option.py

import argparse

parser = argparse.ArgumentParser(description='RTFM')
parser.add_argument('--feature-extractor', default='i3d', choices=['i3d', 'clip'])
parser.add_argument('--feature-size', type=int, default=2048, help='size of feature (default: 2048)/xd i3d=1024 clip=512')
parser.add_argument('--modality', default='RGB', help='the type of the input, RGB,AUDIO, or MIX')
parser.add_argument('--rgb-list', default='list/shanghai-i3d-train-10crop.list', help='list of rgb features ')
parser.add_argument('--test-rgb-list', default='list/shanghai-i3d-test-10crop.list', help='list of test rgb features ')
parser.add_argument('--gt', default='list/gt-sh.npy', help='file of ground truth ')
parser.add_argument('--gpus', default=0, type=int, choices=[0,1], help='gpus')
parser.add_argument('--lr', type=str, default='[0.001]*15000', help='learning rates for steps(list form)')
parser.add_argument('--batch-size', type=int, default=32, help='number of instances in a batch of data (default: 16)')
parser.add_argument('--workers', default=4, help='number of workers in dataloader')
parser.add_argument('--model-name', default='IFS', help='name to save model')
parser.add_argument('--pretrained-ckpt', default=None, help='ckpt for pretrained model')
parser.add_argument('--num-classes', type=int, default=1, help='number of class')
parser.add_argument('--dataset', default='ucf', help='dataset to train on (default: shanghai) /ucf/xd)')
parser.add_argument('--plot-freq', type=int, default=10, help='frequency of plotting (default: 10)')
parser.add_argument('--max-epoch', type=int, default=500, help='maximum iteration to train (default: 100)')