SYMBOL INDEX (51 symbols across 10 files)

FILE: data/dataloader.py
  function random_horizontal_flip (line 14) | def random_horizontal_flip(imgs):
  function random_rotate (line 20) | def random_rotate(imgs):
  function CheckImageFile (line 33) | def CheckImageFile(filename):
  function ImageTransform (line 36) | def ImageTransform(loadSize):
  class ErasingData (line 42) | class ErasingData(Dataset):
    method __init__ (line 43) | def __init__(self, dataRoot, loadSize, training=True):
    method __getitem__ (line 51) | def __getitem__(self, index):
    method __len__ (line 73) | def __len__(self):
  class devdata (line 76) | class devdata(Dataset):
    method __init__ (line 77) | def __init__(self, dataRoot, gtRoot, loadSize=512):
    method __getitem__ (line 86) | def __getitem__(self, index):
    method __len__ (line 97) | def __len__(self):

FILE: evaluatuion.py
  function ssim (line 39) | def ssim(img1, img2, cs_map=False):
  function msssim (line 75) | def msssim(img1, img2):
  function ImageTransform (line 109) | def ImageTransform(loadSize, cropSize):
  function visual (line 117) | def visual(image):

FILE: gauss.py
  function gaussian2 (line 9) | def gaussian2(size, sigma):
  function fspecial_gauss (line 24) | def fspecial_gauss(size, sigma):
  function main (line 31) | def main():

FILE: loss/Loss.py
  function gram_matrix (line 10) | def gram_matrix(feat):
  function visual (line 18) | def visual(image):
  function dice_loss (line 22) | def dice_loss(input, target):
  class LossWithGAN_STE (line 38) | class LossWithGAN_STE(nn.Module):
    method __init__ (line 39) | def __init__(self, logPath, extractor, Lamda, lr, betasInit=(0.5, 0.9)):
    method forward (line 50) | def forward(self, input, mask, x_o1,x_o2,x_o3,output,mm, gt, count, ep...

FILE: models/Model.py
  class VGG16FeatureExtractor (line 6) | class VGG16FeatureExtractor(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 20) | def forward(self, image):

FILE: models/discriminator.py
  class Discriminator_STE (line 6) | class Discriminator_STE(nn.Module):
    method __init__ (line 7) | def __init__(self, inputChannels):
    method forward (line 33) | def forward(self, input, masks):

FILE: models/networks.py
  function get_pad (line 6) | def get_pad(in_,  ksize, stride, atrous=1):
  class ConvWithActivation (line 10) | class ConvWithActivation(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 22) | def forward(self, input):
  class DeConvWithActivation (line 29) | class DeConvWithActivation(torch.nn.Module):
    method __init__ (line 33) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 41) | def forward(self, input):

FILE: models/sa_gan.py
  function img2photo (line 9) | def img2photo(imgs):
  function visual (line 12) | def visual(imgs):
  class Residual (line 16) | class Residual(nn.Module):
    method __init__ (line 17) | def __init__(self, in_channels, out_channels, same_shape=True, **kwargs):
    method forward (line 31) | def forward(self,x):
  class ASPP (line 40) | class ASPP(nn.Module):
    method __init__ (line 41) | def __init__(self, in_channel=512, depth=256):
    method forward (line 53) | def forward(self, x):
  class STRnet2 (line 72) | class STRnet2(nn.Module):
    method __init__ (line 73) | def __init__(self, n_in_channel=3):
    method forward (line 173) | def forward(self, x):

FILE: test_image_STE.py
  function visual (line 38) | def visual(image):

FILE: train_STE.py
  function visual (line 41) | def visual(image):