from __future__ import absolute_import from __future__ import print_function import argparse def init_parser(): parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) # ************************************************************ # Method # ************************************************************ parser.add_argument('--application', type=str, default='image', choices=['image', 'video'], help='image-reid or video-reid') parser.add_argument('--method', type=str, default='softmax', help='methodology') # ************************************************************ # Datasets # ************************************************************ parser.add_argument('--root', type=str, default='data', help='root path to data directory') parser.add_argument('-s', '--source-names', type=str, required=True, nargs='+', help='source datasets (delimited by space)') parser.add_argument('-t', '--target-names', type=str, required=True, nargs='+', help='target datasets (delimited by space)') parser.add_argument('-j', '--workers', type=int, default=4, help='number of data loading workers (tips: 4 or 8 times number of gpus)') parser.add_argument('--split-id', type=int, default=0, help='split index (note: 0-based)') parser.add_argument('--height', type=int, default=256, help='height of an image') parser.add_argument('--width', type=int, default=128, help='width of an image') parser.add_argument('--train-sampler', type=str, default='RandomSampler', help='sampler for trainloader') parser.add_argument('--combineall', action='store_true', help='combine all data in a dataset (train+query+gallery) for training') # ************************************************************ # Data augmentation # ************************************************************ parser.add_argument('--random-erase', action='store_true', help='use random erasing for data augmentation') parser.add_argument('--color-jitter', action='store_true', help='randomly change the brightness, contrast and saturation') parser.add_argument('--color-aug', action='store_true', help='randomly alter the intensities of RGB channels') # ************************************************************ # Video datasets # ************************************************************ parser.add_argument('--seq-len', type=int, default=15, help='number of images to sample in a tracklet') parser.add_argument('--sample-method', type=str, default='evenly', help='how to sample images from a tracklet') parser.add_argument('--pooling-method', type=str, default='avg', choices=['avg', 'max'], help='how to pool features over a tracklet (for video reid)') # ************************************************************ # Dataset-specific setting # ************************************************************ parser.add_argument('--cuhk03-labeled', action='store_true', help='use labeled images, if false, use detected images') parser.add_argument('--cuhk03-classic-split', action='store_true', help='use classic split by Li et al. CVPR\'14') parser.add_argument('--use-metric-cuhk03', action='store_true', help='use cuhk03\'s metric for evaluation') parser.add_argument('--market1501-500k', action='store_true', help='add 500k distractors to the gallery set for market1501') # ************************************************************ # Optimization options # ************************************************************ parser.add_argument('--optim', type=str, default='adam', help='optimization algorithm (see optimizers.py)') parser.add_argument('--lr', type=float, default=0.0003, help='initial learning rate') parser.add_argument('--weight-decay', type=float, default=5e-04, help='weight decay') # sgd parser.add_argument('--momentum', type=float, default=0.9, help='momentum factor for sgd and rmsprop') parser.add_argument('--sgd-dampening', type=float, default=0, help='sgd\'s dampening for momentum') parser.add_argument('--sgd-nesterov', action='store_true', help='whether to enable sgd\'s Nesterov momentum') # rmsprop parser.add_argument('--rmsprop-alpha', type=float, default=0.99, help='rmsprop\'s smoothing constant') # adam/amsgrad parser.add_argument('--adam-beta1', type=float, default=0.9, help='exponential decay rate for adam\'s first moment') parser.add_argument('--adam-beta2', type=float, default=0.999, help='exponential decay rate for adam\'s second moment') # ************************************************************ # Training hyperparameters # ************************************************************ parser.add_argument('--max-epoch', type=int, default=60, help='maximum epochs to run') parser.add_argument('--start-epoch', type=int, default=0, help='manual epoch number (useful when restart)') parser.add_argument('--train-batch-size', type=int, default=32, help='training batch size') parser.add_argument('--test-batch-size', type=int, default=100, help='test batch size') parser.add_argument('--always-fixbase', action='store_true', help='always fix base network and only train specified layers') parser.add_argument('--fixbase-epoch', type=int, default=0, help='how many epochs to fix base network (only train randomly initialized classifier)') parser.add_argument('--open-layers', type=str, nargs='+', default=['classifier'], help='open specified layers for training while keeping others frozen') parser.add_argument('--staged-lr', action='store_true', help='set different lr to different layers') parser.add_argument('--new-layers', type=str, nargs='+', default=['classifier'], help='newly added layers with default lr') parser.add_argument('--base-lr-mult', type=float, default=0.1, help='learning rate multiplier for base layers') # ************************************************************ # Learning rate scheduler options # ************************************************************ parser.add_argument('--lr-scheduler', type=str, default='multi_step', help='learning rate scheduler (see lr_schedulers.py)') parser.add_argument('--stepsize', type=int, default=[20, 40], nargs='+', help='stepsize to decay learning rate') parser.add_argument('--gamma', type=float, default=0.1, help='learning rate decay') # ************************************************************ # Cross entropy loss-specific setting # ************************************************************ parser.add_argument('--label-smooth', action='store_true', help='use label smoothing regularizer in cross entropy loss') # ************************************************************ # Hard triplet loss-specific setting # ************************************************************ parser.add_argument('--margin', type=float, default=0.3, help='margin for triplet loss') parser.add_argument('--num-instances', type=int, default=4, help='number of instances per identity') parser.add_argument('--weight-t', type=float, default=1, help='weight to balance hard triplet loss') parser.add_argument('--weight-x', type=float, default=1, help='weight to balance cross entropy loss') # ************************************************************ # Architecture # ************************************************************ parser.add_argument('-a', '--arch', type=str, default='resnet50') parser.add_argument('--no-pretrained', action='store_true', help='do not load pretrained weights') # ************************************************************ # Test settings # ************************************************************ parser.add_argument('--load-weights', type=str, default='', help='load pretrained weights but ignore layers that do not match in size') parser.add_argument('--evaluate', action='store_true', help='evaluate only') parser.add_argument('--eval-freq', type=int, default=-1, help='evaluation frequency (set to -1 to test only in the end)') parser.add_argument('--start-eval', type=int, default=0, help='start to evaluate after a specific epoch') parser.add_argument('--dist-metric', type=str, default='euclidean', help='distance metric') # ************************************************************ # Miscs # ************************************************************ parser.add_argument('--print-freq', type=int, default=10, help='print frequency') parser.add_argument('--seed', type=int, default=1, help='manual seed') parser.add_argument('--resume', type=str, default='', metavar='PATH', help='resume from a checkpoint') parser.add_argument('--save-dir', type=str, default='log', help='path to save log and model weights') parser.add_argument('--use-cpu', action='store_true', help='use cpu') parser.add_argument('--gpu-devices', type=str, default='0', help='gpu device ids for CUDA_VISIBLE_DEVICES') parser.add_argument('--use-avai-gpus', action='store_true', help='use available gpus instead of specified devices (useful when using managed clusters)') parser.add_argument('--visrank', action='store_true', help='visualize ranked results, only available in evaluation mode') parser.add_argument('--visrank-topk', type=int, default=20, help='visualize topk ranks') return parser