remove unused packages
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6
main.py
6
main.py
@ -15,18 +15,15 @@ import time
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from tensorboardX import SummaryWriter
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from tensorboardX import SummaryWriter
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from datasets import __datasets__
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from datasets import __datasets__
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from models import __models__
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from models import __models__
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from models import *
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from utils import *
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from utils import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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import skimage
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import gc
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import gc
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import datetime
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import cv2
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cudnn.benchmark = True
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cudnn.benchmark = True
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parser = argparse.ArgumentParser(description='Group-wise Correlation Stereo Network (GwcNet)')
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parser = argparse.ArgumentParser(description='Group-wise Correlation Stereo Network (GwcNet)')
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parser.add_argument('--model', default='gwcnet-g', help='select a model structure', choices=__models__.keys())
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parser.add_argument('--model', default='gwcnet-g', help='select a model structure', choices=__models__.keys())
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parser.add_argument('--maxdisp', type=int, default=192, help='maximum disparity')
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parser.add_argument('--dataset', required=True, help='dataset name', choices=__datasets__.keys())
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parser.add_argument('--dataset', required=True, help='dataset name', choices=__datasets__.keys())
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parser.add_argument('--datapath', required=True, help='data path')
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parser.add_argument('--datapath', required=True, help='data path')
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@ -36,7 +33,6 @@ parser.add_argument('--testlist', required=True, help='testing list')
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parser.add_argument('--lr', type=float, default=0.001, help='base learning rate')
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parser.add_argument('--lr', type=float, default=0.001, help='base learning rate')
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parser.add_argument('--batch_size', type=int, default=16, help='training batch size')
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parser.add_argument('--batch_size', type=int, default=16, help='training batch size')
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parser.add_argument('--test_batch_size', type=int, default=8, help='testing batch size')
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parser.add_argument('--test_batch_size', type=int, default=8, help='testing batch size')
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parser.add_argument('--maxdisp', type=int, default=192, help='maximum disparity')
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parser.add_argument('--epochs', type=int, required=True, help='number of epochs to train')
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parser.add_argument('--epochs', type=int, required=True, help='number of epochs to train')
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parser.add_argument('--lrepochs', type=str, required=True, help='the epochs to decay lr: the downscale rate')
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parser.add_argument('--lrepochs', type=str, required=True, help='the epochs to decay lr: the downscale rate')
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@ -4,7 +4,6 @@ import torch.nn as nn
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import torch.utils.data
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import torch.utils.data
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from torch.autograd import Variable
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from torch.autograd import Variable
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import torch.nn.functional as F
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import torch.nn.functional as F
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import math
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from models.submodule import *
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from models.submodule import *
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@ -5,7 +5,6 @@ import torch.utils.data
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from torch.autograd import Variable
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from torch.autograd import Variable
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from torch.autograd.function import Function
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from torch.autograd.function import Function
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import torch.nn.functional as F
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import torch.nn.functional as F
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import math
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import numpy as np
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import numpy as np
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@ -7,13 +7,7 @@ from torch.autograd import Variable
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import torchvision.utils as vutils
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import torchvision.utils as vutils
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import torch.nn.functional as F
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import torch.nn.functional as F
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import numpy as np
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import numpy as np
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import time
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from datasets import *
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from models import *
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import copy
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import copy
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import yaml
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import sys
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import argparse
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def make_iterative_func(func):
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def make_iterative_func(func):
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@ -6,10 +6,6 @@ from torch.autograd import Variable, Function
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import torch.nn.functional as F
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import torch.nn.functional as F
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import math
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import math
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import numpy as np
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import numpy as np
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import cv2
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# disable multi-thread
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cv2.setNumThreads(0)
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def gen_error_colormap():
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def gen_error_colormap():
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