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on
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Running
on
Zero
| from latentsync.pipelines.lipsync_pipeline import LipsyncPipeline | |
| import torch | |
| pipeline = LipsyncPipeline( | |
| scheduler=None, | |
| vae=None, | |
| audio_encoder=None, | |
| unet=None, | |
| ).to("cuda") | |
| def apply_lipsync(video_input_path, audio_path, video_out_path): | |
| torch.manual_seed(1234) | |
| print(f"Initial seed: {torch.initial_seed()}") | |
| pipeline( | |
| video_path=video_input_path, | |
| audio_path=audio_path, | |
| video_out_path=video_out_path, | |
| video_mask_path=video_out_path.replace(".mp4", "_mask.mp4"), | |
| num_frames=16, | |
| num_inference_steps=20, | |
| guidance_scale=1.0, | |
| weight_dtype=torch.float16, | |
| width=256, | |
| height=256, | |
| ) | |
| return video_out_path | |