Function config_parser

opt.py:3–96

(cmd=None)

import configargparse

def config_parser(cmd=None):
    parser = configargparse.ArgumentParser()
    parser.add_argument('--config', is_config_file=True,
                        help='config file path')
    parser.add_argument("--expname", type=str,
                        help='experiment name')
    parser.add_argument("--basedir", type=str, default='./logs/',
                        help='where to store ckpts and logs')
    parser.add_argument("--datadir", type=str, default='./data/llff/fern',
                        help='input data directory')
    parser.add_argument('--with_depth', action='store_true')
    parser.add_argument('--with_depth_loss', action='store_true')
    parser.add_argument('--with_rgb_loss', action='store_true')
    parser.add_argument('--imgScale_train', type=float, default=1.0)
    parser.add_argument('--imgScale_test', type=float, default=1.0)
    parser.add_argument('--img_downscale', type=float, default=1.0)
    parser.add_argument('--pad', type=int, default=24)

    # loader options
    parser.add_argument("--batch_size", type=int, default=1024)
    parser.add_argument("--num_epochs", type=int, default=8)
    parser.add_argument("--pts_dim", type=int, default=3)
    parser.add_argument("--dir_dim", type=int, default=3)
    parser.add_argument("--alpha_feat_dim", type=int, default=8)
    parser.add_argument('--net_type', type=str, default='v0')
    parser.add_argument('--dataset_name', type=str, default='blender',
                        choices=['dtu', 'blender', 'llff', 'dtu_ft'])
    parser.add_argument('--use_color_volume', default=False, action="store_true",
                        help='project colors into a volume without indexing from image everytime')
    parser.add_argument('--use_density_volume', default=False, action="store_true",
                        help='point sampling with density')

    # training options
    parser.add_argument("--netdepth", type=int, default=6,
                        help='layers in network')
    parser.add_argument("--netwidth", type=int, default=128,
                        help='channels per layer')
    parser.add_argument("--netdepth_fine", type=int, default=6,
                        help='layers in fine network')
    parser.add_argument("--netwidth_fine", type=int, default=128,
                        help='channels per layer in fine network')
    parser.add_argument("--lrate", type=float, default=5e-4,
                        help='learning rate')
    parser.add_argument('--decay_step', nargs='+', type=int, default=[5000, 8000, 9000],
                        help='scheduler decay step')
    parser.add_argument('--decay_gamma', type=float, default=0.5,
                        help='learning rate decay amount')
    parser.add_argument('--lr_scheduler', type=str, default='steplr',
                        help='scheduler type',
                        choices=['steplr', 'cosine', 'poly'])
    parser.add_argument('--warmup_epochs', type=int, default=0,
                        help='Gradually warm-up(increasing) learning rate in optimizer')

    parser.add_argument("--chunk", type=int, default=1024,
                        help='number of rays processed in parallel, decrease if running out of memory')
    parser.add_argument("--netchunk", type=int, default=1024,
                        help='number of pts sent through network in parallel, decrease if running out of memory')
    parser.add_argument("--ckpt", type=str, default=None,