213 lines
10 KiB
Python
213 lines
10 KiB
Python
import argparse
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def argument_parser():
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parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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# ************************************************************
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# Datasets (general)
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# ************************************************************
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parser.add_argument('--root', type=str, default='data',
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help="root path to data directory")
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parser.add_argument('-s', '--source-names', type=str, required=True, nargs='+',
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help="source datasets (delimited by space)")
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parser.add_argument('-t', '--target-names', type=str, required=True, nargs='+',
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help="target datasets (delimited by space)")
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parser.add_argument('-j', '--workers', default=4, type=int,
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help="number of data loading workers (tips: 4 or 8 times number of gpus)")
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parser.add_argument('--height', type=int, default=256,
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help="height of an image")
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parser.add_argument('--width', type=int, default=128,
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help="width of an image")
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parser.add_argument('--split-id', type=int, default=0,
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help="split index (note: 0-based)")
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parser.add_argument('--train-sampler', type=str, default='',
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help="sampler for trainloader")
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# ************************************************************
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# Video datasets
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# ************************************************************
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parser.add_argument('--seq-len', type=int, default=15,
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help="number of images to sample in a tracklet")
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parser.add_argument('--sample-method', type=str, default='evenly',
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help="how to sample images from a tracklet")
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parser.add_argument('--pool-tracklet-features', type=str, default='avg', choices=['avg', 'max'],
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help="how to pool features over a tracklet (for video reid)")
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# ************************************************************
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# CUHK03-specific setting
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# ************************************************************
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parser.add_argument('--cuhk03-labeled', action='store_true',
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help="use labeled images, if false, use detected images")
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parser.add_argument('--cuhk03-classic-split', action='store_true',
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help="use classic split by Li et al. CVPR'14")
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parser.add_argument('--use-metric-cuhk03', action='store_true',
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help="use cuhk03's metric for evaluation")
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# ************************************************************
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# Optimization options
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# ************************************************************
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parser.add_argument('--optim', type=str, default='adam',
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help="optimization algorithm (see optimizers.py)")
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parser.add_argument('--lr', default=0.0003, type=float,
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help="initial learning rate")
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parser.add_argument('--weight-decay', default=5e-04, type=float,
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help="weight decay")
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# sgd
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parser.add_argument('--momentum', default=0.9, type=float,
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help="momentum factor for sgd and rmsprop")
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parser.add_argument('--sgd-dampening', default=0, type=float,
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help="sgd's dampening for momentum")
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parser.add_argument('--sgd-nesterov', action='store_true',
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help="whether to enable sgd's Nesterov momentum")
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# rmsprop
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parser.add_argument('--rmsprop-alpha', default=0.99, type=float,
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help="rmsprop's smoothing constant")
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# adam/amsgrad
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parser.add_argument('--adam-beta1', default=0.9, type=float,
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help="exponential decay rate for adam's first moment")
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parser.add_argument('--adam-beta2', default=0.999, type=float,
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help="exponential decay rate for adam's second moment")
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# ************************************************************
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# Training hyperparameters
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# ************************************************************
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parser.add_argument('--max-epoch', default=60, type=int,
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help="maximum epochs to run")
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parser.add_argument('--start-epoch', default=0, type=int,
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help="manual epoch number (useful when restart)")
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parser.add_argument('--stepsize', default=[20, 40], nargs='+', type=int,
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help="stepsize to decay learning rate")
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parser.add_argument('--gamma', default=0.1, type=float,
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help="learning rate decay")
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parser.add_argument('--train-batch-size', default=32, type=int,
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help="training batch size")
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parser.add_argument('--test-batch-size', default=100, type=int,
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help="test batch size")
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parser.add_argument('--fixbase', action='store_true',
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help="always fix base network")
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parser.add_argument('--fixbase-epoch', type=int, default=0,
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help="how many epochs to fix base network (only train randomly initialized classifier)")
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parser.add_argument('--open-layers', type=str, nargs='+', default=['classifier'],
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help="open specified layers for training while keeping others frozen")
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# ************************************************************
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# Cross entropy loss-specific setting
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# ************************************************************
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parser.add_argument('--label-smooth', action='store_true',
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help="use label smoothing regularizer in cross entropy loss")
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# ************************************************************
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# Hard triplet loss-specific setting
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# ************************************************************
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parser.add_argument('--margin', type=float, default=0.3,
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help="margin for triplet loss")
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parser.add_argument('--num-instances', type=int, default=4,
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help="number of instances per identity")
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parser.add_argument('--htri-only', action='store_true',
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help="only use hard triplet loss")
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parser.add_argument('--lambda-xent', type=float, default=1,
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help="weight to balance cross entropy loss")
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parser.add_argument('--lambda-htri', type=float, default=1,
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help="weight to balance hard triplet loss")
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# ************************************************************
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# Architecture
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# ************************************************************
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parser.add_argument('-a', '--arch', type=str, default='resnet50')
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# ************************************************************
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# Test settings
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# ************************************************************
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parser.add_argument('--load-weights', type=str, default='',
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help="load pretrained weights but ignore layers that don't match in size")
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parser.add_argument('--evaluate', action='store_true',
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help="evaluate only")
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parser.add_argument('--eval-freq', type=int, default=-1,
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help="evaluation frequency (set to -1 to test only in the end)")
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parser.add_argument('--start-eval', type=int, default=0,
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help="start to evaluate after a specific epoch")
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# ************************************************************
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# Miscs
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# ************************************************************
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parser.add_argument('--print-freq', type=int, default=10,
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help="print frequency")
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parser.add_argument('--seed', type=int, default=1,
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help="manual seed")
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parser.add_argument('--resume', type=str, default='', metavar='PATH',
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help="resume from a checkpoint")
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parser.add_argument('--save-dir', type=str, default='log',
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help="path to save log and model weights")
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parser.add_argument('--use-cpu', action='store_true',
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help="use cpu")
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parser.add_argument('--gpu-devices', default='0', type=str,
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help='gpu device ids for CUDA_VISIBLE_DEVICES')
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parser.add_argument('--use-avai-gpus', action='store_true',
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help="use available gpus instead of specified devices (useful when using managed clusters)")
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parser.add_argument('--visualize-ranks', action='store_true',
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help="visualize ranked results, only available in evaluation mode")
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return parser
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def image_dataset_kwargs(parsed_args):
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"""
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Build kwargs for ImageDataManager in data_manager.py from
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the parsed command-line arguments.
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"""
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return {
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'source_names': parsed_args.source_names,
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'target_names': parsed_args.target_names,
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'root': parsed_args.root,
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'split_id': parsed_args.split_id,
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'height': parsed_args.height,
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'width': parsed_args.width,
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'train_batch_size': parsed_args.train_batch_size,
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'test_batch_size': parsed_args.test_batch_size,
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'workers': parsed_args.workers,
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'train_sampler': parsed_args.train_sampler,
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'num_instances': parsed_args.num_instances,
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'cuhk03_labeled': parsed_args.cuhk03_labeled,
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'cuhk03_classic_split': parsed_args.cuhk03_classic_split
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}
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def video_dataset_kwargs(parsed_args):
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"""
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Build kwargs for VideoDataManager in data_manager.py from
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the parsed command-line arguments.
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"""
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return {
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'source_names': parsed_args.source_names,
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'target_names': parsed_args.target_names,
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'root': parsed_args.root,
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'split_id': parsed_args.split_id,
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'height': parsed_args.height,
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'width': parsed_args.width,
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'train_batch_size': parsed_args.train_batch_size,
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'test_batch_size': parsed_args.test_batch_size,
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'workers': parsed_args.workers,
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'seq_len': parsed_args.seq_len,
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'sample_method': parsed_args.sample_method
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}
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def optimizer_kwargs(parsed_args):
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"""
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Build kwargs for optimizer in optimizer.py from
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the parsed command-line arguments.
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"""
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return {
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'optim': parsed_args.optim,
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'lr': parsed_args.lr,
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'weight_decay': parsed_args.weight_decay,
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'momentum': parsed_args.momentum,
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'sgd_dampening': parsed_args.sgd_dampening,
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'sgd_nesterov': parsed_args.sgd_nesterov,
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'rmsprop_alpha': parsed_args.rmsprop_alpha,
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'adam_beta1': parsed_args.adam_beta1,
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'adam_beta2': parsed_args.adam_beta2
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} |