Download VideoX-Fun/VBench/bin/evaluate from YFanwang/Backup: direct link, hf CLI and curl.
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- Download file 1.77 kB
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https://huggingface.co/datasets/YFanwang/Backup/resolve/main/VideoX-Fun/VBench/bin/evaluate
- Command line
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hf download hf://datasets/YFanwang/Backup/VideoX-Fun/VBench/bin/evaluate
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curl -L -o evaluate https://huggingface.co/datasets/YFanwang/Backup/resolve/main/VideoX-Fun/VBench/bin/evaluate
1.77 kB
| #!/usr/bin/env python3 | |
| import torch | |
| import vbench | |
| from vbench import VBench | |
| import argparse | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description='VBench') | |
| parser.add_argument( | |
| "--output_path", | |
| type=str, | |
| default='./evaluation_results/', | |
| help="output path to save the evaluation results", | |
| ) | |
| parser.add_argument( | |
| "--full_json_dir", | |
| type=str, | |
| default='./VBench_full_info.json', | |
| help="path to save the json file that contains the prompt and dimension information", | |
| ) | |
| parser.add_argument( | |
| "--videos_path", | |
| type=str, | |
| required=True, | |
| help="folder that contains the sampled videos", | |
| ) | |
| parser.add_argument( | |
| "--dimension", | |
| type=str, | |
| required=True, | |
| help="evaluation dimensions", | |
| ) | |
| parser.add_argument( | |
| "--load_ckpt_from_local", | |
| type=bool, | |
| required=False, | |
| help="whether load checkpoints from local default paths (assuming you have downloaded the checkpoints locally", | |
| ) | |
| parser.add_argument( | |
| "--read_frame", | |
| type=bool, | |
| required=False, | |
| help="whether directly read frames, or directly read videos", | |
| ) | |
| args = parser.parse_args() | |
| return args | |
| def main(): | |
| args = parse_args() | |
| print(f'args: {args}') | |
| device = torch.device("cuda") | |
| my_VBench = VBench(device, args.full_json_dir, args.output_path) | |
| print(f'start evaluation') | |
| my_VBench.evaluate( | |
| videos_path = args.videos_path, | |
| name = args.dimension, | |
| dimension_list = [args.dimension], | |
| local=args.load_ckpt_from_local, | |
| read_frame=args.read_frame, | |
| ) | |
| print('done') | |
| if __name__ == "__main__": | |
| main() | |