289 lines
14 KiB
Python
289 lines
14 KiB
Python
from __future__ import absolute_import
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from __future__ import print_function
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import argparse
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def init_parser():
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parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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parser.add_argument('--app', type=str, default='image', choices=['image', 'video'],
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help='application')
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parser.add_argument('--loss', type=str, default='softmax', choices=['softmax', 'triplet'],
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help='methodology')
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# ************************************************************
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# Datasets
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# ************************************************************
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parser.add_argument('--root', type=str, default='reid-data', required=True,
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help='root path to data directory')
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parser.add_argument('-s', '--sources', type=str, required=True, nargs='+',
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help='source datasets (delimited by space)')
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parser.add_argument('-t', '--targets', type=str, required=False, nargs='+',
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help='target datasets (delimited by space)')
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parser.add_argument('-j', '--workers', type=int, default=4,
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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('--split-id', type=int, default=0,
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help='split index (note: 0-based)')
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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('--train-sampler', type=str, default='RandomSampler',
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help='sampler for trainloader')
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parser.add_argument('--combineall', action='store_true',
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help='combine all data in a dataset (train+query+gallery) for training')
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# ************************************************************
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# Data augmentation
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# ************************************************************
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parser.add_argument('--random-erase', action='store_true',
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help='use random erasing for data augmentation')
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parser.add_argument('--color-jitter', action='store_true',
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help='randomly change the brightness, contrast and saturation')
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parser.add_argument('--color-aug', action='store_true',
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help='randomly alter the intensities of RGB channels')
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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('--pooling-method', 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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# Dataset-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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parser.add_argument('--market1501-500k', action='store_true',
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help='add 500k distractors to the gallery set for market1501')
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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', type=float, default=0.0003,
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help='initial learning rate')
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parser.add_argument('--weight-decay', type=float, default=5e-04,
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help='weight decay')
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# sgd
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parser.add_argument('--momentum', type=float, default=0.9,
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help='momentum factor for sgd and rmsprop')
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parser.add_argument('--sgd-dampening', type=float, default=0,
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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', type=float, default=0.99,
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help='rmsprop\'s smoothing constant')
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# adam/amsgrad
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parser.add_argument('--adam-beta1', type=float, default=0.9,
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help='exponential decay rate for adam\'s first moment')
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parser.add_argument('--adam-beta2', type=float, default=0.999,
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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', type=int, default=60,
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help='maximum epochs to run')
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parser.add_argument('--start-epoch', type=int, default=0,
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help='manual epoch number (useful when restart)')
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parser.add_argument('--batch-size', type=int, default=32,
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help='batch size')
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parser.add_argument('--fixbase-epoch', type=int, default=0,
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help='number of epochs to fix base layers')
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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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parser.add_argument('--staged-lr', action='store_true',
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help='set different lr to different layers')
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parser.add_argument('--new-layers', type=str, nargs='+', default=['classifier'],
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help='newly added layers with default lr')
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parser.add_argument('--base-lr-mult', type=float, default=0.1,
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help='learning rate multiplier for base layers')
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# ************************************************************
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# Learning rate scheduler options
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# ************************************************************
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parser.add_argument('--lr-scheduler', type=str, default='multi_step',
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help='learning rate scheduler (see lr_schedulers.py)')
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parser.add_argument('--stepsize', type=int, default=[20, 40], nargs='+',
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help='stepsize to decay learning rate')
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parser.add_argument('--gamma', type=float, default=0.1,
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help='learning rate decay')
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# ************************************************************
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# Cross entropy loss
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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
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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('--weight-t', type=float, default=1,
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help='weight to balance hard triplet loss')
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parser.add_argument('--weight-x', type=float, default=1,
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help='weight to balance cross entropy 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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help='model architecture')
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parser.add_argument('--no-pretrained', action='store_true',
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help='do not load pretrained weights')
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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 do not 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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parser.add_argument('--dist-metric', type=str, default='euclidean',
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help='distance metric')
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parser.add_argument('--normalize-feature', action='store_true',
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help='normalize feature vectors before calculating distance')
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parser.add_argument('--ranks', type=str, default=[1, 5, 10, 20], nargs='+',
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help='cmc ranks')
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parser.add_argument('--rerank', action='store_true',
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help='use person re-ranking (by Zhong et al. CVPR2017)')
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parser.add_argument('--visrank', action='store_true',
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help='visualize ranked results, only available in evaluation mode')
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parser.add_argument('--visrank-topk', type=int, default=20,
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help='visualize topk ranks')
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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=20,
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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', type=str, default='0',
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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')
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return parser
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def imagedata_kwargs(parsed_args):
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return {
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'root': parsed_args.root,
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'sources': parsed_args.sources,
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'targets': parsed_args.targets,
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'height': parsed_args.height,
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'width': parsed_args.width,
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'random_erase': parsed_args.random_erase,
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'color_jitter': parsed_args.color_jitter,
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'color_aug': parsed_args.color_aug,
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'use_cpu': parsed_args.use_cpu,
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'split_id': parsed_args.split_id,
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'combineall': parsed_args.combineall,
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'batch_size': parsed_args.batch_size,
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'workers': parsed_args.workers,
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'num_instances': parsed_args.num_instances,
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'train_sampler': parsed_args.train_sampler,
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# image
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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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'market1501_500k': parsed_args.market1501_500k,
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}
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def videodata_kwargs(parsed_args):
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return {
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'root': parsed_args.root,
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'sources': parsed_args.sources,
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'targets': parsed_args.targets,
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'height': parsed_args.height,
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'width': parsed_args.width,
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'random_erase': parsed_args.random_erase,
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'color_jitter': parsed_args.color_jitter,
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'color_aug': parsed_args.color_aug,
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'use_cpu': parsed_args.use_cpu,
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'split_id': parsed_args.split_id,
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'combineall': parsed_args.combineall,
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'batch_size': parsed_args.batch_size,
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'workers': parsed_args.workers,
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'num_instances': parsed_args.num_instances,
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'train_sampler': parsed_args.train_sampler,
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# video
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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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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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'staged_lr': parsed_args.staged_lr,
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'new_layers': parsed_args.new_layers,
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'base_lr_mult': parsed_args.base_lr_mult
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}
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def lr_scheduler_kwargs(parsed_args):
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return {
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'lr_scheduler': parsed_args.lr_scheduler,
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'stepsize': parsed_args.stepsize,
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'gamma': parsed_args.gamma
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}
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def engine_run_kwargs(parsed_args):
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return {
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'save_dir': parsed_args.save_dir,
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'max_epoch': parsed_args.max_epoch,
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'start_epoch': parsed_args.start_epoch,
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'fixbase_epoch': parsed_args.fixbase_epoch,
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'open_layers': parsed_args.open_layers,
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'start_eval': parsed_args.start_eval,
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'eval_freq': parsed_args.eval_freq,
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'test_only': parsed_args.evaluate,
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'print_freq': parsed_args.print_freq,
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'dist_metric': parsed_args.dist_metric,
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'normalize_feature': parsed_args.normalize_feature,
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'visrank': parsed_args.visrank,
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'visrank_topk': parsed_args.visrank_topk,
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'use_metric_cuhk03': parsed_args.use_metric_cuhk03,
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'ranks': parsed_args.ranks,
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'rerank': parsed_args.rerank
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} |