w={w} h={h} ddd={ddd})')
elif cmd_idx in [LottieTensor.CMD_FONTS, LottieTensor.CMD_FONTS_END, LottieTensor.CMD_CHARS,
LottieTensor.CMD_CHARS_END, LottieTensor.CMD_CHAR_SHAPES,
LottieTensor.CMD_CHAR_SHAPES_END, LottieTensor.CMD_TEXT_KEYFRAMES,
LottieTensor.CMD_TEXT_KEYFRAMES_END, LottieTensor.CMD_TEXT_DATA,
LottieTensor.CMD_TEXT_DATA_END, LottieTensor.CMD_OPACITY_ANIMATED_END,
LottieTensor.CMD_END_END, LottieTensor.CMD_START_END,
LottieTensor.CMD_OFFSET_END, LottieTensor.CMD_OPACITY_ANIMATORS_END]:
lines.append(f"({cmd})")
continue
elif cmd_idx in [LottieTensor.CMD_POSITION_X, LottieTensor.CMD_POSITION_Y, LottieTensor.CMD_POSITION_Z]:
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
current_context = cmd # Set context
else:
val = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
lines.append(f"({cmd} {val})")
# line based on command type
# Keep all existing formatting logic but update text_keyframe
elif cmd_idx == LottieTensor.CMD_TEXT_KEYFRAME:
# Initialize tokenizer if not already done
if LottieTensor.tokenizer is None:
LottieTensor.init_tokenizer()
t = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.T])
# Retrieve all stored attributes
# Retrieve numeric values
font_size = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.FONT_SIZE])
ca = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.CA])
justify = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.JUSTIFY])
tracking = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.TRACKING])
line_height = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.LINE_HEIGHT])
letter_spacing = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.LETTER_SPACING])
# Retrieve fill_color from numeric params
fill_r = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.FILL_COLOR_R]/255)
fill_g = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.FILL_COLOR_G]/255)
fill_b = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.FILL_COLOR_B]/255)
fill_color = f"[{fill_r},{fill_g},{fill_b}]"
# Retrieve string values
#font_family = string_params.get(f"{cmd_key}_font_family", "")
#text = string_params.get(f"{cmd_key}_text", "")
# Decode font_family from tokens
font_family = ""
font_family_count = int(params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT]) if params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT] > -2000 else 0
if font_family_count > 0:
font_family_tokens = []
for i in range(min(font_family_count, 10)):
token_val = params[LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START + i]
if token_val > -2000:
font_family_tokens.append(int(token_val))
if font_family_tokens:
try:
font_family = LottieTensor.tokenizer.decode(font_family_tokens)
except:
font_family = ""
# Decode text from tokens
text = ""
text_count = int(params[LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT]) if params[LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT] > -2000 else 0
if text_count > 0:
text_tokens = []
for i in range(min(text_count, 15)):
token_val = params[LottieTensor.Index.TextKeyframe.TEXT_TOKENS_START + i]
if token_val > -2000:
text_tokens.append(int(token_val))
if text_tokens:
try:
text = LottieTensor.tokenizer.decode(text_tokens)
except:
text = ""
# Build the output line
line = f'({cmd} t={t} font_size={font_size} font_family="{font_family}" text="{text}" ca={ca} justify={justify} tracking={tracking} line_height={line_height} letter_spacing={letter_spacing} fill_color={fill_color}'
# Add stroke_color if present
if params[LottieTensor.Index.TextKeyframe.HAS_STROKE_COLOR] > 0.5:
stroke_r = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_R]/255)
stroke_g = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_G]/255)
stroke_b = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.STROKE_COLOR_B]/255)
stroke_color = f"[{stroke_r},{stroke_g},{stroke_b}]"
line += f' stroke_color={stroke_color}'
# Add stroke_width if present and not zero
stroke_width = params[LottieTensor.Index.TextKeyframe.STROKE_WIDTH] if params[LottieTensor.Index.TextKeyframe.STROKE_WIDTH] > -2000 else 0
if abs(stroke_width) > 1e-6:
line += f' stroke_width={LottieTensor._format_value(stroke_width)}'
# Add offset if true
if params[LottieTensor.Index.TextKeyframe.OFFSET] > 0.5:
line += ' offset=true'
# Add wrap_position if present (新增)
wrap_pos_x = params[LottieTensor.Index.TextKeyframe.WRAP_POSITION_X]
wrap_pos_y = params[LottieTensor.Index.TextKeyframe.WRAP_POSITION_Y]
if wrap_pos_x > -2000 and wrap_pos_y > -2000:
line += f' wrap_position=[{LottieTensor._format_value(wrap_pos_x)},{LottieTensor._format_value(wrap_pos_y)}]'
# Add wrap_size if present (新增)
wrap_size_x = params[LottieTensor.Index.TextKeyframe.WRAP_SIZE_X]
wrap_size_y = params[LottieTensor.Index.TextKeyframe.WRAP_SIZE_Y]
if wrap_size_x > -2000 and wrap_size_y > -2000:
line += f' wrap_size=[{LottieTensor._format_value(wrap_size_x)},{LottieTensor._format_value(wrap_size_y)}]'
line += ')'
lines.append(line)
elif cmd_idx == LottieTensor.CMD_STAR:
#name = string_params.get(f"{cmd_key}_name", "None")
d = int(params[LottieTensor.Index.Star.D]) if params[LottieTensor.Index.Star.D] > -2000 else 1
sy = int(params[LottieTensor.Index.Star.SY]) if params[LottieTensor.Index.Star.SY] > -2000 else 1
lines.append(f'({cmd} d={d} sy={sy})')
elif cmd_idx == LottieTensor.CMD_INNER_RADIUS:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_OUTER_RADIUS:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_INNER_ROUNDNESS:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_OUTER_ROUNDNESS:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_POINTS_STAR: # 这会输出 points_star
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'(points_star {val})') # 强制输出为 points_star
elif cmd_idx == LottieTensor.CMD_STAR_ROTATION:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_MORE_OPTIONS:
# Reconstruct more_options line
g = int(params[LottieTensor.Index.MoreOptions.G]) if params[LottieTensor.Index.MoreOptions.G] > -2000 else 1
alignment_a = int(params[LottieTensor.Index.MoreOptions.ALIGNMENT_A]) if params[LottieTensor.Index.MoreOptions.ALIGNMENT_A] > -2000 else 0
alignment_k1 = int(params[LottieTensor.Index.MoreOptions.ALIGNMENT_K1]) if params[LottieTensor.Index.MoreOptions.ALIGNMENT_K1] > -2000 else 0
alignment_k2 = int(params[LottieTensor.Index.MoreOptions.ALIGNMENT_K2]) if params[LottieTensor.Index.MoreOptions.ALIGNMENT_K2] > -2000 else 0
alignment_ix = int(params[LottieTensor.Index.MoreOptions.ALIGNMENT_IX]) if params[LottieTensor.Index.MoreOptions.ALIGNMENT_IX] > -2000 else 2
lines.append(f'({cmd} g {g} alignment a={alignment_a} alignment_k {alignment_k1} {alignment_k2} alignment_ix {alignment_ix})')
elif cmd_idx == LottieTensor.CMD_LAYER:
# Use stored layer name if available
#name = string_params.get(f"{cmd_key}_name", "Layer")
index = LottieTensor._format_value(params[LottieTensor.Index.Layer.INDEX])
in_point = LottieTensor._format_value(params[LottieTensor.Index.Layer.IN_POINT])
out_point = LottieTensor._format_value(params[LottieTensor.Index.Layer.OUT_POINT])
start_time = LottieTensor._format_value(params[LottieTensor.Index.Layer.START_TIME])
# 开始构建输出行
line = f'({cmd} index={index} in_point={in_point} out_point={out_point} start_time={start_time}'
# 只输出非默认/非填充值的可选参数
if params[LottieTensor.Index.Layer.DDD] > -2000:
ddd = int(params[LottieTensor.Index.Layer.DDD])
line += f' ddd={ddd}'
#if params[LottieTensor.Index.Layer.HD] > -2000:
# hd = "true" if params[LottieTensor.Index.Layer.HD] > 0.5 else "false"
# line += f' hd={hd}'
if params[LottieTensor.Index.Layer.HD] > -2000 and params[LottieTensor.Index.Layer.HD] > 0.5:
line += f' hd=true'
if params[LottieTensor.Index.Layer.CP] > -2000:
cp = "true" if params[LottieTensor.Index.Layer.CP] > 0.5 else "false"
line += f' cp={cp}'
if params[LottieTensor.Index.Layer.CT] > -2000:
ct = int(params[LottieTensor.Index.Layer.CT])
line += f' ct={ct}'
if params[LottieTensor.Index.Layer.HAS_MASK] > -2000:
hasMask = "true" if params[LottieTensor.Index.Layer.HAS_MASK] > 0.5 else "false"
line += f' hasMask={hasMask}'
# masksProperties 总是作为字符串存储
masksProperties = string_params.get(f"{cmd_key}_masksProperties", "")
if masksProperties:
line += f' masksProperties={masksProperties}'
if params[LottieTensor.Index.Layer.AO] > -2000:
ao = int(params[LottieTensor.Index.Layer.AO])
line += f' ao={ao}'
if params[LottieTensor.Index.Layer.TT] > -2000:
tt = int(params[LottieTensor.Index.Layer.TT])
line += f' tt={tt}'
if params[LottieTensor.Index.Layer.TP] > -2000:
tp = int(params[LottieTensor.Index.Layer.TP])
line += f' tp={tp}'
if params[LottieTensor.Index.Layer.TD] > -2000:
td = int(params[LottieTensor.Index.Layer.TD])
line += f' td={td}'
line += ')'
lines.append(line)
elif cmd_idx == LottieTensor.CMD_NULL_LAYER:
# Use stored layer name if available
#name = string_params.get(f"{cmd_key}_name", "null_layer")
index = LottieTensor._format_value(params[LottieTensor.Index.NullLayer.INDEX])
in_point = LottieTensor._format_value(params[LottieTensor.Index.NullLayer.IN_POINT])
out_point = LottieTensor._format_value(params[LottieTensor.Index.NullLayer.OUT_POINT])
start_time = LottieTensor._format_value(params[LottieTensor.Index.NullLayer.START_TIME])
line = f'({cmd} index={index} in_point={in_point} out_point={out_point} start_time={start_time}'
#lines.append(f'({cmd} index={index} name="{name}" in_point={in_point} out_point={out_point} start_time={start_time} ct={ct})')
if params[LottieTensor.Index.PrecompLayer.HD] > -2000 and params[LottieTensor.Index.PrecompLayer.HD] > 0.5:
line += f' hd=true'
if params[LottieTensor.Index.PrecompLayer.CP] > -2000:
cp = "true" if params[LottieTensor.Index.PrecompLayer.CP] > 0.5 else "false"
line += f' cp={cp}'
if params[LottieTensor.Index.PrecompLayer.HAS_MASK] > -2000:
hasMask = "true" if params[LottieTensor.Index.PrecompLayer.HAS_MASK] > 0.5 else "false"
line += f' hasMask={hasMask}'
if params[LottieTensor.Index.PrecompLayer.AO] > -2000:
ao = int(params[LottieTensor.Index.PrecompLayer.AO])
line += f' ao={ao}'
if params[LottieTensor.Index.PrecompLayer.TT] > -2000:
tt = int(params[LottieTensor.Index.PrecompLayer.TT])
line += f' tt={tt}'
if params[LottieTensor.Index.PrecompLayer.TP] > -2000:
tp = int(params[LottieTensor.Index.PrecompLayer.TP])
line += f' tp={tp}'
if params[LottieTensor.Index.PrecompLayer.TD] > -2000:
td = int(params[LottieTensor.Index.PrecompLayer.TD])
line += f' td={td}'
line += ')'
lines.append(line)
elif cmd_idx == LottieTensor.CMD_PRECOMP_LAYER:
# Use stored layer name if available
#name = string_params.get(f"{cmd_key}_name", "precomp_layer")
index = LottieTensor._format_value(params[LottieTensor.Index.PrecompLayer.INDEX])
in_point = LottieTensor._format_value(params[LottieTensor.Index.PrecompLayer.IN_POINT])
out_point = LottieTensor._format_value(params[LottieTensor.Index.PrecompLayer.OUT_POINT])
start_time = LottieTensor._format_value(params[LottieTensor.Index.PrecompLayer.START_TIME])
# Output w and h with full precision
#w = params[LottieTensor.Index.PrecompLayer.W]
#h = params[LottieTensor.Index.PrecompLayer.H]
# Format w and h preserving their full precision
# Check if the value is very close to an integer
#if abs(w - round(w)) < 1e-10:
# w_str = str(int(round(w)))
#else:
# Keep full precision for non-integer values
# w_str = str(w)
#if abs(h - round(h)) < 1e-10:
# h_str = str(int(round(h)))
#else:
# Keep full precision for non-integer values
# h_str = str(h)
line = f'({cmd} index={index} in_point={in_point} out_point={out_point} start_time={start_time}'
if params[LottieTensor.Index.PrecompLayer.H] > -2000:
h = int(params[LottieTensor.Index.PrecompLayer.H])
line += f' h={h}'
if params[LottieTensor.Index.PrecompLayer.W] > -2000:
w = int(params[LottieTensor.Index.PrecompLayer.W])
line += f' w={w}'
if params[LottieTensor.Index.PrecompLayer.DDD] > -2000:
ddd = int(params[LottieTensor.Index.PrecompLayer.DDD])
line += f' ddd={ddd}'
if params[LottieTensor.Index.PrecompLayer.HD] > -2000 and params[LottieTensor.Index.PrecompLayer.HD] > 0.5:
line += f' hd=true'
if params[LottieTensor.Index.PrecompLayer.CP] > -2000:
cp = "true" if params[LottieTensor.Index.PrecompLayer.CP] > 0.5 else "false"
line += f' cp={cp}'
if params[LottieTensor.Index.PrecompLayer.CT] > -2000:
ct = int(params[LottieTensor.Index.PrecompLayer.CT])
line += f' ct={ct}'
if params[LottieTensor.Index.PrecompLayer.HAS_MASK] > -2000:
hasMask = "true" if params[LottieTensor.Index.PrecompLayer.HAS_MASK] > 0.5 else "false"
line += f' hasMask={hasMask}'
# masksProperties 总是作为字符串存储
masksProperties = string_params.get(f"{cmd_key}_masksProperties", "")
if masksProperties:
line += f' masksProperties={masksProperties}'
if params[LottieTensor.Index.PrecompLayer.AO] > -2000:
ao = int(params[LottieTensor.Index.PrecompLayer.AO])
line += f' ao={ao}'
if params[LottieTensor.Index.PrecompLayer.TT] > -2000:
tt = int(params[LottieTensor.Index.PrecompLayer.TT])
line += f' tt={tt}'
if params[LottieTensor.Index.PrecompLayer.TP] > -2000:
tp = int(params[LottieTensor.Index.PrecompLayer.TP])
line += f' tp={tp}'
if params[LottieTensor.Index.PrecompLayer.TD] > -2000:
td = int(params[LottieTensor.Index.PrecompLayer.TD])
line += f' td={td}'
line += ')'
lines.append(line)
elif cmd_idx == LottieTensor.CMD_REFERENCE_ID:
# Get tokenizer
tokenizer = LottieTensor.get_tokenizer()
# Decode reference_id from tokens
id_count = int(params[LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT]) if params[LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT] > -2000 else 0
id_tokens = []
for i in range(id_count):
if params[LottieTensor.Index.ReferenceId.ID_TOKEN_0 + i] > -2000:
id_tokens.append(int(params[LottieTensor.Index.ReferenceId.ID_TOKEN_0 + i]))
reference_id = tokenizer.decode(id_tokens, skip_special_tokens=True) if id_tokens else "comp_0"
lines.append(f'({cmd} "{reference_id}")')
elif cmd_idx == LottieTensor.CMD_DIMENSIONS:
# 输出dimensions命令
width = LottieTensor._format_value(params[LottieTensor.Index.Dimensions.WIDTH])
height = LottieTensor._format_value(params[LottieTensor.Index.Dimensions.HEIGHT])
lines.append(f'({cmd} width={width} height={height})')
elif cmd_idx == LottieTensor.CMD_STROKE:
#name = string_params.get(f"{cmd_key}_name", "Stroke")
color_animated = params[LottieTensor.Index.Stroke.COLOR_ANIMATED] > 0.5
line = f'({cmd}'
if color_animated:
line += ' color_animated=true'
else:
# Convert RGB values from 0-255 back to 0-1 range
r = LottieTensor._format_value(params[LottieTensor.Index.Stroke.R] / 255)
g = LottieTensor._format_value(params[LottieTensor.Index.Stroke.G] / 255)
b = LottieTensor._format_value(params[LottieTensor.Index.Stroke.B] / 255)
a = LottieTensor._format_value(params[LottieTensor.Index.Stroke.A] / 255)
line += f' r={r} g={g} b={b} a={a}'
color_dim = int(params[LottieTensor.Index.Stroke.COLOR_DIM]) if params[LottieTensor.Index.Stroke.COLOR_DIM] > -2000 else 4
has_c_a = "True" if params[LottieTensor.Index.Stroke.HAS_C_A] > 0.5 else "False"
has_c_ix = "True" if params[LottieTensor.Index.Stroke.HAS_C_IX] > 0.5 else "False"
c_ix = int(params[LottieTensor.Index.Stroke.C_IX]) if params[LottieTensor.Index.Stroke.C_IX] > -2000 else 3
bm = int(params[LottieTensor.Index.Stroke.BM]) if params[LottieTensor.Index.Stroke.BM] > -2000 else 0
lc = int(params[LottieTensor.Index.Stroke.LC]) if params[LottieTensor.Index.Stroke.LC] > -2000 else 1
lj = int(params[LottieTensor.Index.Stroke.LJ]) if params[LottieTensor.Index.Stroke.LJ] > -2000 else 1
ml = int(params[LottieTensor.Index.Stroke.ML]) if params[LottieTensor.Index.Stroke.ML] > -2000 else 4
line += f' color_dim={color_dim} has_c_a={has_c_a} has_c_ix={has_c_ix}'
if not color_animated:
line += f' c_ix={c_ix}'
line += f' bm={bm} lc={lc} lj={lj} ml={ml}'
# Check if width is animated
width_animated = params[LottieTensor.Index.Stroke.WIDTH_ANIMATED] > 0.5
if width_animated:
line += ' width_animated=true'
current_context = "width"
# IMPORTANT: Close the parenthesis here
line += ')'
lines.append(line)
# Add the separate (width_animated true) command after the stroke
if width_animated:
lines.append('(width_animated true)')
if color_animated:
current_context = "stroke_color"
# Add dashes output in to_sequence method (after line 5800):
elif cmd_idx == LottieTensor.CMD_DASHES:
# Check if we have the complete dashes string stored
dashes_str = string_params.get(f"{cmd_key}_dashes", "")
if dashes_str:
# The stored string already includes quotes if needed, don't add extra quotes
lines.append(f'({cmd} {dashes_str})')
else:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_DASH:
type_map = {0: "d", 1: "g", 2: "o"}
type_val = int(params[LottieTensor.Index.Dash.TYPE]) if params[LottieTensor.Index.Dash.TYPE] > -2000 else 0
dash_type = type_map.get(type_val, "d")
# 除以100恢复原值
length = LottieTensor._format_value(params[LottieTensor.Index.Dash.LENGTH] / 10, preserve_int=False)
v_ix = int(params[LottieTensor.Index.Dash.V_IX]) if params[LottieTensor.Index.Dash.V_IX] > -2000 else 1
lines.append(f'({cmd} type="{dash_type}" length={length} v_ix={v_ix})')
elif cmd_idx == LottieTensor.CMD_DASH_ANIMATED:
# Convert numeric type back to string
type_map = {0: "d", 1: "g", 2: "o"}
type_val = int(params[LottieTensor.Index.DashAnimated.TYPE]) if params[LottieTensor.Index.DashAnimated.TYPE] > -2000 else 2
dash_type = type_map.get(type_val, "o")
v_ix = int(params[LottieTensor.Index.DashAnimated.V_IX]) if params[LottieTensor.Index.DashAnimated.V_IX] > -2000 else 7
# Get name from string_params
name = string_params.get(f"{cmd_key}_name", "")
lines.append(f'({cmd} type="{dash_type}" name="{name}" v_ix={v_ix})')
current_context = "dash_animated"
elif cmd_idx == LottieTensor.CMD_DASH_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.DashKeyframe.T])
# 除以100恢复原值
s = LottieTensor._format_value(params[LottieTensor.Index.DashKeyframe.S] / 10, preserve_int=False)
i_x = params[LottieTensor.Index.DashKeyframe.I_X]/100
i_y = params[LottieTensor.Index.DashKeyframe.I_Y]/100
o_x = params[LottieTensor.Index.DashKeyframe.O_X]/100
o_y = params[LottieTensor.Index.DashKeyframe.O_Y]/100
has_easing = (i_x > -2000 or i_y > -2000 or o_x > -2000 or o_y > -2000)
if has_easing:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
lines.append(f'({cmd} t={t} s={s} i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val})')
else:
lines.append(f'({cmd} t={t} s={s})')
elif cmd_idx == LottieTensor.CMD_DASH_ANIMATED_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_DASH_OFFSET:
# 除以100恢复原值
o = LottieTensor._format_value(params[LottieTensor.Index.DashOffset.O] / 10, preserve_int=False)
lines.append(f'({cmd} {o})')
elif cmd_idx == LottieTensor.CMD_DASHES_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_DASH_ANIMATED_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_SIZE_END:
lines.append(f'({cmd})')
# 7. Add output for color_keyframe:
elif cmd_idx == LottieTensor.CMD_COLOR_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.T])
r = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.S1]/255)
g = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.S2]/255)
b = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.S3]/255)
a = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1]/255)
i_x = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_X]/100, preserve_int=False)
i_y = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_Y]/100, preserve_int=False)
o_x = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_X]/100, preserve_int=False)
o_y = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_Y]/100, preserve_int=False)
lines.append(f'({cmd} t={t} r={r} g={g} b={b} a={a} i_x={i_x} i_y={i_y} o_x={o_x} o_y={o_y})')
elif cmd_idx == LottieTensor.CMD_OPACITY_ANIMATED:
lines.append(f'({cmd} true)')
current_context = "opacity_animated"
elif cmd_idx == LottieTensor.CMD_OPACITY_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.T])
keyframe_line = f'({cmd} t={t}'
# Check if s parameter is valid
if params[LottieTensor.Index.Keyframe.S1] > -2000:
s = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.S1])
keyframe_line += f' s={s}'
# Check if easing parameters exist
i_x = params[LottieTensor.Index.Keyframe.I_X]/100
i_y = params[LottieTensor.Index.Keyframe.I_Y]/100
o_x = params[LottieTensor.Index.Keyframe.O_X]/100
o_y = params[LottieTensor.Index.Keyframe.O_Y]/100
if i_x > -2000 or i_y > -2000 or o_x > -2000 or o_y > -2000:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
keyframe_line += f' i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val}'
keyframe_line += ')'
lines.append(keyframe_line)
elif cmd_idx == LottieTensor.CMD_WIDTH_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.WidthKeyframe.T])
keyframe_line = f'({cmd} t={t}'
# Check if s parameter is valid - 除以100恢复原值
if params[LottieTensor.Index.WidthKeyframe.S] > -2000:
s = LottieTensor._format_value(params[LottieTensor.Index.WidthKeyframe.S] / 10, preserve_int=False)
keyframe_line += f' s={s}'
# easing参数处理（保持不变，除以100）
i_x = params[LottieTensor.Index.WidthKeyframe.I_X]/100
i_y = params[LottieTensor.Index.WidthKeyframe.I_Y]/100
o_x = params[LottieTensor.Index.WidthKeyframe.O_X]/100
o_y = params[LottieTensor.Index.WidthKeyframe.O_Y]/100
has_easing = (i_x > -2000 or i_y > -2000 or o_x > -2000 or o_y > -2000)
if has_easing:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
keyframe_line += f' i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val}'
keyframe_line += ")"
lines.append(keyframe_line)
elif cmd_idx == LottieTensor.CMD_TRANSFORM:
lines.append(f"({cmd})")
elif cmd_idx == LottieTensor.CMD_POSITION:
if cmd == "position" and current_context not in ["position", "scale", "opacity", "rotation", "anchor"]:
# This is a position command for shapes (ellipse, rect, etc.)
x = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE1])
y = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE2])
lines.append(f"({cmd} {x} {y})")
else:
# This is a transform position
if params[LottieTensor.Index.Transform.ANIMATED] == 2.0:
# Separated position (for 3D layers)
lines.append(f"({cmd} separated=true)")
elif params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
else:
x = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
y = LottieTensor._format_value(params[LottieTensor.Index.Transform.Y])
z = LottieTensor._format_value(params[LottieTensor.Index.Transform.Z])
# Check if Z is meaningful
if params[LottieTensor.Index.Transform.Z] > -2000 and abs(params[LottieTensor.Index.Transform.Z]) > 1e-6:
lines.append(f"({cmd} {x} {y} {z})")
else:
lines.append(f"({cmd} {x} {y})")
elif cmd_idx == LottieTensor.CMD_POSITION_X:
# Output position_x with its value
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
value = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f"({cmd} {value})")
else:
lines.append(f"({cmd})")
elif cmd_idx == LottieTensor.CMD_POSITION_Y:
# Output position_y with its value
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
value = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f"({cmd} {value})")
else:
lines.append(f"({cmd})")
elif cmd_idx == LottieTensor.CMD_POSITION_Z:
# Output position_z with its value
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
value = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f"({cmd} {value})")
else:
lines.append(f"({cmd})")
elif cmd_idx == LottieTensor.CMD_SCALE:
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
else:
x = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
y = LottieTensor._format_value(params[LottieTensor.Index.Transform.Y])
z = LottieTensor._format_value(params[LottieTensor.Index.Transform.Z])
# Check if Z is meaningful - output Z if it's not padding value
if params[LottieTensor.Index.Transform.Z] > -2000:
lines.append(f"({cmd} {x} {y} {z})")
else:
lines.append(f"({cmd} {x} {y})")
elif cmd_idx == LottieTensor.CMD_ROTATION:
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
else:
angle = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
lines.append(f"({cmd} {angle})")
elif cmd_idx == LottieTensor.CMD_OPACITY:
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
else:
val = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
lines.append(f"({cmd} {val})")
elif cmd_idx == LottieTensor.CMD_ANCHOR:
if params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f"({cmd} animated=true)")
else:
x = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
y = LottieTensor._format_value(params[LottieTensor.Index.Transform.Y])
z = LottieTensor._format_value(params[LottieTensor.Index.Transform.Z])
# Check if Z is meaningful
if params[LottieTensor.Index.Transform.Z] > -2000 and abs(params[LottieTensor.Index.Transform.Z]) > 1e-6:
lines.append(f"({cmd} {x} {y} {z})")
else:
lines.append(f"({cmd} {x} {y})")
elif cmd_idx == LottieTensor.CMD_TM:
a = int(params[LottieTensor.Index.Tm.A]) if params[LottieTensor.Index.Tm.A] > -2000 else 1
# Always output a parameter
lines.append(f'({cmd} a={a})')
# Set context based on a value
if a > 0.5:
current_context = "tm" # Set context for keyframes
else:
current_context = "tm_static" # Reset context for static value
# Add value command output
elif cmd_idx == LottieTensor.CMD_VALUE:
val = LottieTensor._format_value(params[LottieTensor.Index.Value.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.T])
keyframe_line = f'({cmd} t={t}'
# Check if this is a hold keyframe (using H_FLAG slot)
is_hold = params[LottieTensor.Index.Keyframe.H_FLAG] > 0.5
# Check if s parameter is valid (not padding)
has_s = params[LottieTensor.Index.Keyframe.S1] > -2000
# Only add s parameter if valid and not in path context
if has_s and current_context != "path":
# Format s parameter based on context
if current_context in ["opacity", "rotation", "position_x", "position_y", "position_z", "tm", "width",
"trim_start", "trim_end", "trim_offset", "mask_x", "rotation_animators", "opacity_animators", "tracking_animators"]:
# For single-value properties
s = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.S1], preserve_int=False)
s_str = f'"{s}"'
else:
# For position, scale, anchor - output only non-padding values
s1 = params[LottieTensor.Index.Keyframe.S1]
s2 = params[LottieTensor.Index.Keyframe.S2]
s3 = params[LottieTensor.Index.Keyframe.S3]
s_parts = []
s_parts.append(str(LottieTensor._format_value(s1, preserve_int=False)))
s_parts.append(str(LottieTensor._format_value(s2, preserve_int=False)))
# Only add s3 if it's not padding value and not zero (for 2D animations)
if s3 > -2000 and abs(s3) > 1e-6:
s_parts.append(str(LottieTensor._format_value(s3, preserve_int=False)))
s_str = f'"{" ".join(s_parts)}"'
keyframe_line += f' s={s_str}'
# Check and output e parameter based on context - MODIFIED TO INCLUDE TRIM CONTEXTS
has_e = params[LottieTensor.Index.Keyframe.E1] > -2000
if has_e: # Output e regardless of hold flag
if current_context in ["trim_start", "trim_end", "trim_offset"]:
# For trim contexts, output single e value as quoted string
e_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1], preserve_int=False)
keyframe_line += f' e="{e_val}"'
elif current_context == "rotation":
# For rotation, output single e value
e_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1], preserve_int=False)
keyframe_line += f' e="[{e_val}]"'
elif current_context == "scale":
# For scale, output three e values
e1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1], preserve_int=False) if params[LottieTensor.Index.Keyframe.E1] > -2000 else 0
e2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E2], preserve_int=False) if params[LottieTensor.Index.Keyframe.E2] > -2000 else 0
e3 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E3], preserve_int=False) if params[LottieTensor.Index.Keyframe.E3] > -2000 else 0
keyframe_line += f' e="[{e1}, {e2}, {e3}]"'
# Add other contexts as needed
# Handle hold keyframe
if is_hold:
keyframe_line += ' h=1'
# ALWAYS check and add easing parameters, regardless of hold flag
# The hold flag just means the value is held, but easing can still be defined
if current_context in ["position", "anchor", "scale_animators", "position_animators", "size"]:
# For multi-dimensional properties, output multi-dimensional easing
# Check if we have multi-dimensional easing values
has_multi_easing = (
params[LottieTensor.Index.Keyframe.I_X2] > -2000 or
params[LottieTensor.Index.Keyframe.I_Y2] > -2000 or
params[LottieTensor.Index.Keyframe.O_X2] > -2000 or
params[LottieTensor.Index.Keyframe.O_Y2] > -2000
)
if has_multi_easing:
# Format multi-dimensional easing - DIVIDE BY 100
i_x_vals = []
i_y_vals = []
o_x_vals = []
o_y_vals = []
# Always include first two dimensions - DIVIDE BY 100
i_x1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_X] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_X] > -2000 else 0
i_x2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_X2] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_X2] > -2000 else i_x1
i_x_vals = [i_x1, i_x2]
i_y1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_Y] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_Y] > -2000 else 0
i_y2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_Y2] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_Y2] > -2000 else i_y1
i_y_vals = [i_y1, i_y2]
o_x1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_X] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_X] > -2000 else 0
o_x2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_X2] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_X2] > -2000 else o_x1
o_x_vals = [o_x1, o_x2]
o_y1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_Y] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_Y] > -2000 else 0
o_y2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_Y2] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_Y2] > -2000 else o_y1
o_y_vals = [o_y1, o_y2]
# Only add third dimension if it exists and is non-zero - DIVIDE BY 100
i_x3 = params[LottieTensor.Index.Keyframe.I_X3]
i_y3 = params[LottieTensor.Index.Keyframe.I_Y3]
o_x3 = params[LottieTensor.Index.Keyframe.O_X3]
o_y3 = params[LottieTensor.Index.Keyframe.O_Y3]
# Check if ANY third dimension value is meaningful (not padding and not zero)
has_third_dim = (
(i_x3 > -2000 and abs(i_x3) > 1e-6) or
(i_y3 > -2000 and abs(i_y3) > 1e-6) or
(o_x3 > -2000 and abs(o_x3) > 1e-6) or
(o_y3 > -2000 and abs(o_y3) > 1e-6)
)
if has_third_dim:
i_x_vals.append(LottieTensor._format_value(i_x3 / 100, preserve_int=False) if i_x3 > -2000 else i_x1)
i_y_vals.append(LottieTensor._format_value(i_y3 / 100, preserve_int=False) if i_y3 > -2000 else i_y1)
o_x_vals.append(LottieTensor._format_value(o_x3 / 100, preserve_int=False) if o_x3 > -2000 else o_x1)
o_y_vals.append(LottieTensor._format_value(o_y3 / 100, preserve_int=False) if o_y3 > -2000 else o_y1)
keyframe_line += f' i_x="{" ".join(str(v) for v in i_x_vals)}" i_y="{" ".join(str(v) for v in i_y_vals)}" o_x="{" ".join(str(v) for v in o_x_vals)}" o_y="{" ".join(str(v) for v in o_y_vals)}"'
elif params[LottieTensor.Index.Keyframe.I_X] > -2000 or params[LottieTensor.Index.Keyframe.I_Y] > -2000 or params[LottieTensor.Index.Keyframe.O_X] > -2000 or params[LottieTensor.Index.Keyframe.O_Y] > -2000:
# Fallback to single values if no multi-dimensional values found - DIVIDE BY 100
i_x_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_X] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_X] > -2000 else 0
i_y_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.I_Y] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.I_Y] > -2000 else 0
o_x_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_X] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_X] > -2000 else 0
o_y_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.O_Y] / 100, preserve_int=False) if params[LottieTensor.Index.Keyframe.O_Y] > -2000 else 0
keyframe_line += f' i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val}'
else:
# For single-dimensional properties, parse single easing values - DIVIDE BY 100
i_x = params[LottieTensor.Index.Keyframe.I_X]
i_y = params[LottieTensor.Index.Keyframe.I_Y]
o_x = params[LottieTensor.Index.Keyframe.O_X]
o_y = params[LottieTensor.Index.Keyframe.O_Y]
if i_x > -2000 or i_y > -2000 or o_x > -2000 or o_y > -2000:
i_x_val = LottieTensor._format_value(i_x / 100, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y / 100, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x / 100, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y / 100, preserve_int=False) if o_y > -2000 else 0
keyframe_line += f' i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val}'
# Add to/ti parameters (they are separate from hold flag)
has_to = any(params[LottieTensor.Index.Keyframe.TO1 + j] > -2000 for j in range(3))
has_ti = any(params[LottieTensor.Index.Keyframe.TI1 + j] > -2000 for j in range(3))
if has_to:
to_values = []
for i in range(3):
val = params[LottieTensor.Index.Keyframe.TO1 + i]
if val > -2000:
to_values.append(LottieTensor._format_value(val, preserve_int=False))
else:
break # Stop at first padding value
# Only output non-zero values, but always include at least 2 dimensions if any exist
while len(to_values) > 2 and abs(to_values[-1]) < 1e-10:
to_values.pop() # Remove trailing zeros
# Ensure we have at least 2 values if we have any
while len(to_values) < 2:
to_values.append(0)
keyframe_line += f' to="[{", ".join(str(v) for v in to_values)}]"'
if has_ti:
ti_values = []
for i in range(3):
val = params[LottieTensor.Index.Keyframe.TI1 + i]
if val > -2000:
ti_values.append(LottieTensor._format_value(val, preserve_int=False))
else:
break # Stop at first padding value
# Only output non-zero values, but always include at least 2 dimensions if any exist
while len(ti_values) > 2 and abs(ti_values[-1]) < 1e-10:
ti_values.pop() # Remove trailing zeros
# Ensure we have at least 2 values if we have any
while len(ti_values) < 2:
ti_values.append(0)
keyframe_line += f' ti="[{", ".join(str(v) for v in ti_values)}]"'
# Check and output e parameter based on context
has_e = params[LottieTensor.Index.Keyframe.E1] > -2000
if has_e: # Output e regardless of hold flag
if current_context == "rotation":
# For rotation, output single e value
e_val = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1], preserve_int=False)
keyframe_line += f' e="[{e_val}]"'
elif current_context == "scale":
# For scale, output three e values
e1 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E1], preserve_int=False) if params[LottieTensor.Index.Keyframe.E1] > -2000 else 0
e2 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E2], preserve_int=False) if params[LottieTensor.Index.Keyframe.E2] > -2000 else 0
e3 = LottieTensor._format_value(params[LottieTensor.Index.Keyframe.E3], preserve_int=False) if params[LottieTensor.Index.Keyframe.E3] > -2000 else 0
keyframe_line += f' e="[{e1}, {e2}, {e3}]"'
# Add other contexts as needed
keyframe_line += ")"
lines.append(keyframe_line)
elif cmd_idx == LottieTensor.CMD_GROUP:
#name = string_params.get(f"{cmd_key}_name", "Group")
#mn = string_params.get(f"{cmd_key}_mn", "ADBE Vector Group")
ix = int(params[LottieTensor.Index.Group.IX]) if params[LottieTensor.Index.Group.IX] > -2000 else 1
cix = int(params[LottieTensor.Index.Group.CIX]) if params[LottieTensor.Index.Group.CIX] > -2000 else 2
bm = int(params[LottieTensor.Index.Group.BM]) if params[LottieTensor.Index.Group.BM] > -2000 else 0
hd = "true" if params[LottieTensor.Index.Group.HD] > 0.5 else "false"
np = int(params[LottieTensor.Index.Group.NP]) if params[LottieTensor.Index.Group.NP] > -2000 else 0
lines.append(f'({cmd} ix={ix} cix={cix} bm={bm} hd={hd} np={np})')
elif cmd_idx == LottieTensor.CMD_PATH:
#name = string_params.get(f"{cmd_key}_name", "Path")
#mn = string_params.get(f"{cmd_key}_mn", "ADBE Vector Path") # Add mn
ix = int(params[LottieTensor.Index.Path.IX]) if params[LottieTensor.Index.Path.IX] > -2000 else 1
ind = int(params[LottieTensor.Index.Path.IND]) if params[LottieTensor.Index.Path.IND] > -2000 else 0
ks_ix = int(params[LottieTensor.Index.Path.KS_IX]) if params[LottieTensor.Index.Path.KS_IX] > -2000 else 2
closed = "true" if params[LottieTensor.Index.Path.CLOSED] > 0.5 else "false"
hd = "true" if params[LottieTensor.Index.Path.HD] > 0.5 else "false" # Add HD
# Check if path is animated
if params[LottieTensor.Index.Path.ANIMATED] > 0.5:
lines.append(f'({cmd} ix={ix} ind={ind} ks_ix={ks_ix} animated="true" hd={hd})')
current_context = "path"
else:
lines.append(f'({cmd} ix={ix} ind={ind} ks_ix={ks_ix} closed={closed} hd={hd})')
elif cmd_idx == LottieTensor.CMD_POINT:
# Check if this is a valid point (not padding)
if params[LottieTensor.Index.Point.X] > -2000 and params[LottieTensor.Index.Point.Y] > -2000:
x = LottieTensor._format_value(params[LottieTensor.Index.Point.X])
y = LottieTensor._format_value(params[LottieTensor.Index.Point.Y])
in_x = LottieTensor._format_value(params[LottieTensor.Index.Point.IN_X])
in_y = LottieTensor._format_value(params[LottieTensor.Index.Point.IN_Y])
out_x = LottieTensor._format_value(params[LottieTensor.Index.Point.OUT_X])
out_y = LottieTensor._format_value(params[LottieTensor.Index.Point.OUT_Y])
lines.append(f"({cmd} x={x} y={y} in_x={in_x} in_y={in_y} out_x={out_x} out_y={out_y})")
# else: skip padding points
elif cmd_idx == LottieTensor.CMD_FILL:
#name = string_params.get(f"{cmd_key}_name", "Fill")
color_dim = int(params[LottieTensor.Index.Fill.COLOR_DIM]) if params[LottieTensor.Index.Fill.COLOR_DIM] > -2000 else 3
has_c_a = "True" if params[LottieTensor.Index.Fill.HAS_C_A] > 0.5 else "False"
has_c_ix = "True" if params[LottieTensor.Index.Fill.HAS_C_IX] > 0.5 else "False"
c_ix = int(params[LottieTensor.Index.Fill.C_IX]) if params[LottieTensor.Index.Fill.C_IX] > -2000 else 4
bm = int(params[LottieTensor.Index.Fill.BM]) if params[LottieTensor.Index.Fill.BM] > -2000 else 0
fill_rule = int(params[LottieTensor.Index.Fill.FILL_RULE]) if params[LottieTensor.Index.Fill.FILL_RULE] > -2000 else 1
has_o_a = "True" if params[LottieTensor.Index.Fill.HAS_O_A] > 0.5 else "False"
has_o_ix = "True" if params[LottieTensor.Index.Fill.HAS_O_IX] > 0.5 else "False"
o_ix = int(params[LottieTensor.Index.Fill.O_IX]) if params[LottieTensor.Index.Fill.O_IX] > -2000 else 5
color_animated = params[LottieTensor.Index.Fill.COLOR_ANIMATED] > 0.5
opacity_animated = params[LottieTensor.Index.Fill.OPACITY_ANIMATED] > 0.5
line_parts = [f'({cmd}']
# Handle color output
if color_animated:
# Output color keyframes with easing
color_keyframes_json = string_params.get(f"{cmd_key}_color_keyframes", "[]")
color_keyframes = json.loads(color_keyframes_json)
for i, kf in enumerate(color_keyframes):
line_parts.append(f' c_kf_{i}_t={LottieTensor._format_value(kf["t"])}')
line_parts.append(f' c_kf_{i}_r={LottieTensor._format_value(kf["r"]/255)}')
line_parts.append(f' c_kf_{i}_g={LottieTensor._format_value(kf["g"]/255)}')
line_parts.append(f' c_kf_{i}_b={LottieTensor._format_value(kf["b"]/255)}')
# Add easing parameters if they exist and are non-zero (divide by 100 for float output)
if "i_x" in kf and (abs(kf["i_x"]) > 1e-6 or abs(kf.get("i_y", 0)) > 1e-6 or
abs(kf.get("o_x", 0)) > 1e-6 or abs(kf.get("o_y", 0)) > 1e-6):
line_parts.append(f' c_kf_{i}_i_x={LottieTensor._format_value(kf["i_x"] / 100, preserve_int=False)}')
line_parts.append(f' c_kf_{i}_i_y={LottieTensor._format_value(kf.get("i_y", 0) / 100, preserve_int=False)}')
line_parts.append(f' c_kf_{i}_o_x={LottieTensor._format_value(kf.get("o_x", 0) / 100, preserve_int=False)}')
line_parts.append(f' c_kf_{i}_o_y={LottieTensor._format_value(kf.get("o_y", 0) / 100, preserve_int=False)}')
line_parts.append(f' c_kf_count={len(color_keyframes)}')
line_parts.append(' color_animated=true')
else:
# Output static color
r = LottieTensor._format_value(params[LottieTensor.Index.Fill.R]/255)
g = LottieTensor._format_value(params[LottieTensor.Index.Fill.G]/255)
b = LottieTensor._format_value(params[LottieTensor.Index.Fill.B]/255)
line_parts.append(f' r={r} g={g} b={b} color_animated=false')
# Add common color parameters
line_parts.append(f' color_dim={color_dim} has_c_a={has_c_a} has_c_ix={has_c_ix} c_ix={c_ix} bm={bm} fill_rule={fill_rule}')
# Handle opacity output
if opacity_animated:
# Output opacity keyframes (divide by 100 for float output)
opacity_keyframes_json = string_params.get(f"{cmd_key}_opacity_keyframes", "[]")
opacity_keyframes = json.loads(opacity_keyframes_json)
for i, kf in enumerate(opacity_keyframes):
line_parts.append(f' o_kf_{i}_t={LottieTensor._format_value(kf["t"])}')
line_parts.append(f' o_kf_{i}_s={LottieTensor._format_value(kf["s"])}')
line_parts.append(f' o_kf_{i}_i_x={LottieTensor._format_value(kf["i_x"] / 100, preserve_int=False)}')
line_parts.append(f' o_kf_{i}_i_y={LottieTensor._format_value(kf["i_y"] / 100, preserve_int=False)}')
line_parts.append(f' o_kf_{i}_o_x={LottieTensor._format_value(kf["o_x"] / 100, preserve_int=False)}')
line_parts.append(f' o_kf_{i}_o_y={LottieTensor._format_value(kf["o_y"] / 100, preserve_int=False)}')
line_parts.append(f' o_kf_count={len(opacity_keyframes)}')
line_parts.append(' opacity_animated=true')
else:
# Output static opacity
opacity = LottieTensor._format_value(params[LottieTensor.Index.Fill.OPACITY])
line_parts.append(f' opacity={opacity} opacity_animated=false')
# Add opacity-related parameters
line_parts.append(f' has_o_a={has_o_a} has_o_ix={has_o_ix} o_ix={o_ix})')
lines.append(''.join(line_parts))
elif cmd_idx == LottieTensor.CMD_BEZIER:
closed = "true" if params[LottieTensor.Index.Bezier.CLOSED] > 0.5 else "false"
lines.append(f'({cmd} closed={closed})')
elif cmd_idx == LottieTensor.CMD_ELLIPSE:
#name = string_params.get(f"{cmd_key}_name", "Ellipse Path 1")
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_SIZE:
# Check if size is animated - also check for PAD_VAL
if params[LottieTensor.Index.Transform.ANIMATED] > -2000 and params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "size"
else:
# 修改：使用 Transform.X 和 Transform.Y
x = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
y = LottieTensor._format_value(params[LottieTensor.Index.Transform.Y])
lines.append(f'({cmd} {x} {y})')
elif cmd_idx == LottieTensor.CMD_RECT:
#name = string_params.get(f"{cmd_key}_name", "Rectangle Path 1")
hd = "true" if params[LottieTensor.Index.Rect.HD] > 0.5 else "false"
d = int(params[LottieTensor.Index.Rect.D]) if params[LottieTensor.Index.Rect.D] > -2000 else 1
lines.append(f'({cmd} hd={hd} d={d})')
elif cmd_idx == LottieTensor.CMD_ROUNDED:
rounded = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
ix = int(params[LottieTensor.Index.SingleValue.IX]) if params[LottieTensor.Index.SingleValue.IX] > -2000 else 4
lines.append(f'({cmd} {rounded} ix={ix})')
elif cmd_idx == LottieTensor.CMD_TRIM:
#name = string_params.get(f"{cmd_key}_name", "Trim Paths 1")
ix = int(params[LottieTensor.Index.Trim.IX]) if params[LottieTensor.Index.Trim.IX] > -2000 else 1
lines.append(f'({cmd} ix={ix})')
elif cmd_idx == LottieTensor.CMD_END:
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "trim_end" # Set context for keyframes
else:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_START:
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "trim_start" # Set context for keyframes
else:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_OFFSET:
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "trim_offset" # Set context for keyframes
else:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_MULTIPLE:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 1
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_REPEATER:
#name = string_params.get(f"{cmd_key}_name", "Repeater 1")
ix = int(params[LottieTensor.Index.Repeater.IX]) if params[LottieTensor.Index.Repeater.IX] > -2000 else 1
lines.append(f'({cmd} ix={ix})')
elif cmd_idx == LottieTensor.CMD_COPIES:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
ix = int(params[LottieTensor.Index.SingleValue.IX]) if params[LottieTensor.Index.SingleValue.IX] > -2000 else 1
lines.append(f'({cmd} {val} ix={ix})')
elif cmd_idx == LottieTensor.CMD_REPEATER_OFFSET:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
ix = int(params[LottieTensor.Index.SingleValue.IX]) if params[LottieTensor.Index.SingleValue.IX] > -2000 else 2
lines.append(f'({cmd} {val} ix={ix})')
elif cmd_idx == LottieTensor.CMD_COMPOSITE:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 1
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_REPEATER_TRANSFORM:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_TR_P_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 2
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_A_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 1
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_SCALE:
val1 = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE1])
val2 = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE2])
lines.append(f'({cmd} {val1} {val2})')
elif cmd_idx == LottieTensor.CMD_TR_S_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 3
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_R_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 4
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_SO_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 5
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_EO_IX:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 6
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TRANSFORM_SHAPE:
#name = string_params.get(f"{cmd_key}_name", "Transform")
hd = "true" if params[LottieTensor.Index.TransformShape.HD] > 0.5 else "false"
position_x = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.POSITION_X])
position_y = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.POSITION_Y])
scale_x = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.SCALE_X])
scale_y = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.SCALE_Y])
rotation = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.ROTATION])
opacity = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.OPACITY])
anchor_x = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.ANCHOR_X])
anchor_y = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.ANCHOR_Y])
# Build the output line
line = f'({cmd} hd={hd} position="{position_x} {position_y}" scale="{scale_x} {scale_y}" rotation="{rotation}" opacity="{opacity}" anchor="{anchor_x} {anchor_y}"'
# Only add skew if it's not 0 or PAD_VAL
if params[LottieTensor.Index.TransformShape.SKEW] > -2000 and abs(params[LottieTensor.Index.TransformShape.SKEW]) > 1e-6:
skew = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.SKEW])
line += f' skew="{skew}"'
# Only add skew_axis if it's not 0 or PAD_VAL
if params[LottieTensor.Index.TransformShape.SKEW_AXIS] > -2000 and abs(params[LottieTensor.Index.TransformShape.SKEW_AXIS]) > 1e-6:
skew_axis = LottieTensor._format_value(params[LottieTensor.Index.TransformShape.SKEW_AXIS])
line += f' skew_axis="{skew_axis}"'
line += ')'
lines.append(line)
elif cmd_idx == LottieTensor.CMD_PARENT:
parent_index = int(params[LottieTensor.Index.Parent.PARENT_INDEX]) if params[LottieTensor.Index.Parent.PARENT_INDEX] > -2000 else 0
lines.append(f'({cmd} {parent_index})')
elif cmd_idx == LottieTensor.CMD_ASSET:
# Get tokenizer
tokenizer = LottieTensor.get_tokenizer()
# Decode ID from tokens
id_count = int(params[LottieTensor.Index.Asset.ID_TOKEN_COUNT]) if params[LottieTensor.Index.Asset.ID_TOKEN_COUNT] > -2000 else 0
id_tokens = []
for i in range(id_count):
if params[LottieTensor.Index.Asset.ID_TOKEN_0 + i] > -2000:
id_tokens.append(int(params[LottieTensor.Index.Asset.ID_TOKEN_0 + i]))
asset_id = tokenizer.decode(id_tokens, skip_special_tokens=True) if id_tokens else "comp_0"
fr = LottieTensor._format_value(params[LottieTensor.Index.Asset.FR])
lines.append(f'({cmd} id="{asset_id}" fr={fr})')
elif cmd_idx == LottieTensor.CMD_FONT:
# Get tokenizer
tokenizer = LottieTensor.get_tokenizer()
# Decode family from tokens
family_count = int(params[LottieTensor.Index.Font.FAMILY_TOKEN_COUNT]) if params[LottieTensor.Index.Font.FAMILY_TOKEN_COUNT] > -2000 else 0
family_tokens = []
for i in range(family_count):
if params[LottieTensor.Index.Font.FAMILY_TOKEN_0 + i] > -2000:
family_tokens.append(int(params[LottieTensor.Index.Font.FAMILY_TOKEN_0 + i]))
# Decode style from tokens
style_count = int(params[LottieTensor.Index.Font.STYLE_TOKEN_COUNT]) if params[LottieTensor.Index.Font.STYLE_TOKEN_COUNT] > -2000 else 0
style_tokens = []
for i in range(style_count):
if params[LottieTensor.Index.Font.STYLE_TOKEN_0 + i] > -2000:
style_tokens.append(int(params[LottieTensor.Index.Font.STYLE_TOKEN_0 + i]))
family = tokenizer.decode(family_tokens, skip_special_tokens=True) if family_tokens else ""
style = tokenizer.decode(style_tokens, skip_special_tokens=True) if style_tokens else ""
ascent = LottieTensor._format_value(params[LottieTensor.Index.Font.ASCENT])
lines.append(f'({cmd} family="{family}" style="{style}" ascent={ascent})')
elif cmd_idx == LottieTensor.CMD_CHAR:
# Get tokenizer
tokenizer = LottieTensor.get_tokenizer()
# Decode ch from tokens
ch_count = int(params[LottieTensor.Index.Char.CH_TOKEN_COUNT]) if params[LottieTensor.Index.Char.CH_TOKEN_COUNT] > -2000 else 0
ch_tokens = []
for i in range(ch_count):
if params[LottieTensor.Index.Char.CH_TOKEN_0 + i] > -2000:
ch_tokens.append(int(params[LottieTensor.Index.Char.CH_TOKEN_0 + i]))
# Decode style from tokens
style_count = int(params[LottieTensor.Index.Char.STYLE_TOKEN_COUNT]) if params[LottieTensor.Index.Char.STYLE_TOKEN_COUNT] > -2000 else 0
style_tokens = []
for i in range(style_count):
if params[LottieTensor.Index.Char.STYLE_TOKEN_0 + i] > -2000:
style_tokens.append(int(params[LottieTensor.Index.Char.STYLE_TOKEN_0 + i]))
# Decode family from tokens
family_count = int(params[LottieTensor.Index.Char.FAMILY_TOKEN_COUNT]) if params[LottieTensor.Index.Char.FAMILY_TOKEN_COUNT] > -2000 else 0
family_tokens = []
for i in range(family_count):
if params[LottieTensor.Index.Char.FAMILY_TOKEN_0 + i] > -2000:
family_tokens.append(int(params[LottieTensor.Index.Char.FAMILY_TOKEN_0 + i]))
ch = tokenizer.decode(ch_tokens, skip_special_tokens=True) if ch_tokens else ""
style = tokenizer.decode(style_tokens, skip_special_tokens=True) if style_tokens else ""
family = tokenizer.decode(family_tokens, skip_special_tokens=True) if family_tokens else ""
size = LottieTensor._format_value(params[LottieTensor.Index.Char.SIZE])
w = LottieTensor._format_value(params[LottieTensor.Index.Char.W])
lines.append(f'({cmd} ch="{ch}" size={size} style="{style}" w={w} family="{family}")')
elif cmd_idx == LottieTensor.CMD_TEXT_LAYER:
#name = string_params.get(f"{cmd_key}_name", "Text Layer")
index = LottieTensor._format_value(params[LottieTensor.Index.TextLayer.INDEX])
in_point = LottieTensor._format_value(params[LottieTensor.Index.TextLayer.IN_POINT])
out_point = LottieTensor._format_value(params[LottieTensor.Index.TextLayer.OUT_POINT])
start_time = LottieTensor._format_value(params[LottieTensor.Index.TextLayer.START_TIME])
hasMask = "True" if params[LottieTensor.Index.TextLayer.HAS_MASK] > 0.5 else "False" # 新增
lines.append(f'({cmd} index={index} in_point={in_point} out_point={out_point} start_time={start_time} hasMask={hasMask})') # 修改
#elif cmd_idx == LottieTensor.CMD_TEXT_KEYFRAME:
# t = LottieTensor._format_value(params[LottieTensor.Index.TextKeyframe.T])
# lines.append(f'({cmd} t={t})')
elif cmd_idx == LottieTensor.CMD_FONT_SIZE:
size = LottieTensor._format_value(params[LottieTensor.Index.FontSize.SIZE])
lines.append(f'({cmd} {size})')
elif cmd_idx == LottieTensor.CMD_FONT_FAMILY:
family = string_params.get(f"{cmd_key}_family", "")
lines.append(f'({cmd} "{family}")')
elif cmd_idx == LottieTensor.CMD_TEXT:
text = string_params.get(f"{cmd_key}_text", "")
lines.append(f'({cmd} "{text}")')
elif cmd_idx == LottieTensor.CMD_CA:
value = LottieTensor._format_value(params[LottieTensor.Index.Ca.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_JUSTIFY:
value = LottieTensor._format_value(params[LottieTensor.Index.Justify.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_TRACKING:
value = LottieTensor._format_value(params[LottieTensor.Index.Tracking.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_LINE_HEIGHT:
value = LottieTensor._format_value(params[LottieTensor.Index.LineHeight.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_LETTER_SPACING:
value = LottieTensor._format_value(params[LottieTensor.Index.LetterSpacing.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_FILL_COLOR:
r = LottieTensor._format_value(params[LottieTensor.Index.FillColor.R]/255)
g = LottieTensor._format_value(params[LottieTensor.Index.FillColor.G]/255)
b = LottieTensor._format_value(params[LottieTensor.Index.FillColor.B]/255)
lines.append(f'({cmd} {r} {g} {b})')
elif cmd_idx == LottieTensor.CMD_G:
value = LottieTensor._format_value(params[LottieTensor.Index.G.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_ALIGNMENT:
a = LottieTensor._format_value(params[LottieTensor.Index.Alignment.A])
lines.append(f'({cmd} a={a})')
elif cmd_idx == LottieTensor.CMD_ALIGNMENT_K:
val1 = LottieTensor._format_value(params[LottieTensor.Index.AlignmentK.VALUE1])
val2 = LottieTensor._format_value(params[LottieTensor.Index.AlignmentK.VALUE2])
lines.append(f'({cmd} {val1} {val2})')
elif cmd_idx == LottieTensor.CMD_ALIGNMENT_IX:
value = LottieTensor._format_value(params[LottieTensor.Index.AlignmentIx.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_EFFECTS:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_EFFECT:
#name = string_params.get(f"{cmd_key}_name", "")
match_name = string_params.get(f"{cmd_key}_match_name", "")
type_val = int(params[LottieTensor.Index.Effect.TYPE]) if params[LottieTensor.Index.Effect.TYPE] > -2000 else 0
index = int(params[LottieTensor.Index.Effect.INDEX]) if params[LottieTensor.Index.Effect.INDEX] > -2000 else 1
np = int(params[LottieTensor.Index.Effect.NP]) if params[LottieTensor.Index.Effect.NP] > -2000 else 0
enabled = int(params[LottieTensor.Index.Effect.ENABLED]) if params[LottieTensor.Index.Effect.ENABLED] > -2000 else 1
line = f'({cmd} type={type_val} index={index}'
if np > 0: # Only output np if it's non-zero
line += f' np={np}'
line += f' match_name="{match_name}"'
if enabled != 1: # Only output enabled if it's not the default value
line += f' enabled={enabled}'
line += ')'
lines.append(line)
# Add CMD_LAYER_EFFECT output:
elif cmd_idx == LottieTensor.CMD_LAYER_EFFECT:
#name = string_params.get(f"{cmd_key}_name", "")
match_name = string_params.get(f"{cmd_key}_match_name", "")
index = int(params[LottieTensor.Index.LayerEffect.INDEX]) if params[LottieTensor.Index.LayerEffect.INDEX] > -2000 else 1
value = LottieTensor._format_value(params[LottieTensor.Index.LayerEffect.VALUE])
lines.append(f'({cmd} index={index} value={value} match_name="{match_name}")')
elif cmd_idx == LottieTensor.CMD_DROPDOWN:
#name = string_params.get(f"{cmd_key}_name", "")
index = int(params[LottieTensor.Index.Dropdown.INDEX]) if params[LottieTensor.Index.Dropdown.INDEX] > -2000 else 1
value = int(params[LottieTensor.Index.Dropdown.VALUE]) if params[LottieTensor.Index.Dropdown.VALUE] > -2000 else 0
lines.append(f'({cmd} index={index} value={value})')
elif cmd_idx == LottieTensor.CMD_NO_VALUE:
#@name = string_params.get(f"{cmd_key}_name", "")
index = int(params[LottieTensor.Index.NO_VALUE.INDEX]) if params[LottieTensor.Index.NO_VALUE.INDEX] > -2000 else 1
value = int(params[LottieTensor.Index.NO_VALUE.VALUE]) if params[LottieTensor.Index.NO_VALUE.VALUE] > -2000 else 0
lines.append(f'({cmd} index={index} value={value})')
elif cmd_idx == LottieTensor.CMD_IGNORED:
#name = string_params.get(f"{cmd_key}_name", "")
index = int(params[LottieTensor.Index.Ignored.INDEX]) if params[LottieTensor.Index.Ignored.INDEX] > -2000 else 1
value = LottieTensor._format_value(params[LottieTensor.Index.Ignored.VALUE])
lines.append(f'({cmd} index={index} value={value})')
elif cmd_idx == LottieTensor.CMD_SLIDER:
#name = string_params.get(f"{cmd_key}_name", "")
index = int(params[LottieTensor.Index.Slider.INDEX]) if params[LottieTensor.Index.Slider.INDEX] > -2000 else 1
value = LottieTensor._format_value(params[LottieTensor.Index.Slider.VALUE])
lines.append(f'({cmd} index={index} value={value})')
elif cmd_idx == LottieTensor.CMD_GRADIENT_FILL:
#name = string_params.get(f"{cmd_key}_name", "Gradient Fill 1")
lines.append(f'({cmd})')
current_context = "gradient_fill" # Set context for subsequent commands
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "gradient_fill":
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_FILL_RULE:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 1
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_START_POINT:
x = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE1])
y = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE2])
lines.append(f'({cmd} {x} {y})')
elif cmd_idx == LottieTensor.CMD_END_POINT:
x = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE1])
y = LottieTensor._format_value(params[LottieTensor.Index.TwoValues.VALUE2])
lines.append(f'({cmd} {x} {y})')
elif cmd_idx == LottieTensor.CMD_GRADIENT_TYPE:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 1
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_HIGHLIGHT_LENGTH:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_HIGHLIGHT_ANGLE:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_ORIGINAL_COLORS:
count = int(params[LottieTensor.Index.OriginalColors.COUNT]) if params[LottieTensor.Index.OriginalColors.COUNT] > -2000 else 0
color_values = []
for i in range(count):
if params[LottieTensor.Index.OriginalColors.COLOR_0 + i] > -2000:
color_values.append(LottieTensor._format_value(params[LottieTensor.Index.OriginalColors.COLOR_0 + i])/255)
colors_str = ", ".join(str(v) for v in color_values)
lines.append(f'({cmd} [{colors_str}])')
elif cmd_idx == LottieTensor.CMD_COLOR_POINTS:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 2
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_GRADIENT_FILL_END:
lines.append(f'({cmd})')
current_context = None # Reset context
elif cmd_idx == LottieTensor.CMD_GRADIENT_STROKE:
#name = string_params.get(f"{cmd_key}_name", "Gradient Stroke 1")
lines.append(f'({cmd})')
current_context = "gradient_stroke" # Set context for subsequent commands
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "gradient_stroke":
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
current_context = "gradient_stroke" # Set context for subsequent commands
elif cmd_idx == LottieTensor.CMD_WIDTH:
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
# 除以100恢复原值
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE] / 10, preserve_int=False)
lines.append(f'({cmd} {val})')
#if current_context == "gradient_stroke":
# Check if value exists (not PAD_VAL)
# if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
# val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
# lines.append(f'({cmd} {val})')
# else:
# No value, output just the command
# lines.append(f'({cmd})')
#else:
# Handle width in other contexts if needed
# lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_LINE_CAP:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 2
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_LINE_JOIN:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 2
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_MITER_LIMIT:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 0
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_GRADIENT_STROKE_END:
lines.append(f'({cmd})')
current_context = None # Reset context
elif cmd_idx == LottieTensor.CMD_COLOR:
#name = string_params.get(f"{cmd_key}_name", "Color")
index = int(params[LottieTensor.Index.Color.INDEX]) if params[LottieTensor.Index.Color.INDEX] > -2000 else 1
r = LottieTensor._format_value(params[LottieTensor.Index.Color.R]/255)
g = LottieTensor._format_value(params[LottieTensor.Index.Color.G]/255)
b = LottieTensor._format_value(params[LottieTensor.Index.Color.B]/255)
lines.append(f'({cmd} index={index} r={r} g={g} b={b})')
elif cmd_idx == LottieTensor.CMD_MERGE:
#name = string_params.get(f"{cmd_key}_name", "Merge Paths 1")
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MERGE_MODE:
mode = int(params[LottieTensor.Index.MergeMode.MODE]) if params[LottieTensor.Index.MergeMode.MODE] > -2000 else 1
lines.append(f'({cmd} {mode})')
elif cmd_idx == LottieTensor.CMD_SOLID_LAYER:
#name = string_params.get(f"{cmd_key}_name", "Solid Layer")
#color = string_params.get(f"{cmd_key}_color", "#000000")
r = int(min(255, max(0, params[LottieTensor.Index.SolidLayer.COLOR_R])))
g = int(min(255, max(0, params[LottieTensor.Index.SolidLayer.COLOR_G])))
b = int(min(255, max(0, params[LottieTensor.Index.SolidLayer.COLOR_B])))
a = int(min(255, max(0, params[LottieTensor.Index.SolidLayer.COLOR_A])))
# You can use RGB values directly or convert back to hex if needed
color_rgb = (r, g, b, a)
# Or convert back to hex format if required:
color = f"#{r:02x}{g:02x}{b:02x}{a:02x}"
index = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.INDEX])
in_point = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.IN_POINT])
out_point = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.OUT_POINT])
start_time = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.START_TIME])
width = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.WIDTH])
height = LottieTensor._format_value(params[LottieTensor.Index.SolidLayer.HEIGHT])
hasMask = "True" if params[LottieTensor.Index.SolidLayer.HAS_MASK] > 0.5 else "False"
lines.append(f'({cmd} index={index} in_point={in_point} out_point={out_point} start_time={start_time} color="{color}" width={width} height={height} hasMask={hasMask})')
elif cmd_idx == LottieTensor.CMD_MASKS_PROPERTIES:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASK:
#nm = string_params.get(f"{cmd_key}_nm", "Mask 1")
index = int(params[LottieTensor.Index.Mask.INDEX]) if params[LottieTensor.Index.Mask.INDEX] > -2000 else 0
inv = "true" if params[LottieTensor.Index.Mask.INV] > 0.5 else "false"
# Convert mode value back to string
mode_val = int(params[LottieTensor.Index.Mask.MODE]) if params[LottieTensor.Index.Mask.MODE] > -2000 else 0
mode_map = {0: "a", 1: "s", 2: "i", 3: "n"}
mode = mode_map.get(mode_val, "a")
lines.append(f'({cmd} index={index} inv={inv} mode={mode})')
elif cmd_idx == LottieTensor.CMD_MASK_PT:
a = int(params[LottieTensor.Index.MaskPt.A]) if params[LottieTensor.Index.MaskPt.A] > -2000 else 1
ix = int(params[LottieTensor.Index.MaskPt.IX]) if params[LottieTensor.Index.MaskPt.IX] > -2000 else 1
lines.append(f'({cmd} a={a} ix={ix})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_K_C:
c = "true" if params[LottieTensor.Index.MaskPtK.C] > 0.5 else "false"
lines.append(f'({cmd} {c})') # Changed from c={c} to just {c}
elif cmd_idx in [LottieTensor.CMD_MASK_PT_K_I, LottieTensor.CMD_MASK_PT_K_O, LottieTensor.CMD_MASK_PT_K_V]:
count = int(params[LottieTensor.Index.MaskPtKValues.COUNT]) if params[LottieTensor.Index.MaskPtKValues.COUNT] > -2000 else 0
if count == 0:
# Fallback: find last non-padding value
for i in range(19, -1, -1):
val = params[LottieTensor.Index.MaskPtKValues.V1 + i]
if val > -2000:
count = i + 1
break
values = []
for i in range(count):
val = params[LottieTensor.Index.MaskPtKValues.V1 + i]
if val > -2000:
values.append(LottieTensor._format_value(val))
else:
values.append(0.0)
lines.append(f'({cmd} {" ".join(str(v) for v in values)})')
elif cmd_idx == LottieTensor.CMD_MASK_O:
a = int(params[LottieTensor.Index.MaskO.A]) if params[LottieTensor.Index.MaskO.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.MaskO.K]) if params[LottieTensor.Index.MaskO.K] > -2000 else 100
ix = int(params[LottieTensor.Index.MaskO.IX]) if params[LottieTensor.Index.MaskO.IX] > -2000 else 3
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_MASK_X:
a = int(params[LottieTensor.Index.MaskX.A]) if params[LottieTensor.Index.MaskX.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.MaskX.K]) if params[LottieTensor.Index.MaskX.K] > -2000 else 0
ix = int(params[LottieTensor.Index.MaskX.IX]) if params[LottieTensor.Index.MaskX.IX] > -2000 else 4
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_MASK_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_K:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_K_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASKS_PROPERTIES_END:
lines.append(f'({cmd})')
elif cmd_idx in [LottieTensor.CMD_MASK_PT_K_ARRAY, LottieTensor.CMD_MASK_PT_K_ARRAY_END,
LottieTensor.CMD_MASK_PT_KF_S, LottieTensor.CMD_MASK_PT_KF_S_END,
LottieTensor.CMD_MASK_PT_KF_SHAPE_END, LottieTensor.CMD_MASK_PT_KEYFRAME_END]:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_KEYFRAME:
index = int(params[LottieTensor.Index.MaskPtKeyframe.INDEX]) if params[LottieTensor.Index.MaskPtKeyframe.INDEX] > -2000 else 0
t = LottieTensor._format_value(params[LottieTensor.Index.MaskPtKeyframe.T])
lines.append(f'({cmd} index={index} t={t})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_I:
x = LottieTensor._format_value(params[LottieTensor.Index.MaskPtKfI.X])
y = LottieTensor._format_value(params[LottieTensor.Index.MaskPtKfI.Y])
lines.append(f'({cmd} x={x} y={y})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_O:
x = LottieTensor._format_value(params[LottieTensor.Index.MaskPtKfO.X])
y = LottieTensor._format_value(params[LottieTensor.Index.MaskPtKfO.Y])
lines.append(f'({cmd} x={x} y={y})')
elif cmd_idx == LottieTensor.CMD_MASK_PT_KF_SHAPE:
index = int(params[LottieTensor.Index.MaskPtKfShape.INDEX]) if params[LottieTensor.Index.MaskPtKfShape.INDEX] > -2000 else 0
c = "true" if params[LottieTensor.Index.MaskPtKfShape.C] > 0.5 else "false"
lines.append(f'({cmd} index={index} c={c})')
elif cmd_idx in [LottieTensor.CMD_MASK_PT_KF_SHAPE_I, LottieTensor.CMD_MASK_PT_KF_SHAPE_O,
LottieTensor.CMD_MASK_PT_KF_SHAPE_V]:
# Get the count from params, not from string_params
count = int(params[LottieTensor.Index.MaskPtKfShapeValues.COUNT]) if params[LottieTensor.Index.MaskPtKfShapeValues.COUNT] > -2000 else 0
if count == 0:
# If no count stored, find the last non-padding value
for i in range(19, -1, -1): # Check V1 through V20
if i < LottieTensor.PARAM_DIM:
val = params[LottieTensor.Index.MaskPtKfShapeValues.V1 + i]
if val > -2000:
count = i + 1
break
if count == 0:
count = 8 # Default to 8 if no valid values found
# Output the exact number of values
values = []
for i in range(count):
if i < 20:
val = params[LottieTensor.Index.MaskPtKfShapeValues.V1 + i]
if val > -2000:
values.append(LottieTensor._format_value(val))
else:
values.append(0.0)
else:
values.append(0.0)
lines.append(f'({cmd} {" ".join(str(v) for v in values)})')
elif cmd_idx == LottieTensor.CMD_TR_POSITION:
x = LottieTensor._format_value(params[LottieTensor.Index.TrPosition.X])
y = LottieTensor._format_value(params[LottieTensor.Index.TrPosition.Y])
lines.append(f'({cmd} {x} {y})')
elif cmd_idx == LottieTensor.CMD_TR_ANCHOR:
x = LottieTensor._format_value(params[LottieTensor.Index.TrAnchor.X])
y = LottieTensor._format_value(params[LottieTensor.Index.TrAnchor.Y])
lines.append(f'({cmd} {x} {y})')
elif cmd_idx == LottieTensor.CMD_TR_ROTATION:
val = LottieTensor._format_value(params[LottieTensor.Index.TrRotation.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_START_OPACITY:
val = LottieTensor._format_value(params[LottieTensor.Index.TrStartOpacity.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_TR_END_OPACITY:
if params[LottieTensor.Index.TrEndOpacity.VALUE] > -2000:
val = LottieTensor._format_value(params[LottieTensor.Index.TrEndOpacity.VALUE])
lines.append(f'({cmd} {val})')
else:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_ZIG_ZAG:
#name = string_params.get(f"{cmd_key}_name", "Zig Zag 1")
ix = int(params[LottieTensor.Index.ZigZag.IX]) if params[LottieTensor.Index.ZigZag.IX] > -2000 else 2
lines.append(f'({cmd} ix={ix})')
elif cmd_idx == LottieTensor.CMD_FREQUENCY:
value = LottieTensor._format_value(params[LottieTensor.Index.Frequency.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_AMPLITUDE:
value = LottieTensor._format_value(params[LottieTensor.Index.Amplitude.VALUE])
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_POINT_TYPE:
value = int(params[LottieTensor.Index.PointType.VALUE]) if params[LottieTensor.Index.PointType.VALUE] > -2000 else 2
lines.append(f'({cmd} {value})')
elif cmd_idx == LottieTensor.CMD_ZIG_ZAG_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_ANIMATORS:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_ANIMATOR:
#nm = string_params.get(f"{cmd_key}_nm", "Animator 1")
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_RANGE_SELECTOR:
t = int(params[LottieTensor.Index.RangeSelector.T]) if params[LottieTensor.Index.RangeSelector.T] > -2000 else 0
r = int(params[LottieTensor.Index.RangeSelector.R]) if params[LottieTensor.Index.RangeSelector.R] > -2000 else 1
b = int(params[LottieTensor.Index.RangeSelector.B]) if params[LottieTensor.Index.RangeSelector.B] > -2000 else 1
sh = int(params[LottieTensor.Index.RangeSelector.SH]) if params[LottieTensor.Index.RangeSelector.SH] > -2000 else 1
rn = int(params[LottieTensor.Index.RangeSelector.RN]) if params[LottieTensor.Index.RangeSelector.RN] > -2000 else 0
lines.append(f'({cmd} t={t} r={r} b={b} sh={sh} rn={rn})')
elif cmd_idx == LottieTensor.CMD_RANGE_START:
a = int(params[LottieTensor.Index.RangeStart.A]) if params[LottieTensor.Index.RangeStart.A] > -2000 else 0
lines.append(f'({cmd} a={a})')
if a > 0.5:
current_context = "range_start"
elif cmd_idx == LottieTensor.CMD_RANGE_START_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.RangeStartKeyframe.T])
s = LottieTensor._format_value(params[LottieTensor.Index.RangeStartKeyframe.S])
# Check if this is the last keyframe (no easing values or all zeros)
i_x = params[LottieTensor.Index.RangeStartKeyframe.I_X]/100
i_y = params[LottieTensor.Index.RangeStartKeyframe.I_Y]/100
o_x = params[LottieTensor.Index.RangeStartKeyframe.O_X]/100
o_y = params[LottieTensor.Index.RangeStartKeyframe.O_Y]/100
has_meaningful_easing = (
(i_x > -2000 and abs(i_x) > 1e-6) or
(i_y > -2000 and abs(i_y) > 1e-6) or
(o_x > -2000 and abs(o_x) > 1e-6) or
(o_y > -2000 and abs(o_y) > 1e-6)
)
if has_meaningful_easing:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
lines.append(f'({cmd} t={t} s={s} i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val})')
else:
lines.append(f'({cmd} t={t} s={s})')
elif cmd_idx == LottieTensor.CMD_RANGE_START_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_AMOUNT:
a = int(params[LottieTensor.Index.Amount.A]) if params[LottieTensor.Index.Amount.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.Amount.K]) if params[LottieTensor.Index.Amount.K] > -2000 else 100
ix = int(params[LottieTensor.Index.Amount.IX]) if params[LottieTensor.Index.Amount.IX] > -2000 else 4
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_MAX_EASE:
a = int(params[LottieTensor.Index.MaxEase.A]) if params[LottieTensor.Index.MaxEase.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.MaxEase.K]) if params[LottieTensor.Index.MaxEase.K] > -2000 else 0
ix = int(params[LottieTensor.Index.MaxEase.IX]) if params[LottieTensor.Index.MaxEase.IX] > -2000 else 7
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_MIN_EASE:
a = int(params[LottieTensor.Index.MinEase.A]) if params[LottieTensor.Index.MinEase.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.MinEase.K]) if params[LottieTensor.Index.MinEase.K] > -2000 else 0
ix = int(params[LottieTensor.Index.MinEase.IX]) if params[LottieTensor.Index.MinEase.IX] > -2000 else 8
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_ANIMATOR_PROPERTIES:
lines.append(f'({cmd})')
current_context = "animator_properties"
elif cmd_idx == LottieTensor.CMD_ANIMATOR_PROPERTIES_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_OPACITY and current_context == "animator_properties":
# Special handling for opacity within animator_properties
a = int(params[LottieTensor.Index.Amount.A]) if params[LottieTensor.Index.Amount.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.Amount.K]) if params[LottieTensor.Index.Amount.K] > -2000 else 0
ix = int(params[LottieTensor.Index.Amount.IX]) if params[LottieTensor.Index.Amount.IX] > -2000 else 9
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_RANGE_SELECTOR_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_ANIMATOR_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_ANIMATORS_END:
lines.append(f'({cmd})')
elif cmd_idx == LottieTensor.CMD_RADIUS:
val = LottieTensor._format_value(params[LottieTensor.Index.Radius.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_RANGE_END:
a = int(params[LottieTensor.Index.RangeEnd.A]) if params[LottieTensor.Index.RangeEnd.A] > -2000 else 0
lines.append(f'({cmd} a={a})')
if a > 0.5:
current_context = "range_end"
elif cmd_idx == LottieTensor.CMD_RANGE_END_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.RangeEndKeyframe.T])
s = LottieTensor._format_value(params[LottieTensor.Index.RangeEndKeyframe.S])
# Check if this is the last keyframe (no easing values or all zeros)
i_x = params[LottieTensor.Index.RangeEndKeyframe.I_X]/100
i_y = params[LottieTensor.Index.RangeEndKeyframe.I_Y]/100
o_x = params[LottieTensor.Index.RangeEndKeyframe.O_X]/100
o_y = params[LottieTensor.Index.RangeEndKeyframe.O_Y]/100
has_meaningful_easing = (
(i_x > -2000 and abs(i_x) > 1e-6) or
(i_y > -2000 and abs(i_y) > 1e-6) or
(o_x > -2000 and abs(o_x) > 1e-6) or
(o_y > -2000 and abs(o_y) > 1e-6)
)
if has_meaningful_easing:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
lines.append(f'({cmd} t={t} s={s} i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val})')
else:
lines.append(f'({cmd} t={t} s={s})')
elif cmd_idx == LottieTensor.CMD_RANGE_END_END:
lines.append(f'({cmd})')
current_context = None
# Fix position output in animator_properties context
elif cmd_idx == LottieTensor.CMD_POSITION and current_context == "animator_properties":
# Special handling for position within animator_properties
a = int(params[LottieTensor.Index.Amount.A]) if params[LottieTensor.Index.Amount.A] > -2000 else 0
ix = int(params[LottieTensor.Index.Amount.IX]) if params[LottieTensor.Index.Amount.IX] > -2000 else 2
# Check if we have array values stored
x = params[LottieTensor.Index.Transform.X]
y = params[LottieTensor.Index.Transform.Y]
z = params[LottieTensor.Index.Transform.Z]
if x > -2000 or y > -2000: # Changed condition - check x or y
# Format as array
x_val = LottieTensor._format_value(x) if x > -2000 else 0
y_val = LottieTensor._format_value(y) if y > -2000 else 0
# Only include z if it's meaningful
if z > -2000 and abs(z) > 1e-6:
lines.append(f'({cmd} a={a} k=[{x_val}, {y_val}, {LottieTensor._format_value(z)}] ix={ix})')
else:
lines.append(f'({cmd} a={a} k=[{x_val}, {y_val}, 0] ix={ix})')
else:
# Format as single value
k = LottieTensor._format_value(params[LottieTensor.Index.Amount.K]) if params[LottieTensor.Index.Amount.K] > -2000 else 0
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_ML2:
val = int(params[LottieTensor.Index.SingleValue.VALUE]) if params[LottieTensor.Index.SingleValue.VALUE] > -2000 else 4
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_RANGE_OFFSET_KEYFRAME:
t = LottieTensor._format_value(params[LottieTensor.Index.RangeOffsetKeyframe.T])
s = LottieTensor._format_value(params[LottieTensor.Index.RangeOffsetKeyframe.S])
# Check if this is the last keyframe (no easing values or all zeros)
i_x = params[LottieTensor.Index.RangeOffsetKeyframe.I_X]/100
i_y = params[LottieTensor.Index.RangeOffsetKeyframe.I_Y]/100
o_x = params[LottieTensor.Index.RangeOffsetKeyframe.O_X]/100
o_y = params[LottieTensor.Index.RangeOffsetKeyframe.O_Y]/100
has_meaningful_easing = (
(i_x > -2000 and abs(i_x) > 1e-6) or
(i_y > -2000 and abs(i_y) > 1e-6) or
(o_x > -2000 and abs(o_x) > 1e-6) or
(o_y > -2000 and abs(o_y) > 1e-6)
)
if has_meaningful_easing:
i_x_val = LottieTensor._format_value(i_x, preserve_int=False) if i_x > -2000 else 0
i_y_val = LottieTensor._format_value(i_y, preserve_int=False) if i_y > -2000 else 0
o_x_val = LottieTensor._format_value(o_x, preserve_int=False) if o_x > -2000 else 0
o_y_val = LottieTensor._format_value(o_y, preserve_int=False) if o_y > -2000 else 0
lines.append(f'({cmd} t={t} s={s} i_x={i_x_val} i_y={i_y_val} o_x={o_x_val} o_y={o_y_val})')
else:
lines.append(f'({cmd} t={t} s={s})')
elif cmd_idx == LottieTensor.CMD_RANGE_OFFSET_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_S_M:
a = int(params[LottieTensor.Index.SM.A]) if params[LottieTensor.Index.SM.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.SM.K]) if params[LottieTensor.Index.SM.K] > -2000 else 100
ix = int(params[LottieTensor.Index.SM.IX]) if params[LottieTensor.Index.SM.IX] > -2000 else 6
lines.append(f'({cmd} a={a} k={k} ix={ix})')
# 修改 CMD_OPACITY_ANIMATORS 的输出：
elif cmd_idx == LottieTensor.CMD_OPACITY_ANIMATORS:
a = int(params[LottieTensor.Index.OpacityAnimators.A]) if params[LottieTensor.Index.OpacityAnimators.A] > -2000 else 0
if a > 0.5:
# Animated case - only output a
lines.append(f'({cmd} a={a})')
current_context = "opacity_animators"
else:
# Static case with k value
k = LottieTensor._format_value(params[LottieTensor.Index.OpacityAnimators.K]) if params[LottieTensor.Index.OpacityAnimators.K] > -2000 else 0
ix = int(params[LottieTensor.Index.OpacityAnimators.IX]) if params[LottieTensor.Index.OpacityAnimators.IX] > -2000 else 9
lines.append(f'({cmd} a={a} k={k} ix={ix})')
# 添加 CMD_POSITION_ANIMATORS 的输出：
elif cmd_idx == LottieTensor.CMD_POSITION_ANIMATORS:
a = int(params[LottieTensor.Index.PositionAnimators.A]) if params[LottieTensor.Index.PositionAnimators.A] > -2000 else 0
ix = int(params[LottieTensor.Index.PositionAnimators.IX]) if params[LottieTensor.Index.PositionAnimators.IX] > -2000 else 2
if a > 0.5:
# Animated case
lines.append(f'({cmd} a={a})')
current_context = "position_animators"
else:
# Static case with k value
k_x = params[LottieTensor.Index.PositionAnimators.K_X]
k_y = params[LottieTensor.Index.PositionAnimators.K_Y]
k_z = params[LottieTensor.Index.PositionAnimators.K_Z]
if k_x > -2000 and k_y > -2000:
# Format as array
x_val = LottieTensor._format_value(k_x) if k_x > -2000 else 0
y_val = LottieTensor._format_value(k_y) if k_y > -2000 else 0
z_val = LottieTensor._format_value(k_z) if k_z > -2000 else 0
lines.append(f'({cmd} a={a} k=[{x_val}, {y_val}, {z_val}] ix={ix})')
else:
lines.append(f'({cmd} a={a} k=[0.0, 0.0, 0.0] ix={ix})')
# 添加 CMD_TRACKING_ANIMATORS 的输出：
elif cmd_idx == LottieTensor.CMD_TRACKING_ANIMATORS:
a = int(params[LottieTensor.Index.TrackingAnimators.A]) if params[LottieTensor.Index.TrackingAnimators.A] > -2000 else 0
k = LottieTensor._format_value(params[LottieTensor.Index.TrackingAnimators.K]) if params[LottieTensor.Index.TrackingAnimators.K] > -2000 else 0
ix = int(params[LottieTensor.Index.TrackingAnimators.IX]) if params[LottieTensor.Index.TrackingAnimators.IX] > -2000 else 89
if a > 0.5:
# Animated case
lines.append(f'({cmd} a={a})')
current_context = "tracking_animators"
else:
# Static case
lines.append(f'({cmd} a={a} k={k} ix={ix})')
# 添加结束命令的输出：
elif cmd_idx == LottieTensor.CMD_POSITION_ANIMATORS_END:
lines.append(f'({cmd})')
current_context = None
# Add output formatting (after CMD_OPACITY_ANIMATORS, around line 5590)
elif cmd_idx == LottieTensor.CMD_SCALE_ANIMATORS:
a = int(params[LottieTensor.Index.ScaleAnimators.A]) if params[LottieTensor.Index.ScaleAnimators.A] > -2000 else 0
if a > 0.5:
# Animated case
lines.append(f'({cmd} a={a})')
current_context = "scale_animators"
else:
# Static case with k value
k_x = params[LottieTensor.Index.ScaleAnimators.K_X]
k_y = params[LottieTensor.Index.ScaleAnimators.K_Y]
k_z = params[LottieTensor.Index.ScaleAnimators.K_Z]
if k_x > -2000 and k_y > -2000 and k_z > -2000:
# Check if all values are the same
if abs(k_x - k_y) < 1e-6 and abs(k_y - k_z) < 1e-6:
# Output single value
lines.append(f'({cmd} a={a} k={LottieTensor._format_value(k_x)})')
else:
# Output array
lines.append(f'({cmd} a={a} k=[{LottieTensor._format_value(k_x)}, {LottieTensor._format_value(k_y)}, {LottieTensor._format_value(k_z)}])')
else:
lines.append(f'({cmd} a={a} k=100)')
elif cmd_idx == LottieTensor.CMD_SCALE_ANIMATORS_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_ROTATION_ANIMATORS:
a = int(params[LottieTensor.Index.RotationAnimators.A]) if params[LottieTensor.Index.RotationAnimators.A] > -2000 else 0
if a > 0.5:
# Animated case
lines.append(f'({cmd} a={a})')
current_context = "rotation_animators"
else:
# Static case with k value
k = LottieTensor._format_value(params[LottieTensor.Index.RotationAnimators.K]) if params[LottieTensor.Index.RotationAnimators.K] > -2000 else 0
lines.append(f'({cmd} a={a} k={k})')
elif cmd_idx == LottieTensor.CMD_WIDTH_ANIMATED:
# This is a standalone width_animated command
# The context should already be set from the stroke command
# No parameters needed for this command
pass
elif cmd_idx == LottieTensor.CMD_RANGE_OFFSET:
# Use Amount indices for range_offset
a = int(params[LottieTensor.Index.Amount.A]) if params[LottieTensor.Index.Amount.A] > -2000 else 0
if a > 0.5: # This should be checking a, not params[LottieTensor.Index.Amount.A] again
# Animated case - only output a
lines.append(f'({cmd} a={a})')
current_context = "range_offset"
else:
# Static case - output a, k, and ix
k = LottieTensor._format_value(params[LottieTensor.Index.Amount.K]) if params[LottieTensor.Index.Amount.K] > -2000 else 0
ix = int(params[LottieTensor.Index.Amount.IX]) if params[LottieTensor.Index.Amount.IX] > -2000 else 3
lines.append(f'({cmd} a={a} k={k} ix={ix})')
elif cmd_idx == LottieTensor.CMD_ROTATION_ANIMATORS_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_RECT_SIZE:
# Output rect_size with two values
if params[LottieTensor.Index.Transform.ANIMATED] > -2000 and params[LottieTensor.Index.Transform.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "size"
else:
# 修改：使用 Transform.X 和 Transform.Y
val1 = LottieTensor._format_value(params[LottieTensor.Index.Transform.X])
val2 = LottieTensor._format_value(params[LottieTensor.Index.Transform.Y])
lines.append(f'({cmd} {val1} {val2})')
elif cmd_idx == LottieTensor.CMD_ELLIPSE_SIZE:
# Output rect_size with two values
# 检查是否是动画
animated_val = params[LottieTensor.Index.Transform.ANIMATED]
if animated_val > -2000 and animated_val > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "size" # 确保设置上下文
else:
# 静态值 - 检查 X 和 Y 是否为有效值
x_val = params[LottieTensor.Index.Transform.X]
y_val = params[LottieTensor.Index.Transform.Y]
# 如果 X 和 Y 都是默认值 0 且 ANIMATED 未设置，可能是数据丢失
val1 = LottieTensor._format_value(x_val if x_val > -2000 else 0)
val2 = LottieTensor._format_value(y_val if y_val > -2000 else 0)
lines.append(f'({cmd} {val1} {val2})')
elif cmd_idx == LottieTensor.CMD_RECT_ROUNDED:
if params[LottieTensor.Index.SingleValue.ANIMATED] > 0.5:
lines.append(f'({cmd} animated=true)')
current_context = "rect_rounded" # Set context for keyframes
else:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_RECT_ROUNDED_END:
lines.append(f'({cmd})')
current_context = None
elif cmd_idx == LottieTensor.CMD_SKEW:
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
elif cmd_idx == LottieTensor.CMD_SKEW_AXIS:
if params[LottieTensor.Index.SingleValue.VALUE] > -2000:
val = LottieTensor._format_value(params[LottieTensor.Index.SingleValue.VALUE])
lines.append(f'({cmd} {val})')
else:
# Default case for any unhandled commands
lines.append(f"({cmd})")
return '\n'.join(lines)
# Keep other methods unchanged
def to_tensor(self) -> torch.Tensor:
"""Convert LottieTensor to a single tensor"""
return torch.cat([self.commands.float(), self.params], dim=1)
@staticmethod
def from_tensor(tensor: torch.Tensor) -> 'LottieTensor':
"""Create LottieTensor from tensor"""
commands = tensor[:, 0:1].long()
params = tensor[:, 1:1+LottieTensor.PARAM_DIM].float()
return LottieTensor(commands, params, PAD_VAL=-2001)
def add_sos(self):
"""Add start-of-sequence token"""
self.commands = torch.cat([self.sos_token, self.commands])
pad_params = torch.ones((1, self.PARAM_DIM)) * self.PAD_VAL
self.params = torch.cat([pad_params, self.params])
self.seq_len += 1
return self
def add_eos(self):
"""Add end-of-sequence token"""
self.commands = torch.cat([self.commands, self.eos_token])
pad_params = torch.ones((1, self.PARAM_DIM)) * self.PAD_VAL
self.params = torch.cat([self.params, pad_params])
self.seq_len += 1
return self
def pad(self, seq_len: int):
"""Pad sequence to specified length"""
pad_len = max(seq_len - len(self.commands), 0)
if pad_len > 0:
pad_commands = torch.ones((pad_len, 1)) * LottieTensor.CMD_PAD
pad_params = torch.ones((pad_len, self.PARAM_DIM)) * self.PAD_VAL
self.commands = torch.cat([self.commands, pad_commands.long()])
self.params = torch.cat([self.params, pad_params])
return self
@staticmethod
def _clamp_value(value: float, min_val: float = -2000, max_val: float = 2000) -> float:
"""Clamp a value between min and max bounds"""
return max(min_val, min(max_val, value))
@staticmethod
def _index_clamp_value(value: float, min_val: float = -100, max_val: float = 100) -> float:
"""Clamp a value between min and max bounds"""
return max(min_val, min(max_val, value))
@classmethod
def init_tokenizer(cls, model_path=None):
"""Initialize tokenizer once for the class - 支持多路径fallback"""
if cls.tokenizer is None:
from transformers import AutoTokenizer
if model_path is None:
# 尝试多个可能的路径
possible_paths = [
'/mnt/jfs-test/Qwen2.5-VL-3B-Instruct',
'/data/models/Qwen2.5-VL-3B-Instruct',
'Qwen/Qwen2.5-VL-3B-Instruct', # HuggingFace Hub
]
for path in possible_paths:
try:
cls.tokenizer = AutoTokenizer.from_pretrained(path)
# 只在主进程打印一次
import os
if os.environ.get('RANK', '0') == '0':
print(f"Tokenizer loaded successfully from: {path}")
return
except Exception as e:
continue
raise ValueError(f"Failed to load tokenizer from any known path: {possible_paths}")
else:
cls.tokenizer = AutoTokenizer.from_pretrained(model_path)
@classmethod
def get_tokenizer(cls):
if cls.tokenizer is None:
from transformers import AutoTokenizer
cls.tokenizer = AutoTokenizer.from_pretrained('/mnt/jfs-test/Qwen2.5-VL-3B-Instruct')
return cls.tokenizer
@staticmethod
def get_param_offset(cmd_idx: int, param_idx: int) -> int:
"""
Get the offset for a parameter based on its command and parameter index.
Returns the offset to add to the parameter value.
"""
# 1. 查缓存
cache_key = (cmd_idx, param_idx)
if cache_key in LottieTensor._OFFSET_CACHE:
return LottieTensor._OFFSET_CACHE[cache_key]
# 更新后的offset范围，确保没有overlap
TIME_OFFSET = 155000 # -2000 to 2000: range [153000, 157000] (4001 values)
SPACE_OFFSET = 159100 # -2000 to 2000: range [157100, 161100] (4001 values)
AMPLITUDE_OFFSET = 161200 # 0 to 20: range [161200, 161220] (21 values)
ANCHOR_OFFSET = 161300 # -2000 to 2000: range [161300, 165300] (4001 values)
ANIMATED_OFFSET = 165400 # 0 to 1: range [165400, 165401] (2 values)
H_FLAG_OFFSET = 165402 # 0 to 1: range [165402, 165403] (2 values)
OFFSET_VAL_OFFSET = 165404 # 0 to 1: range [165404, 165405] (2 values)
CA_OFFSET = 165406 # 0 to 2: range [165406, 165408] (3 values)
JUSTIFY_OFFSET = 165409 # 0 to 6: range [165409, 165415] (7 values)
TEXT_TRACKING_OFFSET = 165416 # -100 to 500: range [165416, 166016] (601 values)
HAS_STROKE_COLOR_OFFSET = 166017 # 0 to 1: range [166017, 166018] (2 values)
IX_OFFSET = 166019 # 0 to 1000: range [166019, 167019] (1001 values)
BM_OFFSET = 167020 # 0 to 20: range [167020, 167040] (21 values)
CLOSED_OFFSET = 167041 # 0 to 1: range [167041, 167042] (2 values)
DIRECTION_OFFSET = 167043 # 0 to 5: range [167043, 167048] (6 values)
STAR_TYPE_OFFSET = 167049 # 0 to 5: range [167049, 167054] (6 values)
MULTIPLE_OFFSET = 167055 # 0 to 5: range [167055, 167060] (6 values)
COMPOSITE_OFFSET = 167061 # 0 to 5: range [167061, 167066] (6 values)
SKEW_OFFSET = 167067 # -25 to 25: range [167067, 167117] (51 values)
SKEW_AXIS_OFFSET = 167118 # -25 to 25: range [167118, 167168] (51 values)
SCALE_OFFSET = 167169 # -1000 to 2000: range [167169, 170169] (3001 values)
ROTATION_OFFSET = 170170 # -720 to 720: range [170170, 171610] (1441 values)
EASE_OFFSET = 171611 # -100 to 100: range [171611, 171811] (201 values)
SMOOTH_OFFSET = 171812 # 0 to 100: range [171812, 171912] (101 values)
TRACKING_OFFSET = 171913 # -50 to 50: range [171913, 172013] (101 values)
INDEX_OFFSET = 172014 # 0 to 1000: range [172014, 173014] (1001 values)
DDD_OFFSET = 173015 # 0 to 1: range [173015, 173016] (2 values)
HD_OFFSET = 173017 # 0 to 1: range [173017, 173018] (2 values)
CP_OFFSET = 173019 # 0 to 50: range [173019, 173069] (51 values)
HAS_MASK_OFFSET = 173070 # 0 to 1: range [173070, 173071] (2 values)
AO_OFFSET = 173072 # 0 to 1: range [173072, 173073] (2 values)
TT_OFFSET = 173074 # 0 to 5: range [173074, 173079] (6 values)
TP_OFFSET = 173080 # 0 to 100: range [173080, 173180] (101 values)
TD_OFFSET = 173181 # 0 to 2: range [173181, 173183] (3 values)
CT_OFFSET = 173184 # 0 to 1: range [173184, 173185] (2 values)
NUMBER_OFFSET = 173186 # 0 to 500: range [173186, 173686] (501 values)
DIM_OFFSET = 173687 # 0 to 10: range [173687, 173697] (11 values)
HAS_C_A_OFFSET = 173698 # 0 to 1: range [173698, 173699] (2 values)
HAS_C_IX_OFFSET = 173700 # 0 to 1: range [173700, 173701] (2 values)
HAS_O_A_OFFSET = 173702 # 0 to 1: range [173702, 173703] (2 values)
HAS_O_IX_OFFSET = 173704 # 0 to 1: range [173704, 173705] (2 values)
FILL_RULE_OFFSET = 173706 # 0 to 4: range [173706, 173710] (5 values)
TYPE_OFFSET = 173711 # 0 to 40: range [173711, 173751] (41 values)
TEXT_RANGE_UNITS_OFFSET = 173752 # 0 to 10: range [173752, 173762] (11 values)
INV_OFFSET = 173763 # 0 to 1: range [173763, 173764] (2 values)
MODE_OFFSET = 173765 # 0 to 10: range [173765, 173775] (11 values)
TEXT_SHAPE_TYPE_OFFSET = 173776 # 0 to 10: range [173776, 173786] (11 values)
TEXT_RANDOM_OFFSET = 173787 # 0 to 1: range [173787, 173788] (2 values)
COLOR_POINTS_OFFSET = 173789 # 0 to 50: range [173789, 173839] (51 values)
ROUND_OFFSET = 173840 # -100 to 1000: range [173840, 174940] (1101 values)
RADIUS_OFFSET = 174941 # 0 to 300: range [174941, 175241] (301 values)
FREQUENCY_OFFSET = 175242 # 0 to 150: range [175242, 175392] (151 values)
SPEED_OFFSET = 175393 # -1000 to 1000: range [175393, 177393] (2001 values)
FONT_OFFSET = 177394 # -100 to 2000: range [177394, 179494] (2101 values)
COLOR_OFFSET = 179495 # 0 to 255: range [179495, 179750] (256 values)
LINE_CAP_OFFSET = 179752 # 1 to 3: range [179752, 179754] (3 values)
LINE_JOIN_OFFSET = 179757 # 1 to 3: range [179757, 179759] (3 values)
MITER_LIMIT_OFFSET = 179760 # 0 to 100: range [179760, 179860] (101 values)
EFFECT_OFFSET = 179861 # -250 to 1000: range [179861, 181111] (1251 values)
OPACITY_OFFSET = 181112 # 0 to 100: range [181112, 181212] (101 values)
WIDTH_VALUE_OFFSET = 181300 # 0 to 10000: range [181300, 191300] (10001 values for 0-100.00)
NO_OFFSET = 0
# Time dictionary parameters - all time-related values
time_params = {
LottieTensor.CMD_ANIMATION: [
LottieTensor.Index.Animation.IP,
LottieTensor.Index.Animation.OP
],
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.IN_POINT,
LottieTensor.Index.Layer.OUT_POINT,
LottieTensor.Index.Layer.START_TIME
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.IN_POINT,
LottieTensor.Index.NullLayer.OUT_POINT,
LottieTensor.Index.NullLayer.START_TIME
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.IN_POINT,
LottieTensor.Index.PrecompLayer.OUT_POINT,
LottieTensor.Index.PrecompLayer.START_TIME
],
LottieTensor.CMD_TEXT_LAYER: [
LottieTensor.Index.TextLayer.IN_POINT,
LottieTensor.Index.TextLayer.OUT_POINT,
LottieTensor.Index.TextLayer.START_TIME
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.IN_POINT,
LottieTensor.Index.SolidLayer.OUT_POINT,
LottieTensor.Index.SolidLayer.START_TIME
],
LottieTensor.CMD_KEYFRAME: [
LottieTensor.Index.Keyframe.T
],
LottieTensor.CMD_WIDTH_KEYFRAME: [
LottieTensor.Index.WidthKeyframe.T
],
LottieTensor.CMD_COLOR_KEYFRAME: [
LottieTensor.Index.Keyframe.T
],
LottieTensor.CMD_OPACITY_KEYFRAME: [
LottieTensor.Index.Keyframe.T
],
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.T
],
LottieTensor.CMD_MASK_PT_KEYFRAME: [
LottieTensor.Index.MaskPtKeyframe.T
],
LottieTensor.CMD_RANGE_START_KEYFRAME: [
LottieTensor.Index.RangeStartKeyframe.T
],
LottieTensor.CMD_RANGE_END_KEYFRAME: [
LottieTensor.Index.RangeEndKeyframe.T
],
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: [
LottieTensor.Index.RangeOffsetKeyframe.T
],
LottieTensor.CMD_DASH_KEYFRAME: [
LottieTensor.Index.DashKeyframe.T
],
}
# Space dictionary parameters - all spatial/positional values
space_params = {
LottieTensor.CMD_ANIMATION: [
LottieTensor.Index.Animation.W,
LottieTensor.Index.Animation.H
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.W,
LottieTensor.Index.PrecompLayer.H
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.WIDTH,
LottieTensor.Index.SolidLayer.HEIGHT
],
LottieTensor.CMD_DIMENSIONS: [
LottieTensor.Index.Dimensions.WIDTH,
LottieTensor.Index.Dimensions.HEIGHT
],
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.STROKE_WIDTH,
LottieTensor.Index.TextKeyframe.WRAP_POSITION_X,
LottieTensor.Index.TextKeyframe.WRAP_POSITION_Y,
LottieTensor.Index.TextKeyframe.WRAP_SIZE_X,
LottieTensor.Index.TextKeyframe.WRAP_SIZE_Y
],
LottieTensor.CMD_KEYFRAME: [
LottieTensor.Index.Keyframe.S1, LottieTensor.Index.Keyframe.S2, LottieTensor.Index.Keyframe.S3,
LottieTensor.Index.Keyframe.E1, LottieTensor.Index.Keyframe.E2, LottieTensor.Index.Keyframe.E3,
LottieTensor.Index.Keyframe.TO1, LottieTensor.Index.Keyframe.TO2, LottieTensor.Index.Keyframe.TO3,
LottieTensor.Index.Keyframe.TI1, LottieTensor.Index.Keyframe.TI2, LottieTensor.Index.Keyframe.TI3
],
#LottieTensor.CMD_WIDTH_KEYFRAME: [
# LottieTensor.Index.WidthKeyframe.S,
#],
LottieTensor.CMD_OPACITY_KEYFRAME: [
LottieTensor.Index.Keyframe.S1,
],
LottieTensor.CMD_POSITION: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y, LottieTensor.Index.Transform.Z,
LottieTensor.Index.TwoValues.VALUE1, LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_POSITION_X: [
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_POSITION_Y: [
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_POSITION_Z: [
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_POINT: [
LottieTensor.Index.Point.X, LottieTensor.Index.Point.Y,
LottieTensor.Index.Point.IN_X, LottieTensor.Index.Point.IN_Y,
LottieTensor.Index.Point.OUT_X, LottieTensor.Index.Point.OUT_Y
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.POSITION_X, LottieTensor.Index.TransformShape.POSITION_Y,
],
LottieTensor.CMD_SIZE: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y # 修改
],
LottieTensor.CMD_RECT_SIZE: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y # 修改
],
LottieTensor.CMD_ELLIPSE_SIZE: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y # 修改
],
LottieTensor.CMD_START_POINT: [
LottieTensor.Index.TwoValues.VALUE1, LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_END_POINT: [
LottieTensor.Index.TwoValues.VALUE1, LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_POINTS_STAR: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_START: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_END: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OFFSET: [
LottieTensor.Index.SingleValue.VALUE
],
#LottieTensor.CMD_WIDTH: [
# LottieTensor.Index.SingleValue.VALUE
#],
#LottieTensor.CMD_DASH: [
# LottieTensor.Index.Dash.LENGTH
#],
#LottieTensor.CMD_DASH_OFFSET: [
# LottieTensor.Index.DashOffset.O
#],
#LottieTensor.CMD_DASH_KEYFRAME: [
# LottieTensor.Index.DashKeyframe.S,
# ],
LottieTensor.CMD_TR_POSITION: [
LottieTensor.Index.TrPosition.X, LottieTensor.Index.TrPosition.Y
],
LottieTensor.CMD_REPEATER_OFFSET: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_RANGE_START_KEYFRAME: [
LottieTensor.Index.RangeStartKeyframe.S,
],
LottieTensor.CMD_RANGE_END_KEYFRAME: [
LottieTensor.Index.RangeEndKeyframe.S,
],
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: [
LottieTensor.Index.RangeOffsetKeyframe.S,
],
LottieTensor.CMD_POSITION_ANIMATORS: [
LottieTensor.Index.PositionAnimators.K_X,
LottieTensor.Index.PositionAnimators.K_Y,
LottieTensor.Index.PositionAnimators.K_Z
],
LottieTensor.CMD_MASK_X: [
LottieTensor.Index.MaskX.K
],
LottieTensor.CMD_MASK_PT_K_I: list(range(20)),
LottieTensor.CMD_MASK_PT_K_O: list(range(20)),
LottieTensor.CMD_MASK_PT_K_V: list(range(20)),
LottieTensor.CMD_MASK_PT_KF_I: [
LottieTensor.Index.MaskPtKfI.X, LottieTensor.Index.MaskPtKfI.Y
],
LottieTensor.CMD_MASK_PT_KF_O: [
LottieTensor.Index.MaskPtKfO.X, LottieTensor.Index.MaskPtKfO.Y
],
LottieTensor.CMD_MASK_PT_KF_SHAPE_I: list(range(20)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_O: list(range(20)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_V: list(range(20)),
LottieTensor.CMD_VALUE: [
LottieTensor.Index.Value.VALUE
],
LottieTensor.CMD_MORE_OPTIONS: [
LottieTensor.Index.MoreOptions.ALIGNMENT_K1,
LottieTensor.Index.MoreOptions.ALIGNMENT_K2
],
LottieTensor.CMD_ALIGNMENT_K: [
LottieTensor.Index.AlignmentK.VALUE1,
LottieTensor.Index.AlignmentK.VALUE2
],
LottieTensor.CMD_CHAR: [
LottieTensor.Index.Char.W
],
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.START_POINT_X,
LottieTensor.Index.GradientFill.START_POINT_Y,
LottieTensor.Index.GradientFill.END_POINT_X,
LottieTensor.Index.GradientFill.END_POINT_Y,
LottieTensor.Index.GradientFill.HIGHLIGHT_LENGTH,
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.WIDTH,
LottieTensor.Index.GradientStroke.START_POINT_X,
LottieTensor.Index.GradientStroke.START_POINT_Y,
LottieTensor.Index.GradientStroke.END_POINT_X,
LottieTensor.Index.GradientStroke.END_POINT_Y,
LottieTensor.Index.GradientStroke.HIGHLIGHT_LENGTH,
],
LottieTensor.CMD_HIGHLIGHT_LENGTH: [
LottieTensor.Index.SingleValue.VALUE
],
}
width_value_params = {
LottieTensor.CMD_WIDTH: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_DASH: [
LottieTensor.Index.Dash.LENGTH
],
LottieTensor.CMD_DASH_OFFSET: [
LottieTensor.Index.DashOffset.O
],
LottieTensor.CMD_WIDTH_KEYFRAME: [
LottieTensor.Index.WidthKeyframe.S,
],
LottieTensor.CMD_DASH_KEYFRAME: [
LottieTensor.Index.DashKeyframe.S,
],
}
amplitude_params = {
LottieTensor.CMD_AMPLITUDE: [
LottieTensor.Index.Amplitude.VALUE
],
}
anchor_params = {
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.ANCHOR_X, LottieTensor.Index.TransformShape.ANCHOR_Y,
],
LottieTensor.CMD_TR_ANCHOR: [
LottieTensor.Index.TrAnchor.X, LottieTensor.Index.TrAnchor.Y
],
LottieTensor.CMD_ANCHOR: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y, LottieTensor.Index.Transform.Z
],
}
animated_params = {
LottieTensor.CMD_MORE_OPTIONS: [
LottieTensor.Index.MoreOptions.ALIGNMENT_A,
],
LottieTensor.CMD_ELLIPSE_SIZE: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_RECT_SIZE: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_POSITION: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_POSITION_X: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_POSITION_Y: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_POSITION_Z: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_SCALE: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_ROTATION: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_OPACITY: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_ANCHOR: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_SIZE: [
LottieTensor.Index.Transform.ANIMATED
],
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.ANIMATED,
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.COLOR_ANIMATED,
LottieTensor.Index.Fill.OPACITY_ANIMATED,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.WIDTH_ANIMATED,
LottieTensor.Index.Stroke.COLOR_ANIMATED
],
LottieTensor.CMD_RECT_ROUNDED: [
LottieTensor.Index.SingleValue.ANIMATED
],
LottieTensor.CMD_START: [
LottieTensor.Index.SingleValue.ANIMATED
],
LottieTensor.CMD_END: [
LottieTensor.Index.SingleValue.ANIMATED
],
LottieTensor.CMD_OFFSET: [
LottieTensor.Index.SingleValue.ANIMATED
],
LottieTensor.CMD_MASK_PT: [
LottieTensor.Index.MaskPt.A,
],
LottieTensor.CMD_MASK_O: [
LottieTensor.Index.MaskO.A,
],
LottieTensor.CMD_MASK_X: [
LottieTensor.Index.MaskX.A,
],
LottieTensor.CMD_TM: [
LottieTensor.Index.Tm.A
],
LottieTensor.CMD_RANGE_START: [
LottieTensor.Index.RangeStart.A
],
LottieTensor.CMD_RANGE_END: [
LottieTensor.Index.RangeEnd.A
],
LottieTensor.CMD_RANGE_OFFSET: [
LottieTensor.Index.Amount.A,
],
LottieTensor.CMD_AMOUNT: [
LottieTensor.Index.Amount.A,
],
LottieTensor.CMD_MAX_EASE: [
LottieTensor.Index.MaxEase.A,
],
LottieTensor.CMD_MIN_EASE: [
LottieTensor.Index.MinEase.A,
],
LottieTensor.CMD_S_M: [
LottieTensor.Index.SM.A,
],
LottieTensor.CMD_OPACITY_ANIMATORS: [
LottieTensor.Index.OpacityAnimators.A,
],
LottieTensor.CMD_POSITION_ANIMATORS: [
LottieTensor.Index.PositionAnimators.A,
],
LottieTensor.CMD_SCALE_ANIMATORS: [
LottieTensor.Index.ScaleAnimators.A,
],
LottieTensor.CMD_ROTATION_ANIMATORS: [
LottieTensor.Index.RotationAnimators.A,
],
LottieTensor.CMD_TRACKING_ANIMATORS: [
LottieTensor.Index.TrackingAnimators.A,
],
LottieTensor.CMD_ALIGNMENT: [
LottieTensor.Index.Alignment.A
],
}
h_flag_params = {
LottieTensor.CMD_KEYFRAME: [
LottieTensor.Index.Keyframe.H_FLAG
],
}
offset_val_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.OFFSET,
],
}
ca_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.CA,
],
LottieTensor.CMD_CA: [
LottieTensor.Index.Ca.VALUE
],
}
justify_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.JUSTIFY,
],
LottieTensor.CMD_JUSTIFY: [
LottieTensor.Index.Justify.VALUE
],
}
text_tracking_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.TRACKING,
],
LottieTensor.CMD_TRACKING: [
LottieTensor.Index.Tracking.VALUE
],
}
has_stroke_color_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.HAS_STROKE_COLOR,
],
}
ix_params = {
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.IX,
LottieTensor.Index.Path.KS_IX,
],
LottieTensor.CMD_GROUP: [
LottieTensor.Index.Group.IX,
LottieTensor.Index.Group.CIX,
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.C_IX,
LottieTensor.Index.Fill.O_IX,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.C_IX,
],
LottieTensor.CMD_RECT: [
LottieTensor.Index.Rect.IX,
],
LottieTensor.CMD_ROUNDED: [
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_TRIM: [
LottieTensor.Index.Trim.IX
],
LottieTensor.CMD_REPEATER: [
LottieTensor.Index.Repeater.IX
],
LottieTensor.CMD_COPIES: [
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_REPEATER_OFFSET: [
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_TR_P_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_A_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_S_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_R_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_SO_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_EO_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.ML2_IX,
],
LottieTensor.CMD_MASK_PT: [
LottieTensor.Index.MaskPt.IX,
],
LottieTensor.CMD_MASK_O: [
LottieTensor.Index.MaskO.IX,
],
LottieTensor.CMD_MASK_X: [
LottieTensor.Index.MaskX.IX,
],
LottieTensor.CMD_ZIG_ZAG: [
LottieTensor.Index.ZigZag.IX
],
LottieTensor.CMD_RANGE_OFFSET: [
LottieTensor.Index.Amount.IX
],
LottieTensor.CMD_AMOUNT: [
LottieTensor.Index.Amount.IX
],
LottieTensor.CMD_MAX_EASE: [
LottieTensor.Index.MaxEase.IX
],
LottieTensor.CMD_MIN_EASE: [
LottieTensor.Index.MinEase.IX
],
LottieTensor.CMD_S_M: [
LottieTensor.Index.SM.IX
],
LottieTensor.CMD_OPACITY_ANIMATORS: [
LottieTensor.Index.OpacityAnimators.IX
],
LottieTensor.CMD_POSITION_ANIMATORS: [
LottieTensor.Index.PositionAnimators.IX
],
LottieTensor.CMD_SCALE_ANIMATORS: [
LottieTensor.Index.ScaleAnimators.IX
],
LottieTensor.CMD_ROTATION_ANIMATORS: [
LottieTensor.Index.RotationAnimators.IX
],
LottieTensor.CMD_TRACKING_ANIMATORS: [
LottieTensor.Index.TrackingAnimators.IX
],
LottieTensor.CMD_ALIGNMENT_IX: [
LottieTensor.Index.AlignmentIx.VALUE
],
LottieTensor.CMD_MORE_OPTIONS: [
LottieTensor.Index.MoreOptions.ALIGNMENT_IX
],
LottieTensor.CMD_DASH: [
LottieTensor.Index.Dash.V_IX
],
LottieTensor.CMD_DASH_ANIMATED: [
LottieTensor.Index.DashAnimated.V_IX,
],
}
bm_params = {
LottieTensor.CMD_GROUP: [
LottieTensor.Index.Group.BM,
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.BM,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.BM,
],
}
closed_params = {
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.CLOSED,
],
LottieTensor.CMD_BEZIER: [
LottieTensor.Index.Bezier.CLOSED
],
LottieTensor.CMD_MASK_PT_K_C: [
LottieTensor.Index.MaskPtK.C
],
LottieTensor.CMD_MASK_PT_KF_SHAPE: [
LottieTensor.Index.MaskPtKfShape.C,
],
}
direction_params = {
LottieTensor.CMD_RECT: [
LottieTensor.Index.Rect.D,
],
LottieTensor.CMD_STAR: [
LottieTensor.Index.Star.D,
],
}
star_type_params = {
LottieTensor.CMD_STAR: [
LottieTensor.Index.Star.SY
],
}
multiple_params = {
LottieTensor.CMD_MULTIPLE: [
LottieTensor.Index.SingleValue.VALUE
],
}
composite_params = {
LottieTensor.CMD_COMPOSITE: [
LottieTensor.Index.SingleValue.VALUE
],
}
skew_params = {
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.SKEW,
],
LottieTensor.CMD_SKEW: [
LottieTensor.Index.SingleValue.VALUE
],
}
skew_axis_params = {
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.SKEW_AXIS,
],
LottieTensor.CMD_SKEW_AXIS: [
LottieTensor.Index.SingleValue.VALUE
],
}
scale_params = {
LottieTensor.CMD_SCALE: [
LottieTensor.Index.Transform.X, LottieTensor.Index.Transform.Y, LottieTensor.Index.Transform.Z
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.SCALE_X, LottieTensor.Index.TransformShape.SCALE_Y,
],
LottieTensor.CMD_TR_SCALE: [
LottieTensor.Index.TwoValues.VALUE1, LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_SCALE_ANIMATORS: [
LottieTensor.Index.ScaleAnimators.K_X,
LottieTensor.Index.ScaleAnimators.K_Y,
LottieTensor.Index.ScaleAnimators.K_Z
],
}
rotation_params = {
LottieTensor.CMD_ROTATION: [
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.ROTATION
],
LottieTensor.CMD_STAR_ROTATION: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_ROTATION: [
LottieTensor.Index.TrRotation.VALUE
],
LottieTensor.CMD_ROTATION_ANIMATORS: [
LottieTensor.Index.RotationAnimators.K
],
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.HIGHLIGHT_ANGLE,
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.HIGHLIGHT_ANGLE
],
LottieTensor.CMD_HIGHLIGHT_ANGLE: [
LottieTensor.Index.SingleValue.VALUE
],
}
ease_params = {
LottieTensor.CMD_MAX_EASE: [
LottieTensor.Index.MaxEase.K
],
LottieTensor.CMD_MIN_EASE: [
LottieTensor.Index.MinEase.K
],
}
smooth_params = {
LottieTensor.CMD_S_M: [
LottieTensor.Index.SM.K
],
}
tracking_params = {
LottieTensor.CMD_TRACKING_ANIMATORS: [
LottieTensor.Index.TrackingAnimators.K
],
}
index_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.INDEX,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.INDEX,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.INDEX,
],
LottieTensor.CMD_TEXT_LAYER: [
LottieTensor.Index.TextLayer.INDEX,
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.INDEX,
],
LottieTensor.CMD_PARENT: [
LottieTensor.Index.Parent.PARENT_INDEX
],
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.IND,
],
LottieTensor.CMD_COLOR: [
LottieTensor.Index.Color.INDEX
],
LottieTensor.CMD_MASK: [
LottieTensor.Index.Mask.INDEX,
],
LottieTensor.CMD_MASK_PT_KEYFRAME: [
LottieTensor.Index.MaskPtKeyframe.INDEX
],
LottieTensor.CMD_MASK_PT_KF_SHAPE: [
LottieTensor.Index.MaskPtKfShape.INDEX,
],
LottieTensor.CMD_EFFECT: [
LottieTensor.Index.Effect.INDEX,
],
LottieTensor.CMD_LAYER_EFFECT: [
LottieTensor.Index.LayerEffect.INDEX,
],
LottieTensor.CMD_DROPDOWN: [
LottieTensor.Index.Dropdown.INDEX,
],
LottieTensor.CMD_NO_VALUE: [
LottieTensor.Index.NO_VALUE.INDEX,
],
LottieTensor.CMD_IGNORED: [
LottieTensor.Index.Ignored.INDEX,
],
LottieTensor.CMD_SLIDER: [
LottieTensor.Index.Slider.INDEX,
],
}
ddd_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.DDD,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.DDD,
],
LottieTensor.CMD_ANIMATION: [
LottieTensor.Index.Animation.DDD
],
}
hd_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.HD,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.HD,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.HD,
],
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.HD,
],
LottieTensor.CMD_GROUP: [
LottieTensor.Index.Group.HD,
],
LottieTensor.CMD_RECT: [
LottieTensor.Index.Rect.HD,
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.HD
],
}
cp_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.CP,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.CP,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.CP,
],
}
has_mask_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.HAS_MASK,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.HAS_MASK,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.HAS_MASK,
],
LottieTensor.CMD_TEXT_LAYER: [
LottieTensor.Index.TextLayer.HAS_MASK,
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.HAS_MASK
],
}
ao_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.AO,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.AO,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.AO,
],
}
tt_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.TT,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.TT,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.TT,
],
}
tp_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.TP,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.TP,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.TP,
],
}
td_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.TD,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.TD,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.TD,
],
}
ct_params = {
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.CT,
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.CT,
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.CT,
],
}
number_params = {
LottieTensor.CMD_COPIES: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_AMOUNT: [
LottieTensor.Index.Amount.K
],
LottieTensor.CMD_RANGE_OFFSET: [
LottieTensor.Index.Amount.K
],
LottieTensor.CMD_GROUP: [
LottieTensor.Index.Group.NP
],
LottieTensor.CMD_EFFECT: [
LottieTensor.Index.Effect.NP,
],
}
dim_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.COLOR_DIM,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.COLOR_DIM,
],
}
has_c_a_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.HAS_C_A,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.HAS_C_A,
],
}
has_c_ix_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.HAS_C_IX,
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.HAS_C_IX,
],
}
has_o_a_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.HAS_O_A,
],
}
has_o_ix_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.HAS_O_IX,
],
}
fill_rule_params = {
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.FILL_RULE,
],
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.FILL_RULE,
],
LottieTensor.CMD_FILL_RULE: [
LottieTensor.Index.SingleValue.VALUE
],
}
type_params = {
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.GRADIENT_TYPE,
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.GRADIENT_TYPE,
],
LottieTensor.CMD_GRADIENT_TYPE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_POINT_TYPE: [
LottieTensor.Index.PointType.VALUE
],
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.T,
],
LottieTensor.CMD_DASH: [
LottieTensor.Index.Dash.TYPE,
],
LottieTensor.CMD_DASH_ANIMATED: [
LottieTensor.Index.DashAnimated.TYPE,
],
LottieTensor.CMD_EFFECT: [
LottieTensor.Index.Effect.TYPE,
],
}
text_range_units = {
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.R,
],
}
inv_params = {
LottieTensor.CMD_MASK: [
LottieTensor.Index.Mask.INV,
],
}
mode_params = {
LottieTensor.CMD_MERGE_MODE: [
LottieTensor.Index.MergeMode.MODE
],
LottieTensor.CMD_MASK: [
LottieTensor.Index.Mask.MODE,
],
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.B,
],
}
text_shape_type = {
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.SH,
],
}
text_random = {
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.RN
],
}
color_points_params = {
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.COLOR_POINTS
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.COLOR_POINTS
],
LottieTensor.CMD_COLOR_POINTS: [
LottieTensor.Index.SingleValue.VALUE
],
}
round_params = {
LottieTensor.CMD_ROUNDED: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_RECT_ROUNDED: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_INNER_ROUNDNESS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OUTER_ROUNDNESS: [
LottieTensor.Index.SingleValue.VALUE
],
}
radius_params = {
LottieTensor.CMD_INNER_RADIUS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OUTER_RADIUS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_RADIUS: [
LottieTensor.Index.Radius.VALUE
],
}
frequency_params = {
LottieTensor.CMD_ANIMATION: [
LottieTensor.Index.Animation.FR,
],
LottieTensor.CMD_FREQUENCY: [
LottieTensor.Index.Frequency.VALUE
],
LottieTensor.CMD_ASSET: [
LottieTensor.Index.Asset.FR
],
}
speed_params = {
LottieTensor.CMD_KEYFRAME: [
LottieTensor.Index.Keyframe.I_X, LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X, LottieTensor.Index.Keyframe.O_Y,
LottieTensor.Index.Keyframe.I_X2, LottieTensor.Index.Keyframe.I_Y2,
LottieTensor.Index.Keyframe.O_X2, LottieTensor.Index.Keyframe.O_Y2,
LottieTensor.Index.Keyframe.I_X3, LottieTensor.Index.Keyframe.I_Y3,
LottieTensor.Index.Keyframe.O_X3, LottieTensor.Index.Keyframe.O_Y3,
],
LottieTensor.CMD_WIDTH_KEYFRAME: [
LottieTensor.Index.WidthKeyframe.I_X, LottieTensor.Index.WidthKeyframe.I_Y,
LottieTensor.Index.WidthKeyframe.O_X, LottieTensor.Index.WidthKeyframe.O_Y
],
LottieTensor.CMD_OPACITY_KEYFRAME: [
LottieTensor.Index.Keyframe.I_X, LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X, LottieTensor.Index.Keyframe.O_Y
],
LottieTensor.CMD_COLOR_KEYFRAME: [
LottieTensor.Index.Keyframe.I_X, LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X, LottieTensor.Index.Keyframe.O_Y
],
LottieTensor.CMD_DASH_KEYFRAME: [
LottieTensor.Index.DashKeyframe.I_X, LottieTensor.Index.DashKeyframe.I_Y,
LottieTensor.Index.DashKeyframe.O_X, LottieTensor.Index.DashKeyframe.O_Y
],
LottieTensor.CMD_RANGE_START_KEYFRAME: [
LottieTensor.Index.RangeStartKeyframe.I_X, LottieTensor.Index.RangeStartKeyframe.I_Y,
LottieTensor.Index.RangeStartKeyframe.O_X, LottieTensor.Index.RangeStartKeyframe.O_Y
],
LottieTensor.CMD_RANGE_END_KEYFRAME: [
LottieTensor.Index.RangeEndKeyframe.I_X, LottieTensor.Index.RangeEndKeyframe.I_Y,
LottieTensor.Index.RangeEndKeyframe.O_X, LottieTensor.Index.RangeEndKeyframe.O_Y
],
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: [
LottieTensor.Index.RangeOffsetKeyframe.I_X, LottieTensor.Index.RangeOffsetKeyframe.I_Y,
LottieTensor.Index.RangeOffsetKeyframe.O_X, LottieTensor.Index.RangeOffsetKeyframe.O_Y
],
}
font_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.FONT_SIZE,
LottieTensor.Index.TextKeyframe.LINE_HEIGHT,
LottieTensor.Index.TextKeyframe.LETTER_SPACING
],
LottieTensor.CMD_FONT_SIZE: [
LottieTensor.Index.FontSize.SIZE
],
LottieTensor.CMD_LINE_HEIGHT: [
LottieTensor.Index.LineHeight.VALUE
],
LottieTensor.CMD_LETTER_SPACING: [
LottieTensor.Index.LetterSpacing.VALUE
],
LottieTensor.CMD_FONT: [
LottieTensor.Index.Font.ASCENT
],
LottieTensor.CMD_CHAR: [
LottieTensor.Index.Char.SIZE
],
}
color_params = {
LottieTensor.CMD_TEXT_KEYFRAME: [
LottieTensor.Index.TextKeyframe.FILL_COLOR_R,
LottieTensor.Index.TextKeyframe.FILL_COLOR_G,
LottieTensor.Index.TextKeyframe.FILL_COLOR_B,
LottieTensor.Index.TextKeyframe.STROKE_COLOR_R,
LottieTensor.Index.TextKeyframe.STROKE_COLOR_G,
LottieTensor.Index.TextKeyframe.STROKE_COLOR_B
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.R,
LottieTensor.Index.Stroke.G,
LottieTensor.Index.Stroke.B,
LottieTensor.Index.Stroke.A
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.R,
LottieTensor.Index.Fill.G,
LottieTensor.Index.Fill.B,
],
LottieTensor.CMD_FILL_COLOR: [
LottieTensor.Index.FillColor.R,
LottieTensor.Index.FillColor.G,
LottieTensor.Index.FillColor.B
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.COLOR_R,
LottieTensor.Index.SolidLayer.COLOR_G,
LottieTensor.Index.SolidLayer.COLOR_B,
LottieTensor.Index.SolidLayer.COLOR_A
],
LottieTensor.CMD_COLOR: [
LottieTensor.Index.Color.R,
LottieTensor.Index.Color.G,
LottieTensor.Index.Color.B
],
LottieTensor.CMD_COLOR_KEYFRAME: [
LottieTensor.Index.Keyframe.S1,
LottieTensor.Index.Keyframe.S2,
LottieTensor.Index.Keyframe.S3,
LottieTensor.Index.Keyframe.E1
],
LottieTensor.CMD_ORIGINAL_COLORS: list(range(LottieTensor.Index.OriginalColors.COUNT)),
LottieTensor.CMD_GRADIENT_FILL: list(range(LottieTensor.Index.GradientFill.ORIGINAL_COLOR_0,
LottieTensor.Index.GradientFill.ORIGINAL_COLOR_23 + 1)),
LottieTensor.CMD_GRADIENT_STROKE: list(range(LottieTensor.Index.GradientStroke.ORIGINAL_COLOR_0,
LottieTensor.Index.GradientStroke.ORIGINAL_COLOR_23 + 1)),
}
line_cap_params = {
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.LC,
],
LottieTensor.CMD_LINE_CAP: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.LINE_CAP,
],
}
line_join_params = {
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.LJ,
],
LottieTensor.CMD_LINE_JOIN: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.LINE_JOIN,
],
}
miter_limit_params = {
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.ML
],
LottieTensor.CMD_MITER_LIMIT: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_ML2: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.MITER_LIMIT,
LottieTensor.Index.GradientStroke.ML2
],
}
enabled_params = {
LottieTensor.CMD_EFFECT: [
LottieTensor.Index.Effect.ENABLED
],
}
effect_params = {
LottieTensor.CMD_LAYER_EFFECT: [
LottieTensor.Index.LayerEffect.VALUE
],
LottieTensor.CMD_DROPDOWN: [
LottieTensor.Index.Dropdown.VALUE
],
LottieTensor.CMD_NO_VALUE: [
LottieTensor.Index.NO_VALUE.VALUE
],
LottieTensor.CMD_IGNORED: [
LottieTensor.Index.Ignored.VALUE
],
LottieTensor.CMD_SLIDER: [
LottieTensor.Index.Slider.VALUE
],
}
opacity_params = {
LottieTensor.CMD_GRADIENT_FILL: [
LottieTensor.Index.GradientFill.OPACITY
],
LottieTensor.CMD_GRADIENT_STROKE: [
LottieTensor.Index.GradientStroke.OPACITY
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.OPACITY
],
LottieTensor.CMD_OPACITY: [
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.OPACITY,
],
LottieTensor.CMD_TR_START_OPACITY: [
LottieTensor.Index.TrStartOpacity.VALUE
],
LottieTensor.CMD_TR_END_OPACITY: [
LottieTensor.Index.TrEndOpacity.VALUE
],
LottieTensor.CMD_OPACITY_ANIMATORS: [
LottieTensor.Index.OpacityAnimators.K
],
LottieTensor.CMD_MASK_O: [
LottieTensor.Index.MaskO.K
],
}
# Tokenizer parameters (no offset)
tokenizer_params = {
LottieTensor.CMD_TEXT_KEYFRAME: list(range(LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START,
LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT + 1)),
LottieTensor.CMD_ASSET: list(range(LottieTensor.Index.Asset.ID_TOKEN_0,
LottieTensor.Index.Asset.ID_TOKEN_COUNT + 1)),
LottieTensor.CMD_REFERENCE_ID: list(range(LottieTensor.Index.ReferenceId.ID_TOKEN_0,
LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT + 1)),
LottieTensor.CMD_FONT: list(range(LottieTensor.Index.Font.FAMILY_TOKEN_0,
LottieTensor.Index.Font.STYLE_TOKEN_COUNT + 1)),
LottieTensor.CMD_CHAR: list(range(LottieTensor.Index.Char.CH_TOKEN_0,
LottieTensor.Index.Char.FAMILY_TOKEN_COUNT + 1)),
}
# 添加 width_value_params 的判断（在其他判断之前）
if cmd_idx in width_value_params and param_idx in width_value_params[cmd_idx]:
return WIDTH_VALUE_OFFSET
elif cmd_idx in tokenizer_params and param_idx in tokenizer_params[cmd_idx]:
return NO_OFFSET # No offset for tokenizer tokens
elif cmd_idx in time_params and param_idx in time_params[cmd_idx]:
return TIME_OFFSET
elif cmd_idx in space_params and param_idx in space_params[cmd_idx]:
return SPACE_OFFSET
elif cmd_idx in amplitude_params and param_idx in amplitude_params[cmd_idx]:
return AMPLITUDE_OFFSET
elif cmd_idx in anchor_params and param_idx in anchor_params[cmd_idx]:
return ANCHOR_OFFSET
elif cmd_idx in animated_params and param_idx in animated_params[cmd_idx]:
return ANIMATED_OFFSET
elif cmd_idx in h_flag_params and param_idx in h_flag_params[cmd_idx]:
return H_FLAG_OFFSET
elif cmd_idx in offset_val_params and param_idx in offset_val_params[cmd_idx]:
return OFFSET_VAL_OFFSET
elif cmd_idx in ca_params and param_idx in ca_params[cmd_idx]:
return CA_OFFSET
elif cmd_idx in justify_params and param_idx in justify_params[cmd_idx]:
return JUSTIFY_OFFSET
elif cmd_idx in text_tracking_params and param_idx in text_tracking_params[cmd_idx]:
return TEXT_TRACKING_OFFSET
elif cmd_idx in has_stroke_color_params and param_idx in has_stroke_color_params[cmd_idx]:
return HAS_STROKE_COLOR_OFFSET
elif cmd_idx in ix_params and param_idx in ix_params[cmd_idx]:
return IX_OFFSET
elif cmd_idx in bm_params and param_idx in bm_params[cmd_idx]:
return BM_OFFSET
elif cmd_idx in closed_params and param_idx in closed_params[cmd_idx]:
return CLOSED_OFFSET
elif cmd_idx in direction_params and param_idx in direction_params[cmd_idx]:
return DIRECTION_OFFSET
elif cmd_idx in star_type_params and param_idx in star_type_params[cmd_idx]:
return STAR_TYPE_OFFSET
elif cmd_idx in multiple_params and param_idx in multiple_params[cmd_idx]:
return MULTIPLE_OFFSET
elif cmd_idx in composite_params and param_idx in composite_params[cmd_idx]:
return COMPOSITE_OFFSET
elif cmd_idx in skew_params and param_idx in skew_params[cmd_idx]:
return SKEW_OFFSET
elif cmd_idx in skew_axis_params and param_idx in skew_axis_params[cmd_idx]:
return SKEW_AXIS_OFFSET
elif cmd_idx in scale_params and param_idx in scale_params[cmd_idx]:
return SCALE_OFFSET
elif cmd_idx in rotation_params and param_idx in rotation_params[cmd_idx]:
return ROTATION_OFFSET
elif cmd_idx in ease_params and param_idx in ease_params[cmd_idx]:
return EASE_OFFSET
elif cmd_idx in smooth_params and param_idx in smooth_params[cmd_idx]:
return SMOOTH_OFFSET
elif cmd_idx in tracking_params and param_idx in tracking_params[cmd_idx]:
return TRACKING_OFFSET
elif cmd_idx in index_params and param_idx in index_params[cmd_idx]:
return INDEX_OFFSET
elif cmd_idx in ddd_params and param_idx in ddd_params[cmd_idx]:
return DDD_OFFSET
elif cmd_idx in hd_params and param_idx in hd_params[cmd_idx]:
return HD_OFFSET
elif cmd_idx in cp_params and param_idx in cp_params[cmd_idx]:
return CP_OFFSET
elif cmd_idx in has_mask_params and param_idx in has_mask_params[cmd_idx]:
return HAS_MASK_OFFSET
elif cmd_idx in ao_params and param_idx in ao_params[cmd_idx]:
return AO_OFFSET
elif cmd_idx in tt_params and param_idx in tt_params[cmd_idx]:
return TT_OFFSET
elif cmd_idx in tp_params and param_idx in tp_params[cmd_idx]:
return TP_OFFSET
elif cmd_idx in td_params and param_idx in td_params[cmd_idx]:
return TD_OFFSET
elif cmd_idx in ct_params and param_idx in ct_params[cmd_idx]:
return CT_OFFSET
elif cmd_idx in number_params and param_idx in number_params[cmd_idx]:
return NUMBER_OFFSET
elif cmd_idx in dim_params and param_idx in dim_params[cmd_idx]:
return DIM_OFFSET
elif cmd_idx in has_c_a_params and param_idx in has_c_a_params[cmd_idx]:
return HAS_C_A_OFFSET
elif cmd_idx in has_c_ix_params and param_idx in has_c_ix_params[cmd_idx]:
return HAS_C_IX_OFFSET
elif cmd_idx in has_o_a_params and param_idx in has_o_a_params[cmd_idx]:
return HAS_O_A_OFFSET
elif cmd_idx in has_o_ix_params and param_idx in has_o_ix_params[cmd_idx]:
return HAS_O_IX_OFFSET
elif cmd_idx in fill_rule_params and param_idx in fill_rule_params[cmd_idx]:
return FILL_RULE_OFFSET
elif cmd_idx in type_params and param_idx in type_params[cmd_idx]:
return TYPE_OFFSET
elif cmd_idx in text_range_units and param_idx in text_range_units[cmd_idx]:
return TEXT_RANGE_UNITS_OFFSET
elif cmd_idx in inv_params and param_idx in inv_params[cmd_idx]:
return INV_OFFSET
elif cmd_idx in mode_params and param_idx in mode_params[cmd_idx]:
return MODE_OFFSET
elif cmd_idx in text_shape_type and param_idx in text_shape_type[cmd_idx]:
return TEXT_SHAPE_TYPE_OFFSET
elif cmd_idx in text_random and param_idx in text_random[cmd_idx]:
return TEXT_RANDOM_OFFSET
elif cmd_idx in color_points_params and param_idx in color_points_params[cmd_idx]:
return COLOR_POINTS_OFFSET
elif cmd_idx in round_params and param_idx in round_params[cmd_idx]:
return ROUND_OFFSET
elif cmd_idx in radius_params and param_idx in radius_params[cmd_idx]:
return RADIUS_OFFSET
elif cmd_idx in frequency_params and param_idx in frequency_params[cmd_idx]:
return FREQUENCY_OFFSET
elif cmd_idx in speed_params and param_idx in speed_params[cmd_idx]:
return SPEED_OFFSET
elif cmd_idx in font_params and param_idx in font_params[cmd_idx]:
return FONT_OFFSET
elif cmd_idx in color_params and param_idx in color_params[cmd_idx]:
return COLOR_OFFSET
elif cmd_idx in line_cap_params and param_idx in line_cap_params[cmd_idx]:
return LINE_CAP_OFFSET
elif cmd_idx in line_join_params and param_idx in line_join_params[cmd_idx]:
return LINE_JOIN_OFFSET
elif cmd_idx in miter_limit_params and param_idx in miter_limit_params[cmd_idx]:
return MITER_LIMIT_OFFSET
elif cmd_idx in effect_params and param_idx in effect_params[cmd_idx]:
return EFFECT_OFFSET
elif cmd_idx in opacity_params and param_idx in opacity_params[cmd_idx]:
return OPACITY_OFFSET
else:
return 0 # Default to no offset if not found
LottieTensor._OFFSET_CACHE[cache_key] = offset
return offset
@staticmethod
def get_command_param_indices(cmd_idx: int) -> List[int]:
"""
Get the list of parameter indices for a command in their fixed order.
Returns empty list for commands without parameters.
"""
param_orders = {
LottieTensor.CMD_ANIMATION: [
LottieTensor.Index.Animation.FR,
LottieTensor.Index.Animation.IP,
LottieTensor.Index.Animation.OP,
LottieTensor.Index.Animation.W,
LottieTensor.Index.Animation.H,
LottieTensor.Index.Animation.DDD
],
LottieTensor.CMD_LAYER: [
LottieTensor.Index.Layer.INDEX,
LottieTensor.Index.Layer.IN_POINT,
LottieTensor.Index.Layer.OUT_POINT,
LottieTensor.Index.Layer.START_TIME,
LottieTensor.Index.Layer.DDD,
LottieTensor.Index.Layer.HD,
LottieTensor.Index.Layer.CP,
LottieTensor.Index.Layer.HAS_MASK,
LottieTensor.Index.Layer.AO,
LottieTensor.Index.Layer.TT,
LottieTensor.Index.Layer.TP,
LottieTensor.Index.Layer.TD,
LottieTensor.Index.Layer.CT
],
LottieTensor.CMD_NULL_LAYER: [
LottieTensor.Index.NullLayer.INDEX,
LottieTensor.Index.NullLayer.IN_POINT,
LottieTensor.Index.NullLayer.OUT_POINT,
LottieTensor.Index.NullLayer.START_TIME,
LottieTensor.Index.NullLayer.CT,
LottieTensor.Index.NullLayer.HD,
LottieTensor.Index.NullLayer.HAS_MASK,
LottieTensor.Index.NullLayer.AO,
LottieTensor.Index.NullLayer.TT,
LottieTensor.Index.NullLayer.TP,
LottieTensor.Index.NullLayer.TD,
LottieTensor.Index.NullLayer.CP
],
LottieTensor.CMD_PRECOMP_LAYER: [
LottieTensor.Index.PrecompLayer.INDEX,
LottieTensor.Index.PrecompLayer.IN_POINT,
LottieTensor.Index.PrecompLayer.OUT_POINT,
LottieTensor.Index.PrecompLayer.START_TIME,
LottieTensor.Index.PrecompLayer.W,
LottieTensor.Index.PrecompLayer.H,
LottieTensor.Index.PrecompLayer.CT,
LottieTensor.Index.PrecompLayer.HAS_MASK,
LottieTensor.Index.PrecompLayer.AO,
LottieTensor.Index.PrecompLayer.TT,
LottieTensor.Index.PrecompLayer.TP,
LottieTensor.Index.PrecompLayer.TD,
LottieTensor.Index.PrecompLayer.DDD,
LottieTensor.Index.PrecompLayer.HD,
LottieTensor.Index.PrecompLayer.CP
],
LottieTensor.CMD_TEXT_LAYER: [
LottieTensor.Index.TextLayer.INDEX,
LottieTensor.Index.TextLayer.IN_POINT,
LottieTensor.Index.TextLayer.OUT_POINT,
LottieTensor.Index.TextLayer.START_TIME,
LottieTensor.Index.TextLayer.HAS_MASK
],
LottieTensor.CMD_SOLID_LAYER: [
LottieTensor.Index.SolidLayer.INDEX,
LottieTensor.Index.SolidLayer.IN_POINT,
LottieTensor.Index.SolidLayer.OUT_POINT,
LottieTensor.Index.SolidLayer.START_TIME,
LottieTensor.Index.SolidLayer.WIDTH,
LottieTensor.Index.SolidLayer.HEIGHT,
LottieTensor.Index.SolidLayer.HAS_MASK,
LottieTensor.Index.SolidLayer.COLOR_R,
LottieTensor.Index.SolidLayer.COLOR_G,
LottieTensor.Index.SolidLayer.COLOR_B,
LottieTensor.Index.SolidLayer.COLOR_A
],
LottieTensor.CMD_TRANSFORM: [],
LottieTensor.CMD_POSITION: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X,
LottieTensor.Index.Transform.Y,
LottieTensor.Index.Transform.Z
],
LottieTensor.CMD_POSITION_X: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_POSITION_Y: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_POSITION_Z: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_SCALE: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X,
LottieTensor.Index.Transform.Y,
LottieTensor.Index.Transform.Z
],
LottieTensor.CMD_ROTATION: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_OPACITY: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X
],
LottieTensor.CMD_ANCHOR: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X,
LottieTensor.Index.Transform.Y,
LottieTensor.Index.Transform.Z
],
LottieTensor.CMD_KEYFRAME: [
LottieTensor.Index.Keyframe.T,
LottieTensor.Index.Keyframe.S1,
LottieTensor.Index.Keyframe.S2,
LottieTensor.Index.Keyframe.S3,
LottieTensor.Index.Keyframe.I_X,
LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X,
LottieTensor.Index.Keyframe.O_Y,
LottieTensor.Index.Keyframe.TO1,
LottieTensor.Index.Keyframe.TO2,
LottieTensor.Index.Keyframe.TO3,
LottieTensor.Index.Keyframe.TI1,
LottieTensor.Index.Keyframe.TI2,
LottieTensor.Index.Keyframe.TI3,
LottieTensor.Index.Keyframe.I_X2,
LottieTensor.Index.Keyframe.I_X3,
LottieTensor.Index.Keyframe.I_Y2,
LottieTensor.Index.Keyframe.I_Y3,
LottieTensor.Index.Keyframe.O_X2,
LottieTensor.Index.Keyframe.O_X3,
LottieTensor.Index.Keyframe.O_Y2,
LottieTensor.Index.Keyframe.O_Y3,
LottieTensor.Index.Keyframe.H_FLAG,
LottieTensor.Index.Keyframe.E1,
LottieTensor.Index.Keyframe.E2,
LottieTensor.Index.Keyframe.E3
],
LottieTensor.CMD_GROUP: [
LottieTensor.Index.Group.IX,
LottieTensor.Index.Group.CIX,
LottieTensor.Index.Group.BM,
LottieTensor.Index.Group.HD,
LottieTensor.Index.Group.NP
],
LottieTensor.CMD_PATH: [
LottieTensor.Index.Path.IX,
LottieTensor.Index.Path.IND,
LottieTensor.Index.Path.KS_IX,
LottieTensor.Index.Path.CLOSED,
LottieTensor.Index.Path.HD,
LottieTensor.Index.Path.ANIMATED
],
LottieTensor.CMD_POINT: [
LottieTensor.Index.Point.X,
LottieTensor.Index.Point.Y,
LottieTensor.Index.Point.IN_X,
LottieTensor.Index.Point.IN_Y,
LottieTensor.Index.Point.OUT_X,
LottieTensor.Index.Point.OUT_Y
],
LottieTensor.CMD_FILL: [
LottieTensor.Index.Fill.R,
LottieTensor.Index.Fill.G,
LottieTensor.Index.Fill.B,
LottieTensor.Index.Fill.COLOR_DIM,
LottieTensor.Index.Fill.HAS_C_A,
LottieTensor.Index.Fill.HAS_C_IX,
LottieTensor.Index.Fill.C_IX,
LottieTensor.Index.Fill.BM,
LottieTensor.Index.Fill.FILL_RULE,
LottieTensor.Index.Fill.OPACITY,
LottieTensor.Index.Fill.COLOR_ANIMATED,
LottieTensor.Index.Fill.OPACITY_ANIMATED,
LottieTensor.Index.Fill.HAS_O_A,
LottieTensor.Index.Fill.HAS_O_IX,
LottieTensor.Index.Fill.O_IX
],
LottieTensor.CMD_STROKE: [
LottieTensor.Index.Stroke.R,
LottieTensor.Index.Stroke.G,
LottieTensor.Index.Stroke.B,
LottieTensor.Index.Stroke.COLOR_DIM,
LottieTensor.Index.Stroke.HAS_C_A,
LottieTensor.Index.Stroke.HAS_C_IX,
LottieTensor.Index.Stroke.C_IX,
LottieTensor.Index.Stroke.BM,
LottieTensor.Index.Stroke.LC,
LottieTensor.Index.Stroke.LJ,
LottieTensor.Index.Stroke.ML,
LottieTensor.Index.Stroke.WIDTH_ANIMATED,
LottieTensor.Index.Stroke.COLOR_ANIMATED,
LottieTensor.Index.Stroke.A
],
LottieTensor.CMD_TRANSFORM_SHAPE: [
LottieTensor.Index.TransformShape.POSITION_X,
LottieTensor.Index.TransformShape.POSITION_Y,
LottieTensor.Index.TransformShape.SCALE_X,
LottieTensor.Index.TransformShape.SCALE_Y,
LottieTensor.Index.TransformShape.ROTATION,
LottieTensor.Index.TransformShape.OPACITY,
LottieTensor.Index.TransformShape.ANCHOR_X,
LottieTensor.Index.TransformShape.ANCHOR_Y,
LottieTensor.Index.TransformShape.SKEW,
LottieTensor.Index.TransformShape.SKEW_AXIS,
LottieTensor.Index.TransformShape.HD
],
LottieTensor.CMD_RECT: [
LottieTensor.Index.Rect.HD,
LottieTensor.Index.Rect.D
],
LottieTensor.CMD_ELLIPSE: [],
LottieTensor.CMD_BEZIER: [
LottieTensor.Index.Bezier.CLOSED
],
LottieTensor.CMD_SIZE: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X, # 修改：从 TwoValues.VALUE1 改为 Transform.X
LottieTensor.Index.Transform.Y # 修改：从 TwoValues.VALUE2 改为 Transform.Y
],
LottieTensor.CMD_RECT_SIZE: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X, # 修改
LottieTensor.Index.Transform.Y # 修改
],
LottieTensor.CMD_ELLIPSE_SIZE: [
LottieTensor.Index.Transform.ANIMATED,
LottieTensor.Index.Transform.X, # 修改
LottieTensor.Index.Transform.Y # 修改
],
LottieTensor.CMD_ROUNDED: [
LottieTensor.Index.SingleValue.VALUE,
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_RECT_ROUNDED: [
LottieTensor.Index.SingleValue.ANIMATED,
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TRIM: [
LottieTensor.Index.Trim.IX
],
LottieTensor.CMD_START: [
LottieTensor.Index.SingleValue.ANIMATED,
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_END: [
LottieTensor.Index.SingleValue.ANIMATED,
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OFFSET: [
LottieTensor.Index.SingleValue.ANIMATED,
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_PARENT: [
LottieTensor.Index.Parent.PARENT_INDEX
],
LottieTensor.CMD_REFERENCE_ID: list(range(11)), # 11 tokens
LottieTensor.CMD_DIMENSIONS: [
LottieTensor.Index.Dimensions.WIDTH,
LottieTensor.Index.Dimensions.HEIGHT
],
LottieTensor.CMD_ASSET: list(range(12)), # FR + 10 tokens + count
LottieTensor.CMD_TEXT_KEYFRAME: list(range(47)), # All text keyframe params
LottieTensor.CMD_FONT: list(range(23)), # All font params
LottieTensor.CMD_CHAR: list(range(35)), # All char params
LottieTensor.CMD_WIDTH_KEYFRAME: [
LottieTensor.Index.WidthKeyframe.T,
LottieTensor.Index.WidthKeyframe.S,
LottieTensor.Index.WidthKeyframe.I_X,
LottieTensor.Index.WidthKeyframe.I_Y,
LottieTensor.Index.WidthKeyframe.O_X,
LottieTensor.Index.WidthKeyframe.O_Y
],
LottieTensor.CMD_COLOR_KEYFRAME: [
LottieTensor.Index.Keyframe.T,
LottieTensor.Index.Keyframe.S1,
LottieTensor.Index.Keyframe.S2,
LottieTensor.Index.Keyframe.S3,
LottieTensor.Index.Keyframe.E1,
LottieTensor.Index.Keyframe.I_X,
LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X,
LottieTensor.Index.Keyframe.O_Y
],
LottieTensor.CMD_OPACITY_KEYFRAME: [
LottieTensor.Index.Keyframe.T,
LottieTensor.Index.Keyframe.S1,
LottieTensor.Index.Keyframe.I_X,
LottieTensor.Index.Keyframe.I_Y,
LottieTensor.Index.Keyframe.O_X,
LottieTensor.Index.Keyframe.O_Y
],
LottieTensor.CMD_OPACITY_ANIMATED: [],
LottieTensor.CMD_TM: [
LottieTensor.Index.Tm.A
],
LottieTensor.CMD_VALUE: [
LottieTensor.Index.Value.VALUE
],
LottieTensor.CMD_SKEW: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_SKEW_AXIS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_STAR: [
LottieTensor.Index.Star.D,
LottieTensor.Index.Star.SY
],
LottieTensor.CMD_INNER_RADIUS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OUTER_RADIUS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_INNER_ROUNDNESS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_OUTER_ROUNDNESS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_POINTS_STAR: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_STAR_ROTATION: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_MULTIPLE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_REPEATER: [
LottieTensor.Index.Repeater.IX
],
LottieTensor.CMD_COPIES: [
LottieTensor.Index.SingleValue.VALUE,
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_REPEATER_OFFSET: [
LottieTensor.Index.SingleValue.VALUE,
LottieTensor.Index.SingleValue.IX
],
LottieTensor.CMD_COMPOSITE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_REPEATER_TRANSFORM: [],
LottieTensor.CMD_TR_P_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_A_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_SCALE: [
LottieTensor.Index.TwoValues.VALUE1,
LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_TR_S_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_R_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_SO_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_TR_EO_IX: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_MORE_OPTIONS: [
LottieTensor.Index.MoreOptions.G,
LottieTensor.Index.MoreOptions.ALIGNMENT_A,
LottieTensor.Index.MoreOptions.ALIGNMENT_K1,
LottieTensor.Index.MoreOptions.ALIGNMENT_K2,
LottieTensor.Index.MoreOptions.ALIGNMENT_IX
],
LottieTensor.CMD_GRADIENT_FILL: [],
LottieTensor.CMD_START_POINT: [
LottieTensor.Index.TwoValues.VALUE1,
LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_END_POINT: [
LottieTensor.Index.TwoValues.VALUE1,
LottieTensor.Index.TwoValues.VALUE2
],
LottieTensor.CMD_GRADIENT_TYPE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_HIGHLIGHT_LENGTH: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_HIGHLIGHT_ANGLE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_ORIGINAL_COLORS: list(range(48)), # All color values + count
LottieTensor.CMD_COLOR_POINTS: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_GRADIENT_STROKE: [],
LottieTensor.CMD_WIDTH: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_LINE_CAP: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_LINE_JOIN: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_MITER_LIMIT: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_ML2: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_COLOR: [
LottieTensor.Index.Color.INDEX,
LottieTensor.Index.Color.R,
LottieTensor.Index.Color.G,
LottieTensor.Index.Color.B
],
LottieTensor.CMD_EFFECT: [
LottieTensor.Index.Effect.TYPE,
LottieTensor.Index.Effect.INDEX,
LottieTensor.Index.Effect.NP,
LottieTensor.Index.Effect.ENABLED
],
LottieTensor.CMD_LAYER_EFFECT: [
LottieTensor.Index.LayerEffect.INDEX,
LottieTensor.Index.LayerEffect.VALUE
],
LottieTensor.CMD_DROPDOWN: [
LottieTensor.Index.Dropdown.INDEX,
LottieTensor.Index.Dropdown.VALUE
],
LottieTensor.CMD_NO_VALUE: [
LottieTensor.Index.NO_VALUE.INDEX,
LottieTensor.Index.NO_VALUE.VALUE
],
LottieTensor.CMD_IGNORED: [
LottieTensor.Index.Ignored.INDEX,
LottieTensor.Index.Ignored.VALUE
],
LottieTensor.CMD_SLIDER: [
LottieTensor.Index.Slider.INDEX,
LottieTensor.Index.Slider.VALUE
],
LottieTensor.CMD_FILL_RULE: [
LottieTensor.Index.SingleValue.VALUE
],
LottieTensor.CMD_MERGE: [],
LottieTensor.CMD_MERGE_MODE: [
LottieTensor.Index.MergeMode.MODE
],
LottieTensor.CMD_MASKS_PROPERTIES: [],
LottieTensor.CMD_MASK: [
LottieTensor.Index.Mask.INDEX,
LottieTensor.Index.Mask.INV,
LottieTensor.Index.Mask.MODE
],
LottieTensor.CMD_MASK_PT: [
LottieTensor.Index.MaskPt.A,
LottieTensor.Index.MaskPt.IX
],
LottieTensor.CMD_MASK_PT_K: [],
LottieTensor.CMD_MASK_PT_K_C: [
LottieTensor.Index.MaskPtK.C
],
LottieTensor.CMD_MASK_PT_K_I: list(range(21)), # V1-V20 + COUNT
LottieTensor.CMD_MASK_PT_K_O: list(range(21)),
LottieTensor.CMD_MASK_PT_K_V: list(range(21)),
LottieTensor.CMD_MASK_O: [
LottieTensor.Index.MaskO.A,
LottieTensor.Index.MaskO.K,
LottieTensor.Index.MaskO.IX
],
LottieTensor.CMD_MASK_X: [
LottieTensor.Index.MaskX.A,
LottieTensor.Index.MaskX.K,
LottieTensor.Index.MaskX.IX
],
LottieTensor.CMD_MASK_PT_K_ARRAY: [],
LottieTensor.CMD_MASK_PT_KEYFRAME: [
LottieTensor.Index.MaskPtKeyframe.INDEX,
LottieTensor.Index.MaskPtKeyframe.T
],
LottieTensor.CMD_MASK_PT_KF_I: [
LottieTensor.Index.MaskPtKfI.X,
LottieTensor.Index.MaskPtKfI.Y
],
LottieTensor.CMD_MASK_PT_KF_O: [
LottieTensor.Index.MaskPtKfO.X,
LottieTensor.Index.MaskPtKfO.Y
],
LottieTensor.CMD_MASK_PT_KF_S: [],
LottieTensor.CMD_MASK_PT_KF_SHAPE: [
LottieTensor.Index.MaskPtKfShape.INDEX,
LottieTensor.Index.MaskPtKfShape.C
],
LottieTensor.CMD_MASK_PT_KF_SHAPE_I: list(range(21)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_O: list(range(21)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_V: list(range(21)),
LottieTensor.CMD_TR_POSITION: [
LottieTensor.Index.TrPosition.X,
LottieTensor.Index.TrPosition.Y
],
LottieTensor.CMD_TR_ANCHOR: [
LottieTensor.Index.TrAnchor.X,
LottieTensor.Index.TrAnchor.Y
],
LottieTensor.CMD_TR_ROTATION: [
LottieTensor.Index.TrRotation.VALUE
],
LottieTensor.CMD_TR_START_OPACITY: [
LottieTensor.Index.TrStartOpacity.VALUE
],
LottieTensor.CMD_TR_END_OPACITY: [
LottieTensor.Index.TrEndOpacity.VALUE
],
LottieTensor.CMD_ZIG_ZAG: [
LottieTensor.Index.ZigZag.IX
],
LottieTensor.CMD_FREQUENCY: [
LottieTensor.Index.Frequency.VALUE
],
LottieTensor.CMD_AMPLITUDE: [
LottieTensor.Index.Amplitude.VALUE
],
LottieTensor.CMD_POINT_TYPE: [
LottieTensor.Index.PointType.VALUE
],
LottieTensor.CMD_ANIMATORS: [],
LottieTensor.CMD_ANIMATOR: [],
LottieTensor.CMD_RANGE_SELECTOR: [
LottieTensor.Index.RangeSelector.T,
LottieTensor.Index.RangeSelector.R,
LottieTensor.Index.RangeSelector.B,
LottieTensor.Index.RangeSelector.SH,
LottieTensor.Index.RangeSelector.RN
],
LottieTensor.CMD_RANGE_START: [
LottieTensor.Index.RangeStart.A
],
LottieTensor.CMD_RANGE_START_KEYFRAME: [
LottieTensor.Index.RangeStartKeyframe.T,
LottieTensor.Index.RangeStartKeyframe.S,
LottieTensor.Index.RangeStartKeyframe.I_X,
LottieTensor.Index.RangeStartKeyframe.I_Y,
LottieTensor.Index.RangeStartKeyframe.O_X,
LottieTensor.Index.RangeStartKeyframe.O_Y
],
LottieTensor.CMD_AMOUNT: [
LottieTensor.Index.Amount.A,
LottieTensor.Index.Amount.K,
LottieTensor.Index.Amount.IX
],
LottieTensor.CMD_MAX_EASE: [
LottieTensor.Index.MaxEase.A,
LottieTensor.Index.MaxEase.K,
LottieTensor.Index.MaxEase.IX
],
LottieTensor.CMD_MIN_EASE: [
LottieTensor.Index.MinEase.A,
LottieTensor.Index.MinEase.K,
LottieTensor.Index.MinEase.IX
],
LottieTensor.CMD_ANIMATOR_PROPERTIES: [],
LottieTensor.CMD_RADIUS: [
LottieTensor.Index.Radius.VALUE
],
LottieTensor.CMD_RANGE_END: [
LottieTensor.Index.RangeEnd.A
],
LottieTensor.CMD_RANGE_END_KEYFRAME: [
LottieTensor.Index.RangeEndKeyframe.T,
LottieTensor.Index.RangeEndKeyframe.S,
LottieTensor.Index.RangeEndKeyframe.I_X,
LottieTensor.Index.RangeEndKeyframe.I_Y,
LottieTensor.Index.RangeEndKeyframe.O_X,
LottieTensor.Index.RangeEndKeyframe.O_Y
],
LottieTensor.CMD_RANGE_OFFSET: [
LottieTensor.Index.Amount.A,
LottieTensor.Index.Amount.K,
LottieTensor.Index.Amount.IX
],
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: [
LottieTensor.Index.RangeOffsetKeyframe.T,
LottieTensor.Index.RangeOffsetKeyframe.S,
LottieTensor.Index.RangeOffsetKeyframe.I_X,
LottieTensor.Index.RangeOffsetKeyframe.I_Y,
LottieTensor.Index.RangeOffsetKeyframe.O_X,
LottieTensor.Index.RangeOffsetKeyframe.O_Y
],
LottieTensor.CMD_S_M: [
LottieTensor.Index.SM.A,
LottieTensor.Index.SM.K,
LottieTensor.Index.SM.IX
],
LottieTensor.CMD_OPACITY_ANIMATORS: [
LottieTensor.Index.OpacityAnimators.A,
LottieTensor.Index.OpacityAnimators.K,
LottieTensor.Index.OpacityAnimators.IX
],
LottieTensor.CMD_SCALE_ANIMATORS: [
LottieTensor.Index.ScaleAnimators.A,
LottieTensor.Index.ScaleAnimators.K_X,
LottieTensor.Index.ScaleAnimators.K_Y,
LottieTensor.Index.ScaleAnimators.K_Z,
LottieTensor.Index.ScaleAnimators.IX
],
LottieTensor.CMD_ROTATION_ANIMATORS: [
LottieTensor.Index.RotationAnimators.A,
LottieTensor.Index.RotationAnimators.K,
LottieTensor.Index.RotationAnimators.IX
],
LottieTensor.CMD_POSITION_ANIMATORS: [
LottieTensor.Index.PositionAnimators.A,
LottieTensor.Index.PositionAnimators.K_X,
LottieTensor.Index.PositionAnimators.K_Y,
LottieTensor.Index.PositionAnimators.K_Z,
LottieTensor.Index.PositionAnimators.IX
],
LottieTensor.CMD_TRACKING_ANIMATORS: [
LottieTensor.Index.TrackingAnimators.A,
LottieTensor.Index.TrackingAnimators.K,
LottieTensor.Index.TrackingAnimators.IX
],
LottieTensor.CMD_DASHES: [],
LottieTensor.CMD_DASH: [
LottieTensor.Index.Dash.TYPE,
LottieTensor.Index.Dash.LENGTH,
LottieTensor.Index.Dash.V_IX
],
LottieTensor.CMD_DASH_ANIMATED: [
LottieTensor.Index.DashAnimated.TYPE,
LottieTensor.Index.DashAnimated.V_IX
],
LottieTensor.CMD_DASH_KEYFRAME: [
LottieTensor.Index.DashKeyframe.T,
LottieTensor.Index.DashKeyframe.S,
LottieTensor.Index.DashKeyframe.I_X,
LottieTensor.Index.DashKeyframe.I_Y,
LottieTensor.Index.DashKeyframe.O_X,
LottieTensor.Index.DashKeyframe.O_Y
],
LottieTensor.CMD_DASH_OFFSET: [
LottieTensor.Index.DashOffset.O
],
LottieTensor.CMD_WIDTH_ANIMATED: [],
# All end commands have empty param lists
LottieTensor.CMD_POSITION_END: [],
LottieTensor.CMD_SCALE_END: [],
LottieTensor.CMD_ROTATION_END: [],
LottieTensor.CMD_OPACITY_END: [],
LottieTensor.CMD_ANCHOR_END: [],
LottieTensor.CMD_GROUP_END: [],
LottieTensor.CMD_TRANSFORM_END: [],
LottieTensor.CMD_LAYER_END: [],
LottieTensor.CMD_PATH_END: [],
LottieTensor.CMD_RECT_END: [],
LottieTensor.CMD_ELLIPSE_END: [],
LottieTensor.CMD_STAR_END: [],
LottieTensor.CMD_TRIM_END: [],
LottieTensor.CMD_REPEATER_END: [],
LottieTensor.CMD_REPEATER_TRANSFORM_END: [],
LottieTensor.CMD_GRADIENT_FILL_END: [],
LottieTensor.CMD_GRADIENT_STROKE_END: [],
LottieTensor.CMD_MERGE_END: [],
LottieTensor.CMD_ROUNDED_CORNERS_END: [],
LottieTensor.CMD_TWIST_END: [],
LottieTensor.CMD_BEZIER_END: [],
LottieTensor.CMD_TEXT_LAYER_END: [],
LottieTensor.CMD_TEXT_DATA_END: [],
LottieTensor.CMD_SOLID_LAYER_END: [],
LottieTensor.CMD_NULL_LAYER_END: [],
LottieTensor.CMD_PRECOMP_LAYER_END: [],
LottieTensor.CMD_POSITION_X_END: [],
LottieTensor.CMD_POSITION_Y_END: [],
LottieTensor.CMD_POSITION_Z_END: [],
LottieTensor.CMD_SCALE_X_END: [],
LottieTensor.CMD_SCALE_Y_END: [],
LottieTensor.CMD_SCALE_Z_END: [],
LottieTensor.CMD_ROTATION_X_END: [],
LottieTensor.CMD_ROTATION_Y_END: [],
LottieTensor.CMD_ROTATION_Z_END: [],
LottieTensor.CMD_EFFECTS_END: [],
LottieTensor.CMD_EFFECT_END: [],
LottieTensor.CMD_KEYFRAME_END: [],
LottieTensor.CMD_WIDTH_ANIMATED_END: [],
LottieTensor.CMD_FONTS_END: [],
LottieTensor.CMD_CHARS_END: [],
LottieTensor.CMD_CHAR_END: [],
LottieTensor.CMD_CHAR_SHAPES_END: [],
LottieTensor.CMD_TEXT_KEYFRAMES_END: [],
LottieTensor.CMD_TEXT_DOC_END: [],
LottieTensor.CMD_MORE_OPTIONS_END: [],
LottieTensor.CMD_OPACITY_ANIMATED_END: [],
LottieTensor.CMD_MASKS_PROPERTIES_END: [],
LottieTensor.CMD_MASK_END: [],
LottieTensor.CMD_MASK_PT_END: [],
LottieTensor.CMD_MASK_PT_K_END: [],
LottieTensor.CMD_TM_END: [],
LottieTensor.CMD_MASK_PT_K_ARRAY_END: [],
LottieTensor.CMD_MASK_PT_KEYFRAME_END: [],
LottieTensor.CMD_MASK_PT_KF_S_END: [],
LottieTensor.CMD_MASK_PT_KF_SHAPE_END: [],
LottieTensor.CMD_VALUE_END: [],
LottieTensor.CMD_ZIG_ZAG_END: [],
LottieTensor.CMD_ANIMATORS_END: [],
LottieTensor.CMD_ANIMATOR_END: [],
LottieTensor.CMD_RANGE_SELECTOR_END: [],
LottieTensor.CMD_RANGE_START_END: [],
LottieTensor.CMD_RANGE_END_END: [],
LottieTensor.CMD_END_END: [],
LottieTensor.CMD_START_END: [],
LottieTensor.CMD_OFFSET_END: [],
LottieTensor.CMD_RANGE_OFFSET_END: [],
LottieTensor.CMD_SCALE_ANIMATORS_END: [],
LottieTensor.CMD_ROTATION_ANIMATORS_END: [],
LottieTensor.CMD_POSITION_ANIMATORS_END: [],
LottieTensor.CMD_OPACITY_ANIMATORS_END: [],
LottieTensor.CMD_COLOR_ANIMATED_END: [],
LottieTensor.CMD_DASHES_END: [],
LottieTensor.CMD_DASH_ANIMATED_END: [],
LottieTensor.CMD_SIZE_END: [],
LottieTensor.CMD_RECT_ROUNDED_END: [],
LottieTensor.CMD_ANIMATOR_PROPERTIES_END: [],
LottieTensor.CMD_ASSET_END: [],
LottieTensor.CMD_EFFECTS: [],
LottieTensor.CMD_FONTS: [],
LottieTensor.CMD_CHARS: [],
LottieTensor.CMD_CHAR_SHAPES: [],
LottieTensor.CMD_TEXT_KEYFRAMES: [],
LottieTensor.CMD_TEXT_DATA: [],
LottieTensor.CMD_DOCUMENT: [],
LottieTensor.CMD_TEXT_DOC: [],
}
# Commands without parameters
empty_param_cmds = {k for k, v in param_orders.items() if not v}
return param_orders.get(cmd_idx, [])
@staticmethod
def get_vocab_range_for_offset(offset: int) -> tuple:
"""Get the vocabulary range (start, end) for a given offset."""
vocab_ranges = {
0: (1, 151643), # NO_OFFSET (tokenizer tokens)
155000: (153000, 157000), # TIME_OFFSET: -2000 to 2000
159100: (157100, 161100), # SPACE_OFFSET: -2000 to 2000
161200: (161200, 161220), # AMPLITUDE_OFFSET: 0 to 20
161300: (161300, 165300), # ANCHOR_OFFSET: -2000 to 2000
165400: (165400, 165401), # ANIMATED_OFFSET: 0 to 1
165402: (165402, 165403), # H_FLAG_OFFSET: 0 to 1
165404: (165404, 165405), # OFFSET_VAL_OFFSET: 0 to 1
165406: (165406, 165408), # CA_OFFSET: 0 to 2
165409: (165409, 165415), # JUSTIFY_OFFSET: 0 to 6
165416: (165416, 166016), # TEXT_TRACKING_OFFSET: -100 to 500
166017: (166017, 166018), # HAS_STROKE_COLOR_OFFSET: 0 to 1
166019: (166019, 167019), # IX_OFFSET: 0 to 1000
167020: (167020, 167040), # BM_OFFSET: 0 to 20
167041: (167041, 167042), # CLOSED_OFFSET: 0 to 1
167043: (167043, 167048), # DIRECTION_OFFSET: 0 to 5
167049: (167049, 167054), # STAR_TYPE_OFFSET: 0 to 5
167055: (167055, 167060), # MULTIPLE_OFFSET: 0 to 5
167061: (167061, 167066), # COMPOSITE_OFFSET: 0 to 5
167067: (167067, 167117), # SKEW_OFFSET: -25 to 25
167118: (167118, 167168), # SKEW_AXIS_OFFSET: -25 to 25
167169: (167169, 170169), # SCALE_OFFSET: -1000 to 2000
170170: (170170, 171610), # ROTATION_OFFSET: -720 to 720
171611: (171611, 171811), # EASE_OFFSET: -100 to 100
171812: (171812, 171912), # SMOOTH_OFFSET: 0 to 100
171913: (171913, 172013), # TRACKING_OFFSET: -50 to 50
172014: (172014, 173014), # INDEX_OFFSET: 0 to 1000
173015: (173015, 173016), # DDD_OFFSET: 0 to 1
173017: (173017, 173018), # HD_OFFSET: 0 to 1
173019: (173019, 173069), # CP_OFFSET: 0 to 50
173070: (173070, 173071), # HAS_MASK_OFFSET: 0 to 1
173072: (173072, 173073), # AO_OFFSET: 0 to 1
173074: (173074, 173079), # TT_OFFSET: 0 to 5
173080: (173080, 173180), # TP_OFFSET: 0 to 100
173181: (173181, 173183), # TD_OFFSET: 0 to 2
173184: (173184, 173185), # CT_OFFSET: 0 to 1
173186: (173186, 173686), # NUMBER_OFFSET: 0 to 500
173687: (173687, 173697), # DIM_OFFSET: 0 to 10
173698: (173698, 173699), # HAS_C_A_OFFSET: 0 to 1
173700: (173700, 173701), # HAS_C_IX_OFFSET: 0 to 1
173702: (173702, 173703), # HAS_O_A_OFFSET: 0 to 1
173704: (173704, 173705), # HAS_O_IX_OFFSET: 0 to 1
173706: (173706, 173710), # FILL_RULE_OFFSET: 0 to 4
173711: (173711, 173751), # TYPE_OFFSET: 0 to 40
173752: (173752, 173762), # TEXT_RANGE_UNITS_OFFSET: 0 to 10
173763: (173763, 173764), # INV_OFFSET: 0 to 1
173765: (173765, 173775), # MODE_OFFSET: 0 to 10
173776: (173776, 173786), # TEXT_SHAPE_TYPE_OFFSET: 0 to 10
173787: (173787, 173788), # TEXT_RANDOM_OFFSET: 0 to 1
173789: (173789, 173839), # COLOR_POINTS_OFFSET: 0 to 50
173840: (173840, 174940), # ROUND_OFFSET: -100 to 1000
174941: (174941, 175241), # RADIUS_OFFSET: 0 to 300
175242: (175242, 175392), # FREQUENCY_OFFSET: 0 to 150
175393: (175393, 177393), # SPEED_OFFSET: -1000 to 1000
177394: (177394, 179494), # FONT_OFFSET: -100 to 2000
179495: (179495, 179750), # COLOR_OFFSET: 0 to 255
179752: (179752, 179754), # LINE_CAP_OFFSET: 1 to 3
179757: (179757, 179759), # LINE_JOIN_OFFSET: 1 to 3
179760: (179760, 179860), # MITER_LIMIT_OFFSET: 0 to 100
179861: (179861, 181111), # EFFECT_OFFSET: -250 to 1000
181112: (181112, 181212), # OPACITY_OFFSET: 0 to 100
181300: (181300, 191300), # WIDTH_VALUE_OFFSET: 0 to 10000 (新增)
}
return vocab_ranges.get(offset, (0, 0))
@staticmethod
def _find_nearest_layer_end(flattened: List[int], max_length: int, command_offset: int) -> int:
"""
在flattened list中查找最接近max_length的layer end位置
智能截断规则：
1. 从max_length位置向前搜索，找最近的layer end
2. 必须确保至少有ANIMATION命令和一个完整的layer
3. layer end包括: LAYER_END, PRECOMP_LAYER_END, TEXT_LAYER_END, NULL_LAYER_END, SOLID_LAYER_END
4. 如果找不到合适的位置，返回-1（表示放弃样本）
Args:
flattened: 扁平化的token列表
max_length: 目标最大长度
command_offset: 命令token的offset (151936)
Returns:
最近的layer end位置（截断到这里），如果找不到返回-1
"""
# Layer end命令集合
LAYER_END_CMDS = {
LottieTensor.CMD_LAYER_END, # 27
LottieTensor.CMD_PRECOMP_LAYER_END, # 46
LottieTensor.CMD_TEXT_LAYER_END, # 90
LottieTensor.CMD_NULL_LAYER_END, # 44
LottieTensor.CMD_SOLID_LAYER_END, # 95
}
# 向前搜索范围：从max_length向前最多搜索2000个token
# 2000个token大约能包含1-2个完整的layer
search_start = max(0, max_length - 2000)
best_pos = -1
# 从max_length位置向前搜索
for i in range(min(max_length - 1, len(flattened) - 1), search_start - 1, -1):
token = flattened[i]
# 检查是否是命令token
if token >= command_offset and token < command_offset + len(LottieTensor.COMMANDS):
cmd_idx = token - command_offset
if cmd_idx in LAYER_END_CMDS:
# 找到layer end，截断点是这个token之后
candidate_pos = i + 1
# 验证截断后的序列是否完整（必须有ANIMATION和至少一个layer）
if LottieTensor._validate_truncated_sequence(flattened[:candidate_pos], command_offset):
best_pos = candidate_pos
break
return best_pos
@staticmethod
def _validate_truncated_sequence(flattened: List[int], command_offset: int) -> bool:
"""
验证截断后的序列是否完整有效
要求：
1. 必须有ANIMATION命令
2. 必须至少有一个完整的layer（有layer start和layer end配对）
3. layers不能为空
4. 【新增】必须有主layers（不能只有assets中的layers）
Args:
flattened: 截断后的token列表
command_offset: 命令token的offset
Returns:
是否是有效的序列
"""
has_animation = False
layer_count = 0
asset_depth = 0 # 跟踪是否在asset内部
main_layer_count = 0 # 主layers计数（不在asset内的layer）
# Layer start和end命令
LAYER_START_CMDS = {
LottieTensor.CMD_LAYER, # 26 - ShapeLayer
LottieTensor.CMD_PRECOMP_LAYER, # 45
LottieTensor.CMD_TEXT_LAYER, # 89
LottieTensor.CMD_NULL_LAYER, # 43
LottieTensor.CMD_SOLID_LAYER, # 94
}
LAYER_END_CMDS = {
LottieTensor.CMD_LAYER_END,
LottieTensor.CMD_PRECOMP_LAYER_END,
LottieTensor.CMD_TEXT_LAYER_END,
LottieTensor.CMD_NULL_LAYER_END,
LottieTensor.CMD_SOLID_LAYER_END,
}
layer_stack = 0 # 跟踪layer的嵌套深度
for token in flattened:
if token >= command_offset and token < command_offset + len(LottieTensor.COMMANDS):
cmd_idx = token - command_offset
if cmd_idx == LottieTensor.CMD_ANIMATION:
has_animation = True
elif cmd_idx == LottieTensor.CMD_ASSET: # 进入asset
asset_depth += 1
elif cmd_idx == LottieTensor.CMD_ASSET_END: # 离开asset
if asset_depth > 0:
asset_depth -= 1
elif cmd_idx in LAYER_START_CMDS:
layer_stack += 1
elif cmd_idx in LAYER_END_CMDS:
if layer_stack > 0:
layer_stack -= 1
layer_count += 1 # 完成一个完整的layer
# 如果不在asset内部，这是主layer
if asset_depth == 0:
main_layer_count += 1
# 验证条件：
# 1. 有ANIMATION命令
# 2. 至少有一个完整的layer（layer_count >= 1）
# 3. 所有layer都已正确闭合（layer_stack == 0）
# 4. 【新增】至少有一个主layer（main_layer_count >= 1），防止只有assets没有主layers
return has_animation and layer_count >= 1 and layer_stack == 0 and main_layer_count >= 1
def flatten_to_list(lottie_tensor: 'LottieTensor', max_length: int = None) -> List[int]:
"""
Flatten LottieTensor to a 1D list with proper offsets.
紧凑格式：不使用 SKIP_TOKEN，只输出有意义的参数。
"""
COMMAND_OFFSET = 151936
NUMBER_OFFSET = 173186
NUM_COMMANDS = len(LottieTensor.COMMANDS)
# Essential parameter counts - params before this index must always be output
ESSENTIAL_PARAM_COUNT = {
LottieTensor.CMD_ANIMATION: 6,
LottieTensor.CMD_LAYER: 4,
LottieTensor.CMD_NULL_LAYER: 4,
LottieTensor.CMD_PRECOMP_LAYER: 4,
LottieTensor.CMD_TEXT_LAYER: 4,
LottieTensor.CMD_SOLID_LAYER: 6,
LottieTensor.CMD_KEYFRAME: 1,
LottieTensor.CMD_WIDTH_KEYFRAME: 2,
LottieTensor.CMD_COLOR_KEYFRAME: 5,
LottieTensor.CMD_OPACITY_KEYFRAME: 2,
LottieTensor.CMD_POINT: 2,
LottieTensor.CMD_FILL: 3,
LottieTensor.CMD_STROKE: 3,
LottieTensor.CMD_TRANSFORM_SHAPE: 8,
LottieTensor.CMD_GROUP: 1,
LottieTensor.CMD_PATH: 4,
LottieTensor.CMD_POSITION: 1,
LottieTensor.CMD_SCALE: 1,
LottieTensor.CMD_ROTATION: 1,
LottieTensor.CMD_OPACITY: 1,
LottieTensor.CMD_ANCHOR: 1,
LottieTensor.CMD_SIZE: 1,
LottieTensor.CMD_RECT: 1,
LottieTensor.CMD_STAR: 2,
LottieTensor.CMD_TRIM: 1,
LottieTensor.CMD_REPEATER: 1,
LottieTensor.CMD_MASK: 3,
LottieTensor.CMD_MASK_PT: 2,
LottieTensor.CMD_MASK_O: 3,
LottieTensor.CMD_MASK_X: 3,
LottieTensor.CMD_RANGE_SELECTOR: 5,
LottieTensor.CMD_RANGE_START: 1,
LottieTensor.CMD_RANGE_END: 1,
LottieTensor.CMD_RANGE_OFFSET: 1,
LottieTensor.CMD_AMOUNT: 3,
LottieTensor.CMD_EFFECT: 2,
LottieTensor.CMD_COLOR: 4,
LottieTensor.CMD_GRADIENT_TYPE: 1,
LottieTensor.CMD_TR_SCALE: 2,
LottieTensor.CMD_TR_POSITION: 2,
LottieTensor.CMD_TR_ANCHOR: 2,
LottieTensor.CMD_ORIGINAL_COLORS: 0,
LottieTensor.CMD_DASH_KEYFRAME: 2,
LottieTensor.CMD_RANGE_START_KEYFRAME: 2,
LottieTensor.CMD_RANGE_END_KEYFRAME: 2,
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: 2,
LottieTensor.CMD_ELLIPSE_SIZE: 1,
LottieTensor.CMD_RECT_SIZE: 1,
}
# Parameters with default value 0 (not PAD_VAL)
ZERO_DEFAULT_PARAMS = {
LottieTensor.CMD_KEYFRAME: {4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 24, 25},
LottieTensor.CMD_WIDTH_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_COLOR_KEYFRAME: {5, 6, 7, 8},
LottieTensor.CMD_OPACITY_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_DASH_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_RANGE_START_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_RANGE_END_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_RANGE_OFFSET_KEYFRAME: {2, 3, 4, 5},
LottieTensor.CMD_POINT: {2, 3, 4, 5},
LottieTensor.CMD_ANIMATION: {5},
LottieTensor.CMD_LAYER: {4, 5, 6, 7, 8, 9, 10, 11, 12},
LottieTensor.CMD_NULL_LAYER: {4, 5, 6, 7, 8, 9, 10, 11},
LottieTensor.CMD_PRECOMP_LAYER: {4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14},
LottieTensor.CMD_FILL: {3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14}, # Removed 8 (FILL_RULE) - should not default to 0
LottieTensor.CMD_STROKE: {3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13},
LottieTensor.CMD_GROUP: {1, 2, 3, 4},
LottieTensor.CMD_PATH: {4, 5},
LottieTensor.CMD_TRANSFORM_SHAPE: {8, 9, 10},
LottieTensor.CMD_RECT: {1},
LottieTensor.CMD_POSITION: {1, 2, 3},
LottieTensor.CMD_SCALE: {1, 2, 3},
LottieTensor.CMD_ROTATION: {1},
LottieTensor.CMD_OPACITY: {1},
LottieTensor.CMD_ANCHOR: {1, 2, 3},
LottieTensor.CMD_MASK_PT_K_I: set(range(21)),
LottieTensor.CMD_MASK_PT_K_O: set(range(21)),
LottieTensor.CMD_MASK_PT_K_V: set(range(21)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_I: set(range(21)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_O: set(range(21)),
LottieTensor.CMD_MASK_PT_KF_SHAPE_V: set(range(21)),
}
# SIZE类命令集合
SIZE_COMMANDS = {
LottieTensor.CMD_SIZE,
LottieTensor.CMD_ELLIPSE_SIZE,
LottieTensor.CMD_RECT_SIZE
}
TOKENIZER_COMMANDS = {
LottieTensor.CMD_FONT: {
'regular': [LottieTensor.Index.Font.ASCENT],
'token_groups': [
(LottieTensor.Index.Font.FAMILY_TOKEN_COUNT,
LottieTensor.Index.Font.FAMILY_TOKEN_0, 10),
(LottieTensor.Index.Font.STYLE_TOKEN_COUNT,
LottieTensor.Index.Font.STYLE_TOKEN_0, 10)
]
},
LottieTensor.CMD_CHAR: {
'regular': [
LottieTensor.Index.Char.SIZE,
LottieTensor.Index.Char.W
],
'token_groups': [
(LottieTensor.Index.Char.CH_TOKEN_COUNT,
LottieTensor.Index.Char.CH_TOKEN_0, 10),
(LottieTensor.Index.Char.STYLE_TOKEN_COUNT,
LottieTensor.Index.Char.STYLE_TOKEN_0, 10),
(LottieTensor.Index.Char.FAMILY_TOKEN_COUNT,
LottieTensor.Index.Char.FAMILY_TOKEN_0, 10)
]
},
LottieTensor.CMD_ASSET: {
'regular': [LottieTensor.Index.Asset.FR],
'token_groups': [
(LottieTensor.Index.Asset.ID_TOKEN_COUNT,
LottieTensor.Index.Asset.ID_TOKEN_0, 10)
]
},
LottieTensor.CMD_REFERENCE_ID: {
'regular': [],
'token_groups': [
(LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT,
LottieTensor.Index.ReferenceId.ID_TOKEN_0, 10)
]
},
LottieTensor.CMD_TEXT_KEYFRAME: {
'regular': list(range(LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START)),
'token_groups': [
(LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT,
LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START, 10),
(LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT,
LottieTensor.Index.TextKeyframe.TEXT_TOKENS_START, 15)
]
}
}
# 【修复】改进的 ANIMATED 值判断函数 - 使用更严格的阈值
def is_animated_value(value):
"""判断一个值是否表示动画状态"""
if value == LottieTensor.PAD_VAL:
return False
# 使用 0.5 作为阈值，任何 >= 0.5 的值都视为 animated
return value >= 0.5
def get_param_default(cmd_idx, param_pos, params):
"""Get default value for a parameter."""
# 对于SIZE类命令的特殊处理
if cmd_idx in SIZE_COMMANDS:
# 检查ANIMATED状态
animated_val = params[LottieTensor.Index.Transform.ANIMATED] if len(params) > 0 else LottieTensor.PAD_VAL
is_animated = animated_val != LottieTensor.PAD_VAL and is_animated_value(animated_val)
if param_pos == 0: # ANIMATED参数本身
return LottieTensor.PAD_VAL
elif param_pos in {1, 2}: # X 和 Y 参数
if is_animated:
# ANIMATED=1时，X和Y不应该输出（由keyframe提供）
return LottieTensor.PAD_VAL
else:
# ANIMATED=0时，X和Y默认为0
return 0.0
zero_set = ZERO_DEFAULT_PARAMS.get(cmd_idx, set())
if param_pos in zero_set:
return 0.0
return LottieTensor.PAD_VAL
def is_meaningful_value(value, default):
"""Check if a value is meaningful (not default)."""
if value == LottieTensor.PAD_VAL:
return False
if default == LottieTensor.PAD_VAL:
return True
return abs(value - default) > 1e-6
flattened = []
SIZE_END_COMMANDS = {
LottieTensor.CMD_SIZE: LottieTensor.CMD_SIZE_END,
LottieTensor.CMD_ELLIPSE_SIZE: LottieTensor.CMD_SIZE_END,
LottieTensor.CMD_RECT_SIZE: LottieTensor.CMD_SIZE_END,
}
# 【新增】前瞻检测：记录每个SIZE命令后面是否有keyframe
size_cmd_has_keyframe = {}
for i in range(lottie_tensor.seq_len.item()):
cmd_idx = int(lottie_tensor.commands[i].item())
if cmd_idx in SIZE_COMMANDS:
# 检查后续是否有keyframe（在遇到结束标记或其他形状命令之前）
has_kf = False
end_cmd = SIZE_END_COMMANDS.get(cmd_idx, LottieTensor.CMD_SIZE_END)
# 定义会结束 size 上下文的命令
context_end_cmds = {
end_cmd,
LottieTensor.CMD_FILL,
LottieTensor.CMD_STROKE,
LottieTensor.CMD_GROUP_END,
LottieTensor.CMD_ELLIPSE_END,
LottieTensor.CMD_RECT_END,
}
for j in range(i + 1, lottie_tensor.seq_len.item()):
next_cmd = int(lottie_tensor.commands[j].item())
if next_cmd in context_end_cmds:
break
if next_cmd == LottieTensor.CMD_KEYFRAME:
has_kf = True
break
size_cmd_has_keyframe[i] = has_kf
for i in range(lottie_tensor.seq_len.item()):
cmd_idx = int(lottie_tensor.commands[i].item())
if cmd_idx in [LottieTensor.CMD_EOS, LottieTensor.CMD_SOS, LottieTensor.CMD_PAD]:
continue
# Add command token
flattened.append(cmd_idx + COMMAND_OFFSET)
params = lottie_tensor.params[i].tolist()
if cmd_idx in TOKENIZER_COMMANDS:
# Handle tokenizer commands specially
cmd_info = TOKENIZER_COMMANDS[cmd_idx]
# 【方案C】对TOKENIZER_COMMANDS，总是写入所有regular params（包括PAD_VAL）
# 原因：regular params数量少（20个），但跳过PAD_VAL会导致unflatten无法可靠解码
# 其他命令仍然动态截断以节省token
for param_idx in cmd_info['regular']:
if param_idx < len(params):
value = params[param_idx]
offset = LottieTensor.get_param_offset(cmd_idx, param_idx)
flattened.append(int(round(value)) + offset)
for count_idx, token_start, max_tokens in cmd_info['token_groups']:
actual_count = 0
for j in range(max_tokens):
if token_start + j < len(params):
token_val = int(params[token_start + j])
if token_val != LottieTensor.PAD_VAL and token_val > 0:
actual_count = j + 1
flattened.append(actual_count + NUMBER_OFFSET)
for j in range(int(max(0, actual_count))):
if token_start + j < len(params):
token_val = int(params[token_start + j])
if token_val != LottieTensor.PAD_VAL and token_val > 0:
flattened.append(token_val)
else:
# Handle regular commands
param_indices = LottieTensor.get_command_param_indices(cmd_idx)
if param_indices:
essential_count = ESSENTIAL_PARAM_COUNT.get(cmd_idx, len(param_indices))
# 【关键修复】对于SIZE类命令的特殊处理
if cmd_idx in SIZE_COMMANDS:
animated_val = params[LottieTensor.Index.Transform.ANIMATED]
# 【修复】综合判断是否是动画：
# 1. ANIMATED参数明确设为1
# 2. 或者后续有keyframe命令（前瞻检测结果）
is_animated_by_param = animated_val != LottieTensor.PAD_VAL and is_animated_value(animated_val)
is_animated_by_keyframe = size_cmd_has_keyframe.get(i, False)
is_animated = is_animated_by_param or is_animated_by_keyframe
if is_animated:
# 动画模式：只输出ANIMATED参数，值固定为1
offset = LottieTensor.get_param_offset(cmd_idx, param_indices[0])
flattened.append(1 + offset) # 固定输出整数1
continue # 跳过后续处理
# 统一使用动态截断逻辑
last_meaningful = -1
for j, param_idx in enumerate(param_indices):
if param_idx < len(params):
value = params[param_idx]
default = get_param_default(cmd_idx, j, params)
if is_meaningful_value(value, default):
last_meaningful = j
output_count = max(essential_count, last_meaningful + 1) if last_meaningful >= 0 else essential_count
output_count = min(output_count, len(param_indices))
# 写入参数
for j in range(output_count):
param_idx = param_indices[j]
if param_idx < len(params):
value = params[param_idx]
if value == LottieTensor.PAD_VAL:
default = get_param_default(cmd_idx, j, params)
value = default if default != LottieTensor.PAD_VAL else 0.0
offset = LottieTensor.get_param_offset(cmd_idx, param_idx)
flattened.append(int(round(value)) + offset)
# 智能截断逻辑
if max_length and len(flattened) > max_length:
# 如果长度在 max_length 和 2*max_length 之间，智能截断到最近的layer end
if len(flattened) <= 3 * max_length:
truncate_point = LottieTensor._find_nearest_layer_end(flattened, max_length, COMMAND_OFFSET)
if truncate_point > 0:
flattened = flattened[:truncate_point]
else:
# ❌ 找不到合适的layer end，放弃这个样本（返回None标记）
return None
else:
# 超过2倍长度，也放弃（太长了）
return None
return flattened
@staticmethod
def from_list(flattened: List[int]) -> 'LottieTensor':
"""
Reconstruct LottieTensor from a flattened 1D list.
紧凑格式解码：通过判断是否为命令Token来区分边界。
"""
# 【新增】确保tokenizer可用于文本解码
if LottieTensor.tokenizer is None:
try:
LottieTensor.init_tokenizer()
except Exception as e:
print(f"Warning: Failed to initialize tokenizer in from_list: {e}")
COMMAND_OFFSET = 151936
NUMBER_OFFSET = 173186
NUM_COMMANDS = len(LottieTensor.COMMANDS)
# SIZE类命令集合
SIZE_COMMANDS = {
LottieTensor.CMD_SIZE,
LottieTensor.CMD_ELLIPSE_SIZE,
LottieTensor.CMD_RECT_SIZE
}
# 【修复】ANIMATED 阈值常量
ANIMATED_THRESHOLD = 0.5
# Default values for parameters when not provided
PARAM_DEFAULTS = {}
# Keyframe easing defaults
#for i in [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 24, 25]:
for i in [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22]:
PARAM_DEFAULTS[(LottieTensor.CMD_KEYFRAME, i)] = 0.0
for i in range(2, 6):
PARAM_DEFAULTS[(LottieTensor.CMD_WIDTH_KEYFRAME, i)] = 0.0
for i in range(5, 9):
PARAM_DEFAULTS[(LottieTensor.CMD_COLOR_KEYFRAME, i)] = 0.0
for i in range(2, 6):
PARAM_DEFAULTS[(LottieTensor.CMD_OPACITY_KEYFRAME, i)] = 0.0
for i in range(2, 6):
PARAM_DEFAULTS[(LottieTensor.CMD_POINT, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_ANIMATION, 5)] = 0.0
for i in range(4, 13):
PARAM_DEFAULTS[(LottieTensor.CMD_LAYER, i)] = 0.0
for i in range(4, 12):
PARAM_DEFAULTS[(LottieTensor.CMD_NULL_LAYER, i)] = 0.0
for i in range(4, 15):
PARAM_DEFAULTS[(LottieTensor.CMD_PRECOMP_LAYER, i)] = 0.0
for i in range(3, 15):
PARAM_DEFAULTS[(LottieTensor.CMD_FILL, i)] = 0.0
for i in range(3, 14):
PARAM_DEFAULTS[(LottieTensor.CMD_STROKE, i)] = 0.0
for i in range(1, 5):
PARAM_DEFAULTS[(LottieTensor.CMD_GROUP, i)] = 0.0
for i in range(4, 6):
PARAM_DEFAULTS[(LottieTensor.CMD_PATH, i)] = 0.0
for i in range(8, 11):
PARAM_DEFAULTS[(LottieTensor.CMD_TRANSFORM_SHAPE, i)] = 0.0
for i in range(1, 4):
PARAM_DEFAULTS[(LottieTensor.CMD_POSITION, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_SCALE, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_ANCHOR, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_ROTATION, 1)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_OPACITY, 1)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_RECT, 1)] = 0.0
for i in range(21):
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_K_I, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_K_O, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_K_V, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_KF_SHAPE_I, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_KF_SHAPE_O, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_MASK_PT_KF_SHAPE_V, i)] = 0.0
for i in range(2, 6):
PARAM_DEFAULTS[(LottieTensor.CMD_DASH_KEYFRAME, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_RANGE_START_KEYFRAME, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_RANGE_END_KEYFRAME, i)] = 0.0
PARAM_DEFAULTS[(LottieTensor.CMD_RANGE_OFFSET_KEYFRAME, i)] = 0.0
TOKENIZER_COMMANDS = {
LottieTensor.CMD_FONT: {
'regular': [LottieTensor.Index.Font.ASCENT],
'token_groups': [
(LottieTensor.Index.Font.FAMILY_TOKEN_COUNT,
LottieTensor.Index.Font.FAMILY_TOKEN_0, 10),
(LottieTensor.Index.Font.STYLE_TOKEN_COUNT,
LottieTensor.Index.Font.STYLE_TOKEN_0, 10)
]
},
LottieTensor.CMD_CHAR: {
'regular': [
LottieTensor.Index.Char.SIZE,
LottieTensor.Index.Char.W
],
'token_groups': [
(LottieTensor.Index.Char.CH_TOKEN_COUNT,
LottieTensor.Index.Char.CH_TOKEN_0, 10),
(LottieTensor.Index.Char.STYLE_TOKEN_COUNT,
LottieTensor.Index.Char.STYLE_TOKEN_0, 10),
(LottieTensor.Index.Char.FAMILY_TOKEN_COUNT,
LottieTensor.Index.Char.FAMILY_TOKEN_0, 10)
]
},
LottieTensor.CMD_ASSET: {
'regular': [LottieTensor.Index.Asset.FR],
'token_groups': [
(LottieTensor.Index.Asset.ID_TOKEN_COUNT,
LottieTensor.Index.Asset.ID_TOKEN_0, 10)
]
},
LottieTensor.CMD_REFERENCE_ID: {
'regular': [],
'token_groups': [
(LottieTensor.Index.ReferenceId.ID_TOKEN_COUNT,
LottieTensor.Index.ReferenceId.ID_TOKEN_0, 10)
]
},
LottieTensor.CMD_TEXT_KEYFRAME: {
'regular': list(range(LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START)),
'token_groups': [
(LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKEN_COUNT,
LottieTensor.Index.TextKeyframe.FONT_FAMILY_TOKENS_START, 10),
(LottieTensor.Index.TextKeyframe.TEXT_TOKEN_COUNT,
LottieTensor.Index.TextKeyframe.TEXT_TOKENS_START, 15)
]
}
}
def is_command_token(token):
"""Check if a token is a command token."""
return COMMAND_OFFSET <= token < COMMAND_OFFSET + NUM_COMMANDS
def get_default_value(cmd_idx, param_pos, params):
"""Get default value for a parameter."""
# SIZE类命令的特殊处理
if cmd_idx in SIZE_COMMANDS:
animated_val = params[LottieTensor.Index.Transform.ANIMATED]
is_animated = animated_val != LottieTensor.PAD_VAL and animated_val >= ANIMATED_THRESHOLD
if param_pos in {1, 2}: # X 和 Y 参数
if is_animated:
# ANIMATED=1时，X和Y应该保持PAD_VAL（由keyframe提供）
return LottieTensor.PAD_VAL
else:
# ANIMATED=0时，X和Y默认为0
return 0.0
key = (cmd_idx, param_pos)
return PARAM_DEFAULTS.get(key, LottieTensor.PAD_VAL)
# 【新增】辅助函数：检查后续是否有keyframe命令（在遇到对应的END命令之前）
def has_following_keyframe(flattened_list, start_idx, cmd_idx):
"""检查从start_idx开始，是否有keyframe命令出现在结束标记之前"""
# SIZE命令的结束标记
SIZE_END_COMMANDS = {
LottieTensor.CMD_SIZE: LottieTensor.CMD_SIZE_END,
LottieTensor.CMD_ELLIPSE_SIZE: LottieTensor.CMD_SIZE_END,
LottieTensor.CMD_RECT_SIZE: LottieTensor.CMD_SIZE_END,
}
end_cmd = SIZE_END_COMMANDS.get(cmd_idx, LottieTensor.CMD_SIZE_END)
# 会结束 size 上下文的命令集合
context_end_cmds = {
end_cmd,
LottieTensor.CMD_FILL,
LottieTensor.CMD_STROKE,
LottieTensor.CMD_GROUP_END,
LottieTensor.CMD_ELLIPSE_END,
LottieTensor.CMD_RECT_END,
}
for k in range(start_idx, len(flattened_list)):
if is_command_token(flattened_list[k]):
cmd = flattened_list[k] - COMMAND_OFFSET
if cmd in context_end_cmds:
return False
if cmd == LottieTensor.CMD_KEYFRAME:
return True
return False
commands = []
params_list = []
i = 0
while i < len(flattened):
if is_command_token(flattened[i]):
cmd_idx = flattened[i] - COMMAND_OFFSET
commands.append(cmd_idx)
cmd_start_i = i # 记录命令的起始位置
i += 1
params = [LottieTensor.PAD_VAL] * LottieTensor.PARAM_DIM
if cmd_idx in TOKENIZER_COMMANDS:
cmd_info = TOKENIZER_COMMANDS[cmd_idx]
regular_params = cmd_info['regular']
# 【方案C】读取所有regular params - 固定长度，每个都读取
for param_idx in regular_params:
if i < len(flattened) and not is_command_token(flattened[i]):
offset = LottieTensor.get_param_offset(cmd_idx, param_idx)
params[param_idx] = float(flattened[i] - offset)
i += 1
for count_idx, token_start, max_tokens in cmd_info['token_groups']:
if i < len(flattened) and not is_command_token(flattened[i]):
count = flattened[i] - NUMBER_OFFSET
params[count_idx] = float(count)
i += 1
for j in range(int(max(0, count))):
if i < len(flattened) and not is_command_token(flattened[i]):
if token_start + j < LottieTensor.PARAM_DIM:
params[token_start + j] = float(flattened[i])
i += 1
else:
break
else:
param_indices = LottieTensor.get_command_param_indices(cmd_idx)
# Read parameters until next command
param_pos = 0
while (param_pos < len(param_indices) and
i < len(flattened) and
not is_command_token(flattened[i])):
param_idx = param_indices[param_pos]
offset = LottieTensor.get_param_offset(cmd_idx, param_idx)
params[param_idx] = float(flattened[i] - offset)
param_pos += 1
i += 1
# 【关键修复】对于SIZE类命令的特殊后处理
if cmd_idx in SIZE_COMMANDS:
animated_val = params[LottieTensor.Index.Transform.ANIMATED]
# 情况1：只读到了ANIMATED参数且值为1
if param_pos == 1 and animated_val != LottieTensor.PAD_VAL and animated_val >= ANIMATED_THRESHOLD:
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
# 情况2：没有读到有效的ANIMATED参数，通过前瞻检测判断
elif animated_val == LottieTensor.PAD_VAL or animated_val < ANIMATED_THRESHOLD:
# 使用修改后的函数，传入命令类型
if has_following_keyframe(flattened, i, cmd_idx):
params[LottieTensor.Index.Transform.ANIMATED] = 1.0
elif param_pos >= 2:
# 读到了多个参数，是静态 size
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# 情况3：读到了多个参数（静态size），确保ANIMATED=0
elif param_pos >= 2 and (animated_val == LottieTensor.PAD_VAL or animated_val < ANIMATED_THRESHOLD):
params[LottieTensor.Index.Transform.ANIMATED] = 0.0
# Fill in defaults for remaining parameters
for j in range(param_pos, len(param_indices)):
param_idx = param_indices[j]
# 获取默认值，需要传入当前params来判断ANIMATED状态
default_val = get_default_value(cmd_idx, j, params)
if default_val != LottieTensor.PAD_VAL:
params[param_idx] = default_val
params_list.append(params)
else:
i += 1
if commands:
commands_tensor = torch.tensor(commands).reshape(-1, 1).long()
params_tensor = torch.tensor(params_list).float()
else:
commands_tensor = torch.zeros((0, 1)).long()
params_tensor = torch.zeros((0, LottieTensor.PARAM_DIM)).float()
return LottieTensor(commands_tensor, params_tensor)
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