SYMBOL INDEX (119 symbols across 12 files)

FILE: dataloaders/PairwiseImg_test.py
  function flip (line 20) | def flip(I,flip_p):
  function scale_im (line 26) | def scale_im(img_temp,scale):
  function scale_gt (line 30) | def scale_gt(img_temp,scale):
  function my_crop (line 34) | def my_crop(img,gt):
  class PairwiseImg (line 46) | class PairwiseImg(Dataset):
    method __init__ (line 49) | def __init__(self, train=True,
    method __len__ (line 106) | def __len__(self):
    method __getitem__ (line 109) | def __getitem__(self, idx):
    method make_img_gt_pair (line 141) | def make_img_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的
    method get_img_size (line 186) | def get_img_size(self):

FILE: dataloaders/PairwiseImg_video.py
  function flip (line 20) | def flip(I,flip_p):
  function scale_im (line 26) | def scale_im(img_temp,scale):
  function scale_gt (line 30) | def scale_gt(img_temp,scale):
  function my_crop (line 34) | def my_crop(img,gt):
  class PairwiseImg (line 46) | class PairwiseImg(Dataset):
    method __init__ (line 49) | def __init__(self, train=True,
    method __len__ (line 125) | def __len__(self):
    method __getitem__ (line 129) | def __getitem__(self, idx):
    method make_video_gt_pair (line 163) | def make_video_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的
    method get_img_size (line 207) | def get_img_size(self):
    method make_img_gt_pair (line 212) | def make_img_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的

FILE: dataloaders/PairwiseImg_video_test_try.py
  function flip (line 20) | def flip(I,flip_p):
  function scale_im (line 26) | def scale_im(img_temp,scale):
  function scale_gt (line 30) | def scale_gt(img_temp,scale):
  function my_crop (line 34) | def my_crop(img,gt):
  class PairwiseImg (line 46) | class PairwiseImg(Dataset):
    method __init__ (line 49) | def __init__(self, train=True,
    method __len__ (line 106) | def __len__(self):
    method __getitem__ (line 109) | def __getitem__(self, idx):
    method make_img_gt_pair (line 147) | def make_img_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的
    method get_img_size (line 192) | def get_img_size(self):

FILE: dataloaders/PairwiseImg_video_try.py
  function flip (line 20) | def flip(I,flip_p):
  function scale_im (line 26) | def scale_im(img_temp,scale):
  function scale_gt (line 30) | def scale_gt(img_temp,scale):
  function my_crop (line 34) | def my_crop(img,gt):
  class PairwiseImg (line 46) | class PairwiseImg(Dataset):
    method __init__ (line 49) | def __init__(self, train=True,
    method __len__ (line 125) | def __len__(self):
    method __getitem__ (line 129) | def __getitem__(self, idx):
    method make_video_gt_pair (line 174) | def make_video_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的
    method get_img_size (line 218) | def get_img_size(self):
    method make_img_gt_pair (line 223) | def make_img_gt_pair(self, idx): #这个函数存在的意义是为了getitem函数服务的

FILE: deeplab/siamese_model_conf.py
  function conv3x3 (line 15) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 21) | class BasicBlock(nn.Module):
    method __init__ (line 24) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 34) | def forward(self, x):
  class Bottleneck (line 53) | class Bottleneck(nn.Module):
    method __init__ (line 56) | def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=...
    method forward (line 70) | def forward(self, x):
  class ASPP (line 93) | class ASPP(nn.Module):
    method __init__ (line 94) | def __init__(self, dilation_series, padding_series, depth):
    method _make_stage_ (line 121) | def _make_stage_(self, dilation1, padding1):
    method forward (line 128) | def forward(self, x):
  class ResNet (line 160) | class ResNet(nn.Module):
    method __init__ (line 161) | def __init__(self, block, layers, num_classes):
    method _make_layer (line 184) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1):
    method _make_pred_layer (line 201) | def _make_pred_layer(self, block, dilation_series, padding_series, num...
    method forward (line 204) | def forward(self, x):
  class CoattentionModel (line 222) | class CoattentionModel(nn.Module):
    method __init__ (line 223) | def  __init__(self, block, layers, num_classes, all_channel=256, all_d...
    method forward (line 252) | def forward(self, input1, input2): #注意input2 可以是多帧图像
  function Res_Deeplab (line 299) | def Res_Deeplab(num_classes=2):
  function CoattentionNet (line 303) | def CoattentionNet(num_classes=2):

FILE: deeplab/siamese_model_conf_try_single.py
  function conv3x3 (line 16) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 22) | class BasicBlock(nn.Module):
    method __init__ (line 25) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 35) | def forward(self, x):
  class Bottleneck (line 54) | class Bottleneck(nn.Module):
    method __init__ (line 57) | def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=...
    method forward (line 71) | def forward(self, x):
  class ASPP (line 94) | class ASPP(nn.Module):
    method __init__ (line 95) | def __init__(self, dilation_series, padding_series, depth):
    method _make_stage_ (line 122) | def _make_stage_(self, dilation1, padding1):
    method forward (line 129) | def forward(self, x):
  class ResNet (line 161) | class ResNet(nn.Module):
    method __init__ (line 162) | def __init__(self, block, layers, num_classes):
    method _make_layer (line 185) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1):
    method _make_pred_layer (line 202) | def _make_pred_layer(self, block, dilation_series, padding_series, num...
    method forward (line 205) | def forward(self, x):
  class CoattentionModel (line 223) | class CoattentionModel(nn.Module):
    method __init__ (line 224) | def  __init__(self, block, layers, num_classes,  all_channel=256, all_...
    method forward (line 254) | def forward(self, input1, input2): #注意input2 可以是多帧图像
  function CoattentionNet (line 309) | def CoattentionNet(num_classes=2,nframes=2):

FILE: deeplab/utils.py
  function loss_calc (line 6) | def loss_calc(pred, label, ignore_label):
  function lr_poly (line 18) | def lr_poly(base_lr, iter, max_iter, power):
  function get_1x_lr_params (line 22) | def get_1x_lr_params(model):
  function get_10x_lr_params (line 40) | def get_10x_lr_params(model):
  function adjust_learning_rate (line 52) | def adjust_learning_rate(optimizer, i_iter, learning_rate, num_steps, po...

FILE: densecrf_apply_cvpr2019.py
  function worker (line 22) | def worker(scale, g_dim, g_factor,s_dim,C_dim,c_factor):

FILE: test_coattention_conf.py
  function get_arguments (line 37) | def get_arguments():
  function configure_dataset_model (line 57) | def configure_dataset_model(args):
  function convert_state_dict (line 89) | def convert_state_dict(state_dict):
  function sigmoid (line 108) | def sigmoid(inX):
  function main (line 111) | def main():

FILE: test_iteration_conf_group.py
  function get_arguments (line 37) | def get_arguments():
  function configure_dataset_model (line 57) | def configure_dataset_model(args):
  function convert_state_dict (line 74) | def convert_state_dict(state_dict):
  function sigmoid (line 93) | def sigmoid(inX):
  function main (line 96) | def main():

FILE: train_iteration_conf.py
  function get_arguments (line 35) | def get_arguments():
  function configure_dataset_init_model (line 78) | def configure_dataset_init_model(args):
  function adjust_learning_rate (line 133) | def adjust_learning_rate(optimizer, i_iter, epoch, max_iter):
  function loss_calc1 (line 147) | def loss_calc1(pred, label):
  function loss_calc2 (line 171) | def loss_calc2(pred, label):
  function get_1x_lr_params (line 184) | def get_1x_lr_params(model):
  function get_10x_lr_params (line 218) | def get_10x_lr_params(model):
  function lr_poly (line 242) | def lr_poly(base_lr, iter, max_iter, power, epoch):
  function netParams (line 252) | def netParams(model):
  function main (line 270) | def main():

FILE: train_iteration_conf_group.py
  function get_arguments (line 35) | def get_arguments():
  function configure_dataset_init_model (line 78) | def configure_dataset_init_model(args):
  function adjust_learning_rate (line 133) | def adjust_learning_rate(optimizer, i_iter, epoch, max_iter):
  function loss_calc1 (line 147) | def loss_calc1(pred, label):
  function loss_calc2 (line 171) | def loss_calc2(pred, label):
  function get_1x_lr_params (line 184) | def get_1x_lr_params(model):
  function get_10x_lr_params (line 218) | def get_10x_lr_params(model):
  function lr_poly (line 242) | def lr_poly(base_lr, iter, max_iter, power, epoch):
  function netParams (line 252) | def netParams(model):
  function main (line 270) | def main():