Function config_parser

script/dm/options.py:2–138

()

import configargparse
def config_parser():
    parser = configargparse.ArgumentParser()
    parser.add_argument("-f", "--fff", help="a dummy argument to fool ipython", default="1")
    parser.add_argument("--multi_gpu", action='store_true', help='use multiple gpu on the server')

    # 7Scenes
    parser.add_argument("--trainskip", type=int, default=1, help='will load 1/N images from train sets, useful for large datasets like 7 Scenes')
    parser.add_argument("--df", type=float, default=1., help='image downscale factor')
    parser.add_argument("--reduce_embedding", type=int, default=-1, help='fourier embedding mode: -1: paper default, \
                                                                        0: reduce by half, 1: remove embedding, 2: DNeRF embedding')
    parser.add_argument("--epochToMaxFreq", type=int, default=-1, help='DNeRF embedding mode: (based on DNeRF paper): \
                                                                        hyper-parameter for when α should reach the maximum number of frequencies m')
    parser.add_argument("--render_pose_only", action='store_true', help='render a spiral video for 7 Scene')
    parser.add_argument("--save_pose_avg_stats", action='store_true', help='save a pose avg stats to unify NeRF, posenet, nerf tracking training')
    parser.add_argument("--load_pose_avg_stats", action='store_true', help='load precomputed pose avg stats to unify NeRF, posenet, nerf tracking training')
    parser.add_argument("--finetune_unlabel", action='store_true', help='finetune unlabeled sequence like MapNet')
    parser.add_argument("--i_eval",   type=int, default=50, help='frequency of eval posenet result')
    parser.add_argument("--save_all_ckpt", action='store_true', help='save all ckpts for each epoch')
    parser.add_argument("--train_local_nerf", type=int, default=-1, help='train local NeRF with ith training sequence only, ie. Stairs can pick 0~3')
    parser.add_argument("--render_video_train", action='store_true', help='render train set NeRF and save as video, make sure i_eval is True')
    parser.add_argument("--render_video_test", action='store_true', help='render val set NeRF and save as video,  make sure i_eval is True')
    parser.add_argument("--no_DNeRF_viewdir", action='store_true', default=False, help='will not use DNeRF in viewdir encoding')
    parser.add_argument("--val_on_psnr", action='store_true', default=False, help='EarlyStopping with max validation psnr')
    parser.add_argument("--feature_matching_lvl", nargs='+', type=int, default=[0,1,2], 
                        help='lvl of features used for feature matching, default use lvl 0, 1, 2')

    ##################### PoseNet Settings ########################
    parser.add_argument("--pose_only", type=int, default=0, help='posenet type to train, \
                        1: train baseline posenet, 2: posenet+nerf manual optimize, \
                        3: featurenet,')
    parser.add_argument("--learning_rate", type=float, default=0.00001, help='learning rate')
    parser.add_argument("--batch_size", type=int, default=1, help='train posenet only')
    parser.add_argument("--pretrain_model_path", type=str, default='', help='model path of pretrained pose regrssion model')
    parser.add_argument("--pretrain_featurenet_path", type=str, default='', help='model path of pretrained featurenet model')
    parser.add_argument("--model_name", type=str, help='pose model output folder name')
    parser.add_argument("--combine_loss", action='store_true',
                        help='combined l2 pose loss + rgb mse loss')
    parser.add_argument("--combine_loss_w", nargs='+', type=float, default=[0.5, 0.5], 
                        help='weights of combined loss ex, [0.5 0.5], \
                        default None, only use when combine_loss is True')
    parser.add_argument("--patience", nargs='+', type=int, default=[200, 50], help='set training schedule for patience [EarlyStopping, reduceLR]')
    parser.add_argument("--resize_factor", type=int, default=2, help='image resize downsample ratio')
    parser.add_argument("--freezeBN", action='store_true', help='Freeze the Batch Norm layer at training PoseNet')
    parser.add_argument("--preprocess_ImgNet", action='store_true', help='Normalize input data for PoseNet')
    parser.add_argument("--eval", action='store_true', help='eval model')
    parser.add_argument("--no_save_multiple", action='store_true', help='default, save multiple posenet model, if true, save only one posenet model')
    parser.add_argument("--resnet34", action='store_true', default=False, help='use resnet34 backbone instead of mobilenetV2')
    parser.add_argument("--efficientnet", action='store_true', default=False, help='use efficientnet-b3 backbone instead of mobilenetV2')
    parser.add_argument("--efficientnet_block", type=int, default=6, help='choose which features from feature block (0-6) of efficientnet to use')
    parser.add_argument("--dropout", type=float, default=0.5, help='dropout rate for resnet34 backbone')
    parser.add_argument("--DFNet", action='store_true', default=False, help='use DFNet')
    parser.add_argument("--DFNet_s", action='store_true', default=False, help='use accelerated DFNet, performance is similar to DFNet but slightly faster')
    parser.add_argument("--val_batch_size", type=int, default=1, help='batch_size for validation, higher number leads to faster speed')

    ##################### NeRF Settings ########################
    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')