| import argparse | |
| def init(): | |
| parser = argparse.ArgumentParser(description="PyTorch") | |
| parser.add_argument('--path_to_images', type=str, default='/fast_dataset/shuai/avadata/images', | |
| help='directory to images') | |
| parser.add_argument('--path_to_save_csv', type=str, default="./dataset/", | |
| help='directory to csv_folder') | |
| parser.add_argument('--experiment_dir_name', type=str, default='.', | |
| help='directory to project') | |
| parser.add_argument('--path_to_model_weight', type=str, default='SRCC_758_LCC_765.pth', | |
| help='directory to pretrain model') | |
| parser.add_argument('--init_lr_res365_last', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr_mobileNet', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr_head', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr_head_rgb', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr_hypernet', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr_tygertnet', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--init_lr', type=int, default=0.0003, help='learning_rate') | |
| parser.add_argument('--num_epoch', type=int, default=20, help='epoch num for train' | |
| ) | |
| parser.add_argument('--batch_size', type=int, default=48, help='16how many pictures to process one time' | |
| ) | |
| parser.add_argument('--num_workers', type=int, default=6, help='num_workers', | |
| ) | |
| parser.add_argument('--gpu_id', type=str, default='0', help='which gpu to use') | |
| args = parser.parse_args() | |
| return args | |