dense_feature_matching_script

    parser.add_argument('--image_downsampling', type=float, default=4.0,
                        help='input image downsampling rate')
    parser.add_argument('--network_downsampling', type=int, default=64, help='network bottom layer downsampling')
    parser.add_argument('--input_size', nargs='+', type=int, required=True,
                        help='input size')
    parser.add_argument('--batch_size', type=int, default=8, help='batch size for testing')
    parser.add_argument('--num_workers', type=int, default=8, help='number of workers for input data loader')
    parser.add_argument('--load_intermediate_data', action='store_true', help='whether to load intermediate data')
    parser.add_argument('--data_root', type=str, required=True, help='path to the data for '
                                                                     'feature matching')
    parser.add_argument('--sequence_root', type=str, required=True,
                        help='root of the specific video sequence')
    parser.add_argument('--trained_model_path', type=str, required=True, help='path to the trained model')
    parser.add_argument('--feature_length', type=int, default=256, help='output channel dimension of network')
    parser.add_argument('--filter_growth_rate', type=int, default=10, help='filter growth rate of network')
    parser.add_argument('--max_feature_detection', type=int, default=3000,
                        help='max allowed number of detected features per frame')
    parser.add_argument('--cross_check_distance', type=float, default=5.0,
                        help='max cross check distance for valid matches')
    parser.add_argument('--id_list', nargs='+', type=int,
                        help='list patient ids')
    parser.add_argument('--gpu_id', type=int, default=0, help='gpu id for matching generation')
    parser.add_argument('--temporal_range', type=int, default=30, help='range for temporal sampling')
    parser.add_argument('--test_keypoint_num', type=int, default=200, help='number of keypoints used for quick '
                                                                           'spatial testing')
    parser.add_argument('--residual_threshold', type=float, default=5.0, help='pixel threshold for ransac estimation')
    parser.add_argument('--octave_layers', type=int, default=8)
    parser.add_argument('--contrast_threshold', type=float, default=0.00005)
    parser.add_argument('--edge_threshold', type=float, default=100)
    parser.add_argument('--sigma', type=float, default=1.1)
    parser.add_argument('--skip_interval', type=int, default=5,
                        help="number of skipping frames in searching state")
    parser.add_argument('--min_inlier_ratio', type=float, default=0.2,
                        help="minimum inlier ratio of ransac")
    parser.add_argument('--hysterisis_factor', type=float, default=0.7,
                        help="factor of the inlier ratio in the spatial_range state")


--image_downsampling
4.0
--network_downsampling
64
--input_size
256 320
--batch_size
1
--num_workers
1
--load_intermediate_data
--data_root
"/home/xingtong/Data/example_training_data_root"
--sequence_root
"/home/xingtong/Data/example_training_data_root/1/_start_002603_end_002984_stride_1000_segment_00"
--trained_model_path
"/home/xingtong/Data/Training/dense_descriptor_train_6_25_16_47/checkpoint_model_epoch_100_0.7375500110313298_0.8749000144898892_0.9466000116430223.pt"
--precompute_root
"/home/xingtong/Data/Training/precompute"
--feature_length
128
--filter_growth_rate
10
--max_feature_detection
3000
--cross_check_distance
3.0
--id_list
1
--gpu_id
0
--temporal_range
30
--test_keypoint_num
200
--residual_threshold
5.0
--octave_layers
8
--contrast_threshold
5e-5
--edge_threshold
100
--sigma
1.1
--skip_interval
5
--min_inlier_ratio
0.2
--hysterisis_factor
0.7