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| from pathlib import Path | |
| from sorawm.core import SoraWM | |
| from sorawm.schemas import CleanerType | |
| if __name__ == "__main__": | |
| input_video_path = Path("resources/dog_vs_sam.mp4") | |
| output_video_path = Path("outputs/sora_watermark_removed") | |
| # 1. LAMA is fast and good quality, but not time consistent. | |
| sora_wm = SoraWM(cleaner_type=CleanerType.LAMA) | |
| sora_wm.run(input_video_path, Path(f"{output_video_path}_lama.mp4")) | |
| # 2. E2FGVI_HQ ensures time consistency, but will be very slow on no-cuda device. | |
| sora_wm = SoraWM(cleaner_type=CleanerType.E2FGVI_HQ, enable_torch_compile=False) | |
| sora_wm.run(input_video_path, Path(f"{output_video_path}_e2fgvi_hq.mp4")) | |
| # 3. E2FGVI_HQ with torch compile is fast and good quality, but not time consistent. | |
| sora_wm = SoraWM(cleaner_type=CleanerType.E2FGVI_HQ, enable_torch_compile=True) | |
| sora_wm.run( | |
| input_video_path, Path(f"{output_video_path}_e2fgvi_hq_torch_compile.mp4") | |
| ) | |