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import torch |
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from PIL import Image |
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from diffsynth import save_video, VideoData, load_state_dict |
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from diffsynth.pipelines.wan_video_new import WanVideoPipeline, ModelConfig |
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from modelscope import dataset_snapshot_download |
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pipe = WanVideoPipeline.from_pretrained( |
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torch_dtype=torch.bfloat16, |
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device="cuda", |
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model_configs=[ |
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ModelConfig(model_id="PAI/Wan2.2-Fun-A14B-InP", origin_file_pattern="high_noise_model/diffusion_pytorch_model*.safetensors", offload_device="cpu"), |
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ModelConfig(model_id="PAI/Wan2.2-Fun-A14B-InP", origin_file_pattern="low_noise_model/diffusion_pytorch_model*.safetensors", offload_device="cpu"), |
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ModelConfig(model_id="PAI/Wan2.2-Fun-A14B-InP", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth", offload_device="cpu"), |
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ModelConfig(model_id="PAI/Wan2.2-Fun-A14B-InP", origin_file_pattern="Wan2.1_VAE.pth", offload_device="cpu"), |
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], |
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) |
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state_dict = load_state_dict("models/train/Wan2.2-Fun-A14B-InP_high_noise_full/epoch-1.safetensors") |
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pipe.dit.load_state_dict(state_dict) |
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state_dict = load_state_dict("models/train/Wan2.2-Fun-A14B-InP_low_noise_full/epoch-1.safetensors") |
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pipe.dit2.load_state_dict(state_dict) |
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pipe.enable_vram_management() |
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video = VideoData("data/example_video_dataset/video1.mp4", height=480, width=832) |
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video = pipe( |
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prompt="from sunset to night, a small town, light, house, river", |
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negative_prompt="色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走", |
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input_image=video[0], end_image=video[80], |
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seed=0, tiled=True |
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) |
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save_video(video, "video_Wan2.2-Fun-A14B-InP.mp4", fps=15, quality=5) |
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