mirror of
https://github.com/Wan-Video/Wan2.1.git
synced 2025-07-14 11:40:10 +00:00
68 lines
2.3 KiB
Python
Executable File
68 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python
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# Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.
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import argparse
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import os
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import os.path as osp
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import sys
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import warnings
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warnings.filterwarnings('ignore')
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# Add model path to system path
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sys.path.insert(0, os.path.sep.join(osp.realpath(__file__).split(os.path.sep)[:-2]))
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import wan
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from wan.configs import WAN_CONFIGS
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from wan.utils.utils import cache_video
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def main():
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parser = argparse.ArgumentParser(description='Wan2.1 Text to Video Generation')
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parser.add_argument('--prompt', type=str, required=True, help='Text prompt for video generation')
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parser.add_argument('--resolution', type=str, default='512*320', help='Output resolution in WxH format')
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parser.add_argument('--steps', type=int, default=30, help='Number of sampling steps')
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parser.add_argument('--guide_scale', type=float, default=7.5, help='Guidance scale')
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parser.add_argument('--shift_scale', type=float, default=1.0, help='Shift scale')
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parser.add_argument('--seed', type=int, default=-1, help='Random seed (-1 for random)')
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parser.add_argument('--n_prompt', type=str, default='', help='Negative prompt')
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parser.add_argument('--output', type=str, required=True, help='Output video path')
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args = parser.parse_args()
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# Parse resolution
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W = int(args.resolution.split('*')[0])
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H = int(args.resolution.split('*')[1])
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# Set seed
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seed = None if args.seed < 0 else args.seed
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# Initialize model
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print(f"Initializing Wan T2V model...")
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wan_t2v = wan.T2V(
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model_id=WAN_CONFIGS['wan-t2v-14B']['model_id'],
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device_map='cuda',
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vae_scale_factor=WAN_CONFIGS['wan-t2v-14B']['scale_factor'],
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model_processor_id=WAN_CONFIGS['wan-t2v-14B']['model_processor_id'],
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output_dir=os.path.dirname(args.output),
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)
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print(f"Generating video with prompt: {args.prompt}")
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video = wan_t2v.generate(
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args.prompt,
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size=(W, H),
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shift=args.shift_scale,
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sampling_steps=args.steps,
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guide_scale=args.guide_scale,
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n_prompt=args.n_prompt,
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seed=seed,
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offload_model=True
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)
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# Save video
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video_path = cache_video(args.output, video)
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print(f"Video saved to: {video_path}")
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# Clean up
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del wan_t2v
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if __name__ == "__main__":
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main()
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