| import torch |
| import os |
| from vbench2_beta_trustworthiness import VBenchTrustworthiness |
| from datetime import datetime |
|
|
| import argparse |
|
|
| def parse_args(): |
|
|
| CUR_DIR = os.path.dirname(os.path.abspath(__file__)) |
| parser = argparse.ArgumentParser(description='VBench') |
| parser.add_argument( |
| "--output_path", |
| type=str, |
| default='./evaluation_trustworthy_results/', |
| help="output path to save the evaluation results", |
| ) |
| parser.add_argument( |
| "--full_json_dir", |
| type=str, |
| default=f'{CUR_DIR}/vbench2_beta_trustworthiness/vbench2_trustworthy.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", |
| nargs='+', |
| required=True, |
| help="list of evaluation dimensions, usage: --dimension <dim_1> <dim_2>", |
| ) |
| 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", |
| ) |
| parser.add_argument( |
| "--custom_input", |
| action="store_true", |
| required=False, |
| help="whether use custom input prompt or vbench prompt" |
| ) |
| args = parser.parse_args() |
| return args |
|
|
|
|
| def main(): |
| args = parse_args() |
| print(f'args: {args}') |
|
|
| device = torch.device("cuda") |
| my_VBench = VBenchTrustworthiness(device, args.full_json_dir, args.output_path) |
| |
| print(f'start evaluation') |
| current_time = datetime.now().strftime('%Y-%m-%d-%H:%M:%S') |
| my_VBench.evaluate( |
| videos_path = args.videos_path, |
| name = f'results_{current_time}', |
| dimension_list = args.dimension, |
| local=args.load_ckpt_from_local, |
| read_frame=args.read_frame, |
| custom_prompt=args.custom_input, |
| ) |
| print('done') |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
