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args.py
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import argparse
import criteria
from metrics import Result
def parser():
parser = argparse.ArgumentParser(description='Polarizaiton Densification')
# Parameter
parser.add_argument('--raw-pattern', '-rp',
default='x16',
type=str,
choices=['conv','x4','x16','x64'],
help="sensor raw pattern, [conv(entional)/x4/x16/x64] (default: x16)")
parser.add_argument('--ps',
default=0.35,
type=float,
metavar='PS',
help='polar pixel sensitivity (default: 0.35)')
# Network Parameter
parser.add_argument('--refine-input', '-ri',
default=6,
type=int,
metavar='N',
help='RGB refine input [0~7] (default: 6)')
parser.add_argument('--refine-model', '-rm',
default=0,
type=int,
metavar='N',
help='RGB refine model [0,1] (default: 0)')
parser.add_argument('--comp-input-rgb', '-cir',
default=1,
type=int,
metavar='N',
help='Polarizaiton compensation input (RGB) [0,1] (default: 1)')
parser.add_argument('--comp-input-extra', '-cie',
default=2,
type=int,
metavar='N',
help='Polarization compensation input (extra) [0~3] (default: 2)')
parser.add_argument('--comp-model', '-cm',
default=1,
type=int,
metavar='N',
help='Polarization compensation model [0,1] (default: 1)')
# Hyper Parameter
parser.add_argument('--seed', '-se',
default=-1,
type=int,
metavar='N',
help='seed value. if -1, random seed (default: -1)')
parser.add_argument('--epochs',
default=30,
type=int,
metavar='N',
help='number of total epochs to run (default: 30)')
parser.add_argument('--batch-size', '-b',
default=1,
type=int,
help='mini-batch size (default: 1)')
parser.add_argument('--lr', '--learning-rate', '-lr',
default=1e-3,
type=float,
metavar='LR',
help='initial learning rate (default 1e-3)')
parser.add_argument('--weight-decay', '-wd',
default=1e-6,
type=float,
metavar='W',
help='weight decay (default: 1e-6)')
parser.add_argument('--train-num',
default=0,
type=int,
help='the number of train data, 0 is all (default: 0)')
parser.add_argument('--train-random',
action="store_true",
default=False,
help='random pickup for training data (default: false)')
parser.add_argument('--s0-8bit',
action="store_true",
default=False,
help='s0 bit length precision (default: false)')
# Loss Function
parser.add_argument('-c',
'--criterion',
default='l1_s12',
choices=['l1_s12','l2_s12','l1','l2'],
help='PCN loss function, l1 and l2 calculate s012 (default: l1_S12)')
parser.add_argument('-crgb',
'--rgb-criterion',
default='l2',
choices=['l2','l1'],
help='RGBRN loss function: (default: l2)')
parser.add_argument('--rank-metric',
type=str,
default='rmse',
choices=['rmse', 'mse', 'mae', 'psnr'],
help='metrics for which best result is saved (default: rmse)')
parser.add_argument('--rank-metric-domain',
type=str,
default='s012',
choices=['s12', 's012'],
help='domain of metrics for which best result is saved (default: s012)')
# Paths
parser.add_argument('--data-folder',
default='../data/rsp_dataset/x16/',
type=str,
metavar='PATH',
help='data folder (default: "../data/rsp_dataset/x16/")')
parser.add_argument('--gt-folder',
default='../data/rsp_dataset/gt/',
type=str,
metavar='PATH',
help='ground truth folder (default: "../data/rsp_dataset/gt/")')
parser.add_argument('--result',
default='../data/results/',
type=str,
metavar='PATH',
help='result folder (default: "../data/results/")')
parser.add_argument('--source-directory',
default='.',
type=str,
metavar='PATH',
help='source code directory for backup (default: .)')
parser.add_argument('--suffix',
default="",
type=str,
metavar='FN',
help='suffix of result folder name (default: none)')
# Augmentation Parameter
parser.add_argument('--not-random-crop',
action="store_true",
default=True,
help='Prohibit random cropping (default: true)')
parser.add_argument('-he', '--random-crop-height',
default=576,
type=int,
metavar='N',
help='random crop height (default: 576)')
parser.add_argument('-w',
'--random-crop-width',
default=768,
type=int,
metavar='N',
help='random crop height (default: 768)')
parser.add_argument('--jitter',
type=float,
default=0.0,
metavar='J',
help='color jitter for images, only apply when s0 is 8bit (default: 0.0)')
# Resume
parser.add_argument('--resume',
default='',
type=str,
metavar='PATH',
help='path to latest checkpoint (default: none)')
parser.add_argument('--start-epoch',
default=0,
type=int,
metavar='N',
help='manual epoch number, useful on restarts (default: 0)')
parser.add_argument('-ol', '--optimizer-load',
action="store_true",
default=False,
help='load optimizer when resumimg (default: false)')
parser.add_argument('--autoresume',
action="store_true",
default=False,
help='auto resume from latest checkpoint (default: false)')
parser.add_argument('--bestresume',
action="store_true",
default=False,
help='auto resume from best checkpoint (default: false)')
# Evaluation etc.
parser.add_argument('-e', '--evaluate',
default='',
type=str,
metavar='PATH',
help='use existing models for evaluation (default: none)')
parser.add_argument('--print-freq',
'-p',
default=10,
type=int,
metavar='N',
help='print frequency (default: 10)')
parser.add_argument('--vis-skip',
default=0,
type=int,
metavar='N',
help='skip of visualize comparison image (default: 0)')
parser.add_argument('--save-img-comp',
action="store_true",
default=False,
help='save image comparison for each epoch (default: false)')
parser.add_argument('--eval-each',
action="store_true",
default=False,
help='evaluation for each image (default: false)')
parser.add_argument('--save-interval',
default=1,
type=int,
metavar='N',
help='save model interval (default: 1)')
parser.add_argument('--val-interval',
default=1,
type=int,
metavar='N',
help='validation interval (default: 1)')
parser.add_argument('--train_eval',
action="store_true",
default=False,
help='evaluate when training phase (default: false)')
parser.add_argument('--disp-all',
action="store_true",
default=False,
help="output all results (default: false)")
parser.add_argument('--vis-dif',
action="store_true",
default=False,
help="visualize diffuse component (default: false)")
parser.add_argument('--evalcomp_num',
default=120,
type=int,
metavar='N',
help='number of the image for evaluation visualize (default: 120)')
# Debug
parser.add_argument('--small',
action="store_true",
default=False,
help='use small dataset (default: false)')
parser.add_argument('--small-rate',
default=0.01,
type=float,
metavar='SR',
help='rate of small dataset, use with "small" argument (default: 0.01)')
parser.add_argument('--s12gain',
default=50.0,
type=float,
help='s12gain for visualize (default: 50.0)')
# Others
parser.add_argument('--val-h',
default=576,
type=int,
metavar='N',
help='validation height (default: 576)')
parser.add_argument('--val-w',
default=768,
type=int,
metavar='N',
help='validation width (default: 768)')
parser.add_argument('--workers',
default=4,
type=int,
metavar='N',
help='number of data loading workers (default: 4)')
parser.add_argument('--cpu',
action="store_true",
default=False,
help='run on cpu (default: false)')
parser.add_argument('--gpu',
default=-1,
type=int,
metavar='N',
help='GPU device, if -1, use parallel mode (default: -1)')
args = parser.parse_args()
return args