mirror of
https://github.com/OpenVGLab/OmniLottie.git
synced 2026-09-16 23:26:26 +00:00
init
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@@ -43,7 +43,8 @@ def load_model_once():
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checkpoint_path = "/PATH/TO/OmniLottie"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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device = torch.device("cuda:0" if torch.cuda.is_available() else "xpu:0" if torch.xpu.is_available() else "cpu")
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print(f"Loading model from {checkpoint_path}...")
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model = LottieDecoder(pix_len=4560, text_len=1500)
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@@ -599,6 +600,8 @@ def process_text_to_lottie(text_prompt, max_tokens, use_sampling, temperature, t
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del inputs
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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lottie_json = tokens_to_lottie_json(generated_ids)
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@@ -615,6 +618,8 @@ def process_text_to_lottie(text_prompt, max_tokens, use_sampling, temperature, t
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except Exception as e:
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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return None, f"❌ Error: {str(e)}", None
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def load_image_from_file(file_path):
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@@ -663,6 +668,8 @@ def process_image_to_lottie(image_file, text_description, max_tokens, use_sampli
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del inputs
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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lottie_json = tokens_to_lottie_json(generated_ids)
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@@ -679,6 +686,8 @@ def process_image_to_lottie(image_file, text_description, max_tokens, use_sampli
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except Exception as e:
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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return None, f"❌ Error: {str(e)}", None
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def process_video_to_lottie(video, max_tokens, use_sampling, temperature, top_p, top_k):
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@@ -709,6 +718,8 @@ def process_video_to_lottie(video, max_tokens, use_sampling, temperature, top_p,
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del inputs
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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lottie_json = tokens_to_lottie_json(generated_ids)
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@@ -725,6 +736,8 @@ def process_video_to_lottie(video, max_tokens, use_sampling, temperature, top_p,
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except Exception as e:
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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if torch.xpu.is_available():
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torch.xpu.empty_cache()
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return None, f"❌ Error: {str(e)}", None
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def create_gradio_interface():
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