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: [ 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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)