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https://github.com/modelscope/DiffSynth-Studio.git
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add examples
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import torch
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from diffsynth import save_video,VideoData
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from diffsynth.pipelines.wan_video_new import WanVideoPipeline, ModelConfig
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from PIL import Image
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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-Control-Camera", 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-Control-Camera", 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-Control-Camera", 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-Control-Camera", origin_file_pattern="Wan2.1_VAE.pth", offload_device="cpu"),
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],
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)
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pipe.enable_vram_management()
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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/input_image.jpg"
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)
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input_image = Image.open("data/examples/wan/input_image.jpg")
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video = pipe(
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prompt="一艘小船正勇敢地乘风破浪前行。蔚蓝的大海波涛汹涌,白色的浪花拍打着船身,但小船毫不畏惧,坚定地驶向远方。阳光洒在水面上,闪烁着金色的光芒,为这壮丽的场景增添了一抹温暖。镜头拉近,可以看到船上的旗帜迎风飘扬,象征着不屈的精神与冒险的勇气。这段画面充满力量,激励人心,展现了面对挑战时的无畏与执着。",
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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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seed=0, tiled=True,
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input_image=input_image,
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camera_control_direction="Left", camera_control_speed=0.01,
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)
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save_video(video, "video_left.mp4", fps=15, quality=5)
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video = pipe(
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prompt="一艘小船正勇敢地乘风破浪前行。蔚蓝的大海波涛汹涌,白色的浪花拍打着船身,但小船毫不畏惧,坚定地驶向远方。阳光洒在水面上,闪烁着金色的光芒,为这壮丽的场景增添了一抹温暖。镜头拉近,可以看到船上的旗帜迎风飘扬,象征着不屈的精神与冒险的勇气。这段画面充满力量,激励人心,展现了面对挑战时的无畏与执着。",
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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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seed=0, tiled=True,
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input_image=input_image,
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camera_control_direction="Up", camera_control_speed=0.01,
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)
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save_video(video, "video_up.mp4", fps=15, quality=5)
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35
examples/wanvideo/model_inference/Wan2.2-Fun-A14B-Control.py
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35
examples/wanvideo/model_inference/Wan2.2-Fun-A14B-Control.py
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import torch
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from diffsynth import save_video,VideoData
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from diffsynth.pipelines.wan_video_new import WanVideoPipeline, ModelConfig
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from PIL import Image
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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-Control", 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-Control", 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-Control", 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-Control", origin_file_pattern="Wan2.1_VAE.pth", offload_device="cpu"),
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],
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)
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pipe.enable_vram_management()
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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=["data/examples/wan/control_video.mp4", "data/examples/wan/reference_image_girl.png"]
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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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reference_image = Image.open("data/examples/wan/reference_image_girl.png").resize((576, 832))
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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, reference_image=reference_image,
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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.mp4", fps=15, quality=5)
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35
examples/wanvideo/model_inference/Wan2.2-Fun-A14B-Inp.py
Normal file
35
examples/wanvideo/model_inference/Wan2.2-Fun-A14B-Inp.py
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import torch
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from diffsynth import save_video
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from diffsynth.pipelines.wan_video_new import WanVideoPipeline, ModelConfig
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from PIL import Image
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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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pipe.enable_vram_management()
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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/input_image.jpg"
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)
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image = Image.open("data/examples/wan/input_image.jpg")
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# First and last frame to video
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video = pipe(
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prompt="一艘小船正勇敢地乘风破浪前行。蔚蓝的大海波涛汹涌,白色的浪花拍打着船身,但小船毫不畏惧,坚定地驶向远方。阳光洒在水面上,闪烁着金色的光芒,为这壮丽的场景增添了一抹温暖。镜头拉近,可以看到船上的旗帜迎风飘扬,象征着不屈的精神与冒险的勇气。这段画面充满力量,激励人心,展现了面对挑战时的无畏与执着。",
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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=image,
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seed=0, tiled=True,
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# You can input `end_image=xxx` to control the last frame of the video.
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# The model will automatically generate the dynamic content between `input_image` and `end_image`.
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)
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save_video(video, "video.mp4", fps=15, quality=5)
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