SYMBOL INDEX (219 symbols across 26 files)

FILE: OE_eval.py
  function tensor2im (line 60) | def tensor2im(input_image, imtype=np.uint8):
  function calc_RMSE (line 81) | def calc_RMSE(real_img, fake_img):

FILE: OE_train.py
  function tensor2im (line 63) | def tensor2im(input_image, imtype=np.uint8):
  function calc_RMSE (line 84) | def calc_RMSE(real_img, fake_img):

FILE: data/__init__.py
  function find_dataset_using_name (line 7) | def find_dataset_using_name(dataset_name):
  function get_option_setter (line 31) | def get_option_setter(dataset_name):
  function create_dataset (line 36) | def create_dataset(opt):
  function CreateDataLoader (line 44) | def CreateDataLoader(opt):
  class CustomDatasetDataLoader (line 52) | class CustomDatasetDataLoader(BaseDataLoader):
    method name (line 53) | def name(self):
    method initialize (line 56) | def initialize(self, opt):
    method load_data (line 65) | def load_data(self):
    method __len__ (line 68) | def __len__(self):
    method __iter__ (line 71) | def __iter__(self):

FILE: data/base_data_loader.py
  class BaseDataLoader (line 1) | class BaseDataLoader():
    method __init__ (line 2) | def __init__(self):
    method initialize (line 5) | def initialize(self, opt):
    method load_data (line 9) | def load_data():

FILE: data/base_dataset.py
  class BaseDataset (line 6) | class BaseDataset(data.Dataset):
    method __init__ (line 7) | def __init__(self):
    method name (line 10) | def name(self):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train):
    method initialize (line 17) | def initialize(self, opt):
    method __len__ (line 20) | def __len__(self):
  function get_transform (line 24) | def get_transform(opt):
  function __adjust (line 55) | def __adjust(img):
  function __scale_width (line 75) | def __scale_width(img, target_width):
  function __print_size_warning (line 96) | def __print_size_warning(ow, oh, w, h):

FILE: data/expo_param_dataset.py
  class ExpoParamDataset (line 15) | class ExpoParamDataset(BaseDataset):
    method initialize (line 16) | def initialize(self, opt):
    method __getitem__ (line 46) | def __getitem__(self, index):
    method __len__ (line 165) | def __len__(self):
    method name (line 168) | def name(self):

FILE: data/image_folder.py
  function is_image_file (line 20) | def is_image_file(filename):
  function make_dataset (line 23) | def make_dataset(dir):
  function default_loader (line 36) | def default_loader(path):
  class ImageFolder (line 40) | class ImageFolder(data.Dataset):
    method __init__ (line 42) | def __init__(self, root, transform=None, return_paths=False,
    method __getitem__ (line 56) | def __getitem__(self, index):
    method __len__ (line 66) | def __len__(self):

FILE: data/srd_dataset.py
  class SRDDataset (line 15) | class SRDDataset(BaseDataset):
    method initialize (line 16) | def initialize(self, opt):
    method __getitem__ (line 49) | def __getitem__(self, index):
    method __len__ (line 167) | def __len__(self):
    method name (line 170) | def name(self):

FILE: models/Fusion_model.py
  function tensor2im (line 17) | def tensor2im(input_image, imtype=np.uint8):
  class L_TV (line 38) | class L_TV(nn.Module):
    method __init__ (line 39) | def __init__(self):
    method forward (line 41) | def forward(self, x):
  class GradientLoss (line 51) | class GradientLoss(nn.Module):
    method __init__ (line 52) | def __init__(self, loss_weight=1.0, reduction='mean'):
    method forward (line 60) | def forward(self, pred, target):
  class PoissonGradientLoss (line 84) | class PoissonGradientLoss(nn.Module):
    method __init__ (line 85) | def __init__(self, reduction='mean'):
    method forward (line 94) | def forward(self, source, target, blend, mask):
  class FusionModel (line 103) | class FusionModel(DistangleModel):
    method name (line 104) | def name(self):
    method modify_commandline_options (line 108) | def modify_commandline_options(parser, is_train=True):
    method initialize (line 118) | def initialize(self, opt):
    method set_input (line 166) | def set_input(self, input):
    method forward (line 178) | def forward(self):
    method backward (line 237) | def backward(self):
    method optimize_parameters (line 269) | def optimize_parameters(self):
    method zero_grad (line 279) | def zero_grad(self):
    method vis (line 285) | def vis(self, e, s, path='', eval=False):

FILE: models/Refine_model.py
  function tensor2im (line 17) | def tensor2im(input_image, imtype=np.uint8):
  class L_TV (line 33) | class L_TV(nn.Module):
    method __init__ (line 34) | def __init__(self):
    method forward (line 37) | def forward(self, x):
  class GradientLoss (line 47) | class GradientLoss(nn.Module):
    method __init__ (line 48) | def __init__(self, loss_weight=1.0, reduction='mean'):
    method forward (line 56) | def forward(self, pred, target):
  class PoissonGradientLoss (line 80) | class PoissonGradientLoss(nn.Module):
    method __init__ (line 81) | def __init__(self, reduction='mean'):
    method forward (line 89) | def forward(self, source, target, blend, mask):
  class RefineModel (line 98) | class RefineModel(DistangleModel):
    method name (line 99) | def name(self):
    method modify_commandline_options (line 103) | def modify_commandline_options(parser, is_train=True):
    method initialize (line 114) | def initialize(self, opt):
    method set_input (line 164) | def set_input(self, input):
    method forward (line 177) | def forward(self):
    method backward (line 246) | def backward(self):
    method optimize_parameters (line 271) | def optimize_parameters(self):
    method zero_grad (line 280) | def zero_grad(self):
    method vis (line 284) | def vis(self, e, s, path='', eval=False):

FILE: models/__init__.py
  function find_model_using_name (line 5) | def find_model_using_name(model_name):
  function get_option_setter (line 29) | def get_option_setter(model_name):
  function create_model (line 34) | def create_model(opt):

FILE: models/base_model.py
  class BaseModel (line 8) | class BaseModel():
    method modify_commandline_options (line 13) | def modify_commandline_options(parser, is_train):
    method train (line 17) | def train(self):
    method eval (line 24) | def eval(self):
    method name (line 31) | def name(self):
    method initialize (line 34) | def initialize(self, opt):
    method set_input (line 54) | def set_input(self, input):
    method get_prediction (line 64) | def get_prediction(self,input):
    method forward (line 73) | def forward(self):
    method setup (line 77) | def setup(self, opt, parser=None):
    method test (line 90) | def test(self):
    method get_image_paths (line 95) | def get_image_paths(self):
    method optimize_parameters (line 98) | def optimize_parameters(self):
    method update_learning_rate (line 102) | def update_learning_rate(self,loss=None):
    method get_current_visuals (line 113) | def get_current_visuals(self):
    method get_current_losses (line 133) | def get_current_losses(self):
    method save_networks (line 143) | def save_networks(self, epoch):
    method __patch_instance_norm_state_dict (line 156) | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i...
    method load_networks (line 170) | def load_networks(self, epoch, save_dir=None):
    method print_networks (line 201) | def print_networks(self, verbose):
    method set_requires_grad (line 214) | def set_requires_grad(self, nets, requires_grad=False):

FILE: models/distangle_model.py
  class DistangleModel (line 9) | class DistangleModel(BaseModel):
    method name (line 10) | def name(self):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train=True):
    method initialize (line 24) | def initialize(self, opt):
    method set_input (line 51) | def set_input(self, input):
    method forward (line 60) | def forward(self):
    method get_prediction (line 79) | def get_prediction(self,input):
    method backward_G (line 97) | def backward_G(self):
    method optimize_parameters (line 103) | def optimize_parameters(self):

FILE: models/loss_function.py
  function smooth_loss (line 5) | def smooth_loss(pred_map):

FILE: models/networks.py
  function get_norm_layer (line 11) | def get_norm_layer(norm_type='instance'):
  function get_scheduler (line 23) | def get_scheduler(optimizer, opt):
  function init_weights (line 42) | def init_weights(net, init_type='normal', gain=0.02):
  function init_net (line 66) | def init_net(net, init_type='normal', init_gain=0.02, gpu_ids=[]):
  function define_vgg (line 74) | def define_vgg(num_input,num_classes,init_type='normal', init_gain=0.02,...
  function define_G (line 85) | def define_G(input_nc, output_nc, ngf, netG, norm='batch', use_dropout=F...
  function define_D (line 115) | def define_D(input_nc, ndf, netD,
  class GANLoss (line 142) | class GANLoss(nn.Module):
    method __init__ (line 143) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
    method get_target_tensor (line 152) | def get_target_tensor(self, input, target_is_real):
    method __call__ (line 159) | def __call__(self, input, target_is_real):
  class ResnetGenerator (line 168) | class ResnetGenerator(nn.Module):
    method __init__ (line 169) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 212) | def forward(self, input):
  class ResnetBlock (line 217) | class ResnetBlock(nn.Module):
    method __init__ (line 218) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
    method build_conv_block (line 222) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
    method forward (line 254) | def forward(self, x):
  class UnetGenerator (line 263) | class UnetGenerator(nn.Module):
    method __init__ (line 264) | def __init__(self, input_nc, output_nc, num_downs, ngf=64,
    method forward (line 279) | def forward(self, input):
  class UnetSkipConnectionBlock (line 286) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 287) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 332) | def forward(self, x):
  class NLayerDiscriminator (line 340) | class NLayerDiscriminator(nn.Module):
    method __init__ (line 341) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method forward (line 383) | def forward(self, input):
  class PixelDiscriminator (line 387) | class PixelDiscriminator(nn.Module):
    method __init__ (line 388) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d, use_si...
    method forward (line 408) | def forward(self, input):

FILE: models/resnet.py
  function conv3x3 (line 27) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 33) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 38) | class BasicBlock(nn.Module):
    method __init__ (line 41) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 59) | def forward(self, x):
  class Bottleneck (line 78) | class Bottleneck(nn.Module):
    method __init__ (line 87) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 104) | def forward(self, x):
  class ResNet (line 127) | class ResNet(nn.Module):
    method my_load_state_dict (line 128) | def my_load_state_dict(self,state_dict):
    method __init__ (line 142) | def __init__(self, block, layers, num_classes=1000, zero_init_residual...
    method _make_layer (line 193) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method _forward_impl (line 217) | def _forward_impl(self, x):
    method forward (line 235) | def forward(self, x):
  function _resnet (line 239) | def _resnet(arch, block, layers, pretrained, progress, **kwargs):
  function resnet18 (line 248) | def resnet18(pretrained=False, progress=True, **kwargs):
  function resnet34 (line 260) | def resnet34(pretrained=False, progress=True, **kwargs):
  function resnet50 (line 272) | def resnet50(pretrained=False, progress=True, **kwargs):
  function resnet101 (line 284) | def resnet101(pretrained=False, progress=True, **kwargs):
  function resnet152 (line 296) | def resnet152(pretrained=False, progress=True, **kwargs):
  function resnext50_32x4d (line 308) | def resnext50_32x4d(pretrained=False, progress=True, **kwargs):
  function resnext101_32x8d (line 322) | def resnext101_32x8d(pretrained=False, progress=True, **kwargs):
  function wide_resnet50_2 (line 336) | def wide_resnet50_2(pretrained=False, progress=True, **kwargs):
  function wide_resnet101_2 (line 354) | def wide_resnet101_2(pretrained=False, progress=True, **kwargs):

FILE: models/vgg.py
  function set_parameter_requires_grad (line 14) | def set_parameter_requires_grad(model, feature_extracting):
  function create_vgg (line 19) | def create_vgg(num_ic,num_classes,use_pretrained=False,feature_extract=F...

FILE: options/PAMI_options.py
  class TrainOptions (line 4) | class TrainOptions(BaseOptions):
    method initialize (line 5) | def initialize(self, parser):

FILE: options/base_options.py
  class BaseOptions (line 9) | class BaseOptions():
    method __init__ (line 10) | def __init__(self):
    method initialize (line 13) | def initialize(self, parser):
    method gather_options (line 62) | def gather_options(self):
    method print_options (line 87) | def print_options(self, opt):
    method parse (line 107) | def parse(self):

FILE: options/test_options.py
  class TestOptions (line 4) | class TestOptions(BaseOptions):
    method initialize (line 5) | def initialize(self, parser):

FILE: options/train_options.py
  class TrainOptions (line 4) | class TrainOptions(BaseOptions):
    method initialize (line 5) | def initialize(self, parser):

FILE: util/get_data.py
  class GetData (line 11) | class GetData(object):
    method __init__ (line 29) | def __init__(self, technique='cyclegan', verbose=True):
    method _print (line 37) | def _print(self, text):
    method _get_options (line 42) | def _get_options(r):
    method _present_options (line 48) | def _present_options(self):
    method _download_data (line 58) | def _download_data(self, dataset_url, save_path):
    method get (line 81) | def get(self, save_path, dataset=None):

FILE: util/html.py
  class HTML (line 6) | class HTML:
    method __init__ (line 7) | def __init__(self, web_dir, title, reflesh=0):
    method get_image_dir (line 22) | def get_image_dir(self):
    method add_header (line 25) | def add_header(self, str):
    method add_table (line 29) | def add_table(self, border=1):
    method add_images (line 33) | def add_images(self, ims, txts, links, width=400):
    method save (line 45) | def save(self):

FILE: util/image_pool.py
  class ImagePool (line 5) | class ImagePool():
    method __init__ (line 6) | def __init__(self, pool_size):
    method query (line 12) | def query(self, images):

FILE: util/util.py
  function sdmkdir (line 8) | def sdmkdir(dir_name):
  function tensor2im (line 13) | def tensor2im(input_image, imtype=np.uint8,scale=None):
  function tensor2im_logc (line 31) | def tensor2im_logc(image_tensor, imtype=np.uint8,scale=255):
  function diagnose_network (line 42) | def diagnose_network(net, name='network'):
  function save_image (line 55) | def save_image(image_numpy, image_path):
  function print_numpy (line 60) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 70) | def mkdirs(paths):
  function mkdir (line 78) | def mkdir(path):

FILE: util/visualizer.py
  class Visualizer (line 8) | class Visualizer():
    method __init__ (line 9) | def __init__(self, opt):
    method display_current_results (line 33) | def display_current_results(self, visuals, epoch):
    method plot_current_losses (line 99) | def plot_current_losses(self, epoch, counter_ratio, opt, errors):
    method plot_test_errors (line 114) | def plot_test_errors(self, epoch, counter_ratio, opt, errors):
    method print_current_errors (line 137) | def print_current_errors(self, epoch, i, errors, t):
    method save_images (line 147) | def save_images(self, webpage, visuals, image_path):