mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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46 lines
2.4 KiB
Python
46 lines
2.4 KiB
Python
import torch
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from PIL import Image
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from diffsynth.utils.data import save_video, VideoData
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from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
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from modelscope import dataset_snapshot_download
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vram_config = {
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"offload_dtype": "disk",
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"offload_device": "disk",
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"onload_dtype": torch.bfloat16,
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"onload_device": "cpu",
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"preparing_dtype": torch.bfloat16,
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"preparing_device": "cuda",
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"computation_dtype": torch.bfloat16,
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"computation_device": "cuda",
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}
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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/Wan2.1-Fun-14B-Control", origin_file_pattern="diffusion_pytorch_model*.safetensors", **vram_config),
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ModelConfig(model_id="PAI/Wan2.1-Fun-14B-Control", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth", **vram_config),
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ModelConfig(model_id="PAI/Wan2.1-Fun-14B-Control", origin_file_pattern="Wan2.1_VAE.pth", **vram_config),
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ModelConfig(model_id="PAI/Wan2.1-Fun-14B-Control", origin_file_pattern="models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth", **vram_config),
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],
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tokenizer_config=ModelConfig(model_id="Wan-AI/Wan2.1-T2V-1.3B", origin_file_pattern="google/umt5-xxl/"),
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vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 2,
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)
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dataset_snapshot_download(
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dataset_id="DiffSynth-Studio/examples_in_diffsynth",
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local_dir="./",
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allow_file_pattern=f"data/examples/wan/control_video.mp4"
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)
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# Control video
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control_video = VideoData("data/examples/wan/control_video.mp4", height=832, width=576)
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video = pipe(
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prompt="扁平风格动漫，一位长发少女优雅起舞。她五官精致，大眼睛明亮有神，黑色长发柔顺光泽。身穿淡蓝色T恤和深蓝色牛仔短裤。背景是粉色。",
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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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control_video=control_video, height=832, width=576, num_frames=49,
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seed=1, tiled=True
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)
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save_video(video, "video_Wan2.1-Fun-14B-Control.mp4", fps=15, quality=5)
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