42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
import torch
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from fastvideo.models.hunyuan.diffusion.pipelines.pipeline_hunyuan_video import HunyuanVideoPipeline
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from fastvideo.models.hunyuan.modules.models import HYVideoDiffusionTransformer
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from fastvideo.models.hunyuan.vae.autoencoder_kl_causal_3d import AutoencoderKLCausal3D
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transformer=HYVideoDiffusionTransformer.from_pretrained(
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'data/hyvideo-diffusers',
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torch_dtype=torch.bfloat16,
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subfolder='transformer'
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)
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vae=AutoencoderKLCausal3D.from_pretrained(
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'data/hyvideo-diffusers',
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torch_dtype=torch.float16,
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subfolder='vae'
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)
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pipe = HunyuanVideoPipeline.from_pretrained(
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'data/hyvideo-diffusers',
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transformer=transformer,
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vae=vae
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)
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pipe = pipe.to('cuda')
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pipe.vae.enable_tiling()
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prompt = "Close-up, A little girl wearing a red hoodie in winter strikes a match. The sky is dark, there is a layer of snow on the ground, and it is still snowing lightly. The flame of the match flickers, illuminating the girl's face intermittently."
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result = pipe(
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prompt,
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height=512,
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width=512,
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video_length=29,
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)
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import PIL.Image
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from diffusers.utils import export_to_video
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output = result.videos[0].permute(1, 2, 3, 0).detach().cpu().numpy()
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output = (output * 255).clip(0, 255).astype("uint8")
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output = [PIL.Image.fromarray(x) for x in output]
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export_to_video(output, "output.mp4", fps=24) |