SYMBOL INDEX (278 symbols across 22 files)

FILE: HiFi_Net.py
  class HiFi_Net (line 18) | class HiFi_Net():
    method __init__ (line 24) | def __init__(self):
    method _transform_image (line 42) | def _transform_image(self, image_name):
    method _normalized_threshold (line 54) | def _normalized_threshold(self, res, prob, threshold=0.5, verbose=False):
    method detect (line 64) | def detect(self, image_name, verbose=False):
    method localize (line 82) | def localize(self, image_name):
  function inference (line 103) | def inference(img_path):

FILE: HiFi_Net_loc.py
  function config (line 33) | def config(args):
  function restore_weight (line 55) | def restore_weight(args, FENet, SegNet, FENet_dir, SegNet_dir):
  function Inference_loc (line 68) | def Inference_loc(
  function main (line 140) | def main(args):

FILE: IMD_dataloader.py
  function train_dataset_loader_init (line 9) | def train_dataset_loader_init(args):
  function infer_dataset_loader_init (line 20) | def infer_dataset_loader_init(args, shuffle=True, bs=8):
  function eval_dataset_loader_init (line 31) | def eval_dataset_loader_init(args, val_tag, batch_size=1):

FILE: applications/deepfake_detection/sequence/models/GaussianSmoothing.py
  class GaussianSmoothing (line 11) | class GaussianSmoothing(nn.Module):
    method __init__ (line 24) | def __init__(self, channels, kernel_size, sigma, dim=2):
    method forward (line 66) | def forward(self, input):

FILE: applications/deepfake_detection/sequence/models/HiFiNet_deepfake.py
  class Flatten (line 11) | class Flatten(nn.Module):
    method __init__ (line 12) | def __init__(self):
    method forward (line 15) | def forward(self, x):
  class CatDepth (line 18) | class CatDepth(nn.Module):
    method __init__ (line 19) | def __init__(self):
    method forward (line 22) | def forward(self, x, y):
  class HiFiNet_deepfake (line 25) | class HiFiNet_deepfake(nn.Module):
    method __init__ (line 26) | def __init__(self, use_laplacian=False, drop_rate=0.5, use_magic_loss=...
    method forward (line 57) | def forward(self,x):
    method up (line 69) | def up (self,x, size):
    method up_pix (line 72) | def up_pix(self,x,r):
  function merge_concat (line 77) | def merge_concat(out1, out2):
  function merge_sum (line 80) | def merge_sum(out1, out2):

FILE: applications/deepfake_detection/sequence/models/LaPlacianMs.py
  class LaPlacianMs (line 13) | class LaPlacianMs(nn.Module):
    method __init__ (line 14) | def __init__(self,in_c,gauss_ker_size=3,scale=[2],drop_rate=0.2):
    method down (line 41) | def down(self,x,s):
    method up (line 45) | def up (self,x, size):
    method forward (line 48) | def forward(self, x):

FILE: applications/deepfake_detection/sequence/models/hrnet/seg_hrnet.py
  function srm_generation (line 24) | def srm_generation(image):
  class BayarConstraint (line 64) | class BayarConstraint(object):
    method __init__ (line 65) | def __init__(self):
    method __call__ (line 68) | def __call__(self, module):
  function conv3x3 (line 82) | def conv3x3(in_planes, out_planes, stride=1):
  class CatDepth (line 87) | class CatDepth(nn.Module):
    method __init__ (line 88) | def __init__(self):
    method forward (line 91) | def forward(self, x, y):
  function weights_init (line 94) | def weights_init(init_type='gaussian'):
  class BasicBlock (line 117) | class BasicBlock(nn.Module):
    method __init__ (line 120) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 130) | def forward(self, x):
  class Bottleneck (line 149) | class Bottleneck(nn.Module):
    method __init__ (line 152) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 167) | def forward(self, x):
  class HighResolutionModule (line 190) | class HighResolutionModule(nn.Module):
    method __init__ (line 191) | def __init__(self, num_branches, blocks, num_blocks, num_inchannels,
    method _check_branches (line 208) | def _check_branches(self, num_branches, blocks, num_blocks,
    method _make_one_branch (line 225) | def _make_one_branch(self, branch_index, block, num_blocks, num_channels,
    method _make_branches (line 249) | def _make_branches(self, num_branches, block, num_blocks, num_channels):
    method _make_fuse_layers (line 261) | def _make_fuse_layers(self):
    method get_num_inchannels (line 302) | def get_num_inchannels(self):
    method forward (line 305) | def forward(self, x):
  class HighResolutionNet (line 341) | class HighResolutionNet(nn.Module):
    method __init__ (line 343) | def __init__(self, config, **kwargs):
    method _make_head (line 421) | def _make_head(self, pre_stage_channels):
    method _make_transition_layer (line 474) | def _make_transition_layer(self, num_channels_pre_layer, num_channels_...
    method _make_layer (line 510) | def _make_layer(self, block, inplanes, planes, blocks, stride=1):
    method _make_stage (line 527) | def _make_stage(self, layer_config, num_inchannels, multi_scale_output...
    method forward (line 554) | def forward(self, x):
    method init_weights (line 609) | def init_weights(self, pretrained='',):
  function get_seg_model (line 647) | def get_seg_model(cfg, **kwargs):

FILE: applications/deepfake_detection/sequence/models/hrnet/seg_hrnet_config.py
  function get_cfg_defaults (line 53) | def get_cfg_defaults():

FILE: applications/deepfake_detection/sequence/rnn_stratified_dataloader.py
  function get_image_transformation (line 16) | def get_image_transformation(use_laplacian=False, normalize=True):
  function get_dataloader (line 34) | def get_dataloader(img_path,train_dataset_names,ctype,manipulations_dict...
  function get_img_list (line 96) | def get_img_list(img_path, datasets, ctype, split, window_size, hop, str...
  class ForensicFaceDatasetRNN (line 146) | class ForensicFaceDatasetRNN(data.Dataset):
    method __init__ (line 147) | def __init__(self, list_ids, img_path, dataset_name, ctype, manipulati...
    method __len__ (line 164) | def __len__(self):
    method get_dbfile_path (line 167) | def get_dbfile_path(self,path_pattern):
    method __getitem__ (line 177) | def __getitem__(self, index):

FILE: applications/deepfake_detection/sequence/runjobs_utils.py
  function init_logger (line 10) | def init_logger(name):
  function torch_load_model (line 20) | def torch_load_model(model, optimizer, load_model_path,strict=True):
  class DataConfig (line 33) | class DataConfig(object):
    method __init__ (line 34) | def __init__(self, model_path, model_name):
  class Saver (line 38) | class Saver(object):
    method __init__ (line 39) | def __init__(self, model, optimizer, scheduler, data_config,
    method save_model (line 51) | def save_model(self,epoch,ib,val_loss,before_train,best_only=False,for...
    method check_time (line 78) | def check_time(self):
    method days_hours_minutes (line 84) | def days_hours_minutes(self, td):

FILE: applications/deepfake_detection/sequence/torch_utils.py
  class ROC (line 18) | class ROC(object):
    method __init__ (line 19) | def __init__(self):
    method get_trunc_auc (line 32) | def get_trunc_auc(self,fpr_value):
    method get_tpr_at_fpr (line 42) | def get_tpr_at_fpr(self,fpr_value):
    method eval (line 49) | def eval(self):
    method compute_best_accuracy (line 53) | def compute_best_accuracy(self,n_samples=200):
    method compute_acc (line 68) | def compute_acc(self,list_scores,list_labels,thr):
    method get_precision (line 74) | def get_precision(self,criterion,thr):
  class Metrics (line 86) | class Metrics(object):
    method __init__ (line 87) | def __init__(self):
    method update (line 99) | def update(self,tp,loss_value,samples):
    method get_avg_loss (line 105) | def get_avg_loss(self):
  function count_matching_samples (line 110) | def count_matching_samples(preds,true_labels,criterion,use_magic_loss=Tr...
  function eval_model (line 122) | def eval_model(model,dataset_name,valid_joined_generator,criterion,
  function display_eval_tb (line 173) | def display_eval_tb(writer,metrics,tot_iter,desc='test',old_metrics=False):
  function train_logging (line 185) | def train_logging(string, writer, logger, epoch, saver, tot_iter, loss, ...
  class lrSched_monitor (line 197) | class lrSched_monitor(object):
    method __init__ (line 209) | def __init__(self, model, scheduler, data_config):
    method get_lr_mean (line 218) | def get_lr_mean(self):
    method monitor (line 227) | def monitor(self):
    method load_best_model (line 235) | def load_best_model(self):

FILE: models/GaussianSmoothing.py
  class GaussianSmoothing (line 12) | class GaussianSmoothing(nn.Module):
    method __init__ (line 25) | def __init__(self, channels, kernel_size, sigma, dim=2):
    method forward (line 65) | def forward(self, input):

FILE: models/LaPlacianMs.py
  class LaPlacianMs (line 11) | class LaPlacianMs(nn.Module):
    method __init__ (line 12) | def __init__(self,in_c,gauss_ker_size=3,scale=[2],drop_rate=0.2):
    method down (line 38) | def down(self,x,s):
    method up (line 42) | def up (self,x, size):
    method forward (line 45) | def forward(self, x):

FILE: models/NLCDetection_api.py
  function weights_init (line 12) | def weights_init(init_type='gaussian'):
  class PartialConv (line 33) | class PartialConv(nn.Module):
    method __init__ (line 34) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 47) | def forward(self, input, mask):
  class NonLocalMask (line 75) | class NonLocalMask(nn.Module):
    method __init__ (line 76) | def __init__(self, in_channels, reduce_scale):
    method forward (line 110) | def forward(self, x, img):
  class Flatten (line 151) | class Flatten(nn.Module):
    method __init__ (line 152) | def __init__(self):
    method forward (line 155) | def forward(self, x):
  class Classifer (line 158) | class Classifer(nn.Module):
    method __init__ (line 159) | def __init__(self, in_channels, output_channels):
    method forward (line 169) | def forward(self, x):
  class BranchCLS (line 175) | class BranchCLS(nn.Module):
    method __init__ (line 176) | def __init__(self, in_channels, output_channels):
    method forward (line 192) | def forward(self, x):
  class NLCDetection (line 202) | class NLCDetection(nn.Module):
    method __init__ (line 203) | def __init__(self):
    method forward (line 220) | def forward(self, feat, img):

FILE: models/NLCDetection_loc.py
  function weights_init (line 12) | def weights_init(init_type='gaussian'):
  class PartialConv (line 33) | class PartialConv(nn.Module):
    method __init__ (line 34) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 47) | def forward(self, input, mask):
  class NonLocalMask (line 75) | class NonLocalMask(nn.Module):
    method __init__ (line 76) | def __init__(self, in_channels, reduce_scale):
    method forward (line 109) | def forward(self, x, img):
  class Flatten (line 157) | class Flatten(nn.Module):
    method __init__ (line 158) | def __init__(self):
    method forward (line 161) | def forward(self, x):
  class Classifer (line 164) | class Classifer(nn.Module):
    method __init__ (line 165) | def __init__(self, in_channels, output_channels):
    method forward (line 175) | def forward(self, x):
  class BranchCLS (line 181) | class BranchCLS(nn.Module):
    method __init__ (line 182) | def __init__(self, in_channels, output_channels):
    method forward (line 198) | def forward(self, x):
  class FPN_loc (line 208) | class FPN_loc(nn.Module):
    method __init__ (line 210) | def __init__(self, args, clip_dim=64, multi_feat=None):
  class NLCDetection (line 264) | class NLCDetection(nn.Module):
    method __init__ (line 265) | def __init__(self):
    method feature_resize (line 285) | def feature_resize(self, feat):
    method forward (line 294) | def forward(self, feat, img):

FILE: models/NLCDetection_pconv.py
  function weights_init (line 12) | def weights_init(init_type='gaussian'):
  class PartialConv (line 33) | class PartialConv(nn.Module):
    method __init__ (line 34) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 47) | def forward(self, input, mask):
  class NonLocalMask (line 75) | class NonLocalMask(nn.Module):
    method __init__ (line 76) | def __init__(self, in_channels, reduce_scale):
    method forward (line 110) | def forward(self, x, img):
  class Flatten (line 151) | class Flatten(nn.Module):
    method __init__ (line 152) | def __init__(self):
    method forward (line 155) | def forward(self, x):
  class Classifer (line 158) | class Classifer(nn.Module):
    method __init__ (line 159) | def __init__(self, in_channels, output_channels):
    method forward (line 169) | def forward(self, x):
  class BranchCLS (line 175) | class BranchCLS(nn.Module):
    method __init__ (line 176) | def __init__(self, in_channels, output_channels):
    method forward (line 192) | def forward(self, x):
  class NLCDetection (line 202) | class NLCDetection(nn.Module):
    method __init__ (line 203) | def __init__(self, args):
    method forward (line 221) | def forward(self, feat, img):

FILE: models/seg_hrnet.py
  function srm_generation (line 26) | def srm_generation(image):
  class BayarConstraint (line 66) | class BayarConstraint(object):
    method __init__ (line 67) | def __init__(self):
    method __call__ (line 70) | def __call__(self, module):
  function conv3x3 (line 84) | def conv3x3(in_planes, out_planes, stride=1):
  class CatDepth (line 89) | class CatDepth(nn.Module):
    method __init__ (line 90) | def __init__(self):
    method forward (line 93) | def forward(self, x, y):
  class BasicBlock (line 98) | class BasicBlock(nn.Module):
    method __init__ (line 101) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 111) | def forward(self, x):
  class Bottleneck (line 130) | class Bottleneck(nn.Module):
    method __init__ (line 133) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 148) | def forward(self, x):
  class HighResolutionModule (line 171) | class HighResolutionModule(nn.Module):
    method __init__ (line 172) | def __init__(self, num_branches, blocks, num_blocks, num_inchannels,
    method _check_branches (line 189) | def _check_branches(self, num_branches, blocks, num_blocks,
    method _make_one_branch (line 206) | def _make_one_branch(self, branch_index, block, num_blocks, num_channels,
    method _make_branches (line 230) | def _make_branches(self, num_branches, block, num_blocks, num_channels):
    method _make_fuse_layers (line 242) | def _make_fuse_layers(self):
    method get_num_inchannels (line 283) | def get_num_inchannels(self):
    method forward (line 286) | def forward(self, x):
  class HighResolutionNet (line 322) | class HighResolutionNet(nn.Module):
    method __init__ (line 324) | def __init__(self, config, **kwargs):
    method _make_transition_layer (line 402) | def _make_transition_layer(self, num_channels_pre_layer, num_channels_...
    method _make_layer (line 438) | def _make_layer(self, block, inplanes, planes, blocks, stride=1):
    method _make_stage (line 455) | def _make_stage(self, layer_config, num_inchannels, multi_scale_output...
    method forward (line 482) | def forward(self, x):
    method init_weights (line 530) | def init_weights(self, pretrained='',):
  function get_seg_model (line 568) | def get_seg_model(cfg, **kwargs):

FILE: models/seg_hrnet_config.py
  function get_cfg_defaults (line 53) | def get_cfg_defaults():

FILE: utils/custom_loss.py
  class IsolatingLossFunction (line 14) | class IsolatingLossFunction(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, c, R, p=2, threshold_val=1.85):
    method forward (line 37) | def forward(self, model_output, label, threshold_new=None, update_flag...
    method inference (line 74) | def inference(self, model_output):
  function center_radius_init (line 87) | def center_radius_init(args, FENet, SegNet, train_data_loader, debug=Tru...
  function load_center_radius (line 138) | def load_center_radius(args, FENet, SegNet, train_data_loader, center_ra...
  function load_center_radius_api (line 152) | def load_center_radius_api(center_radius_dir='center'):

FILE: utils/load_data.py
  class BaseData (line 23) | class BaseData(data.Dataset):
    method __init__ (line 27) | def __init__(self, args):
    method __getitem__ (line 39) | def __getitem__(self, index):
    method __len__ (line 43) | def __len__(self):
    method _img_list_retrieve (line 47) | def _img_list_retrieve():
    method _resize_func (line 50) | def _resize_func(self, input_img):
    method get_image (line 57) | def get_image(self, image_name, aug_index=None):
    method rgba2rgb (line 67) | def rgba2rgb(self, rgba, background=(255, 255, 255)):
    method generate_4masks (line 83) | def generate_4masks(self, mask):
    method get_mask (line 126) | def get_mask(self, image_name, cls, aug_index=None):
    method load_mask (line 186) | def load_mask(self, mask_name, real=False, full_syn=False, gray=True, ...
    method get_cls (line 200) | def get_cls(self, image_name):
  class TrainData (line 245) | class TrainData(BaseData):
    method __init__ (line 249) | def __init__(self, args):
    method img_retrieve (line 254) | def img_retrieve(self, file_text, file_folder, real=True):
    method get_item (line 290) | def get_item(self, index):
    method _img_list_retrieve (line 305) | def _img_list_retrieve(self):
  class ValData (line 315) | class ValData(BaseData):
    method __init__ (line 319) | def __init__(self, args):
    method img_retrieve (line 324) | def img_retrieve(self, file_text, file_folder, real=True):
    method get_item (line 355) | def get_item(self, index):
    method _img_list_retrieve (line 369) | def _img_list_retrieve(self):

FILE: utils/load_edata.py
  class BaseData (line 11) | class BaseData(data.Dataset):
    method __init__ (line 15) | def __init__(self, args):
    method __getitem__ (line 26) | def __getitem__(self, index):
    method __len__ (line 30) | def __len__(self):
    method generate_mask (line 33) | def generate_mask(self, mask):
    method rgba2rgb (line 44) | def rgba2rgb(self, rgba, background=(255, 255, 255)):
    method get_image (line 59) | def get_image(self, image_name):
    method get_mask (line 71) | def get_mask(self, mask_name):
    method get_item (line 82) | def get_item(self, index):
  class ValColumbia (line 107) | class ValColumbia(BaseData):
    method __init__ (line 108) | def __init__(self, args):
    method get_item (line 118) | def get_item(self, index):
  class ValCoverage (line 134) | class ValCoverage(BaseData):
    method __init__ (line 135) | def __init__(self, args):
    method get_item (line 145) | def get_item(self, index):
  class ValCasia (line 158) | class ValCasia(BaseData):
    method __init__ (line 159) | def __init__(self, args):
    method get_item (line 187) | def get_item(self, index):
  class ValNIST16 (line 203) | class ValNIST16(BaseData):
    method __init__ (line 204) | def __init__(self, args):
    method get_item (line 215) | def get_item(self, index):
  class ValIMD2020 (line 246) | class ValIMD2020(BaseData):
    method __init__ (line 247) | def __init__(self, args):
    method get_item (line 263) | def get_item(self, index):

FILE: utils/utils.py
  function device_ids_return (line 25) | def device_ids_return(cuda_list):
  function findLastCheckpoint (line 39) | def findLastCheckpoint(save_dir):
  function get_confusion_matrix (line 54) | def get_confusion_matrix(y_true, y_pred):
  function compute_cls_acc_f1 (line 57) | def compute_cls_acc_f1(label_lst, pred_lst, iter_num, tb_writer, descr='...
  function tb_writer_display (line 66) | def tb_writer_display(writer, iter_num, lr_scheduler, epoch,
  function one_hot_label (line 84) | def one_hot_label(vector, Softmax_m=Softmax_m):
  function one_hot_label_new (line 89) | def one_hot_label_new(vector, Softmax_m=Softmax_m):
  function level_1_convert (line 100) | def level_1_convert(input_lst):
  function confusion_matrix_display (line 109) | def confusion_matrix_display(label_lst, res_lst, display_lst, display_na...
  function make_folder (line 121) | def make_folder(folder_name):
  function class_weight (line 128) | def class_weight(mask, mask_idx):
  function setup_optimizer (line 139) | def setup_optimizer(args, SegNet, FENet):
  function restore_weight_helper (line 160) | def restore_weight_helper(model, model_dir, initial_epoch):
  function restore_optimizer (line 174) | def restore_optimizer(optimizer, model_dir):
  function composite_obj (line 186) | def composite_obj(args, loss, loss_1, loss_2, loss_3, loss_4, loss_binary):
  function composite_obj_step (line 200) | def composite_obj_step(args, loss_4_sum, map_loss_sum):
  function viz_log (line 214) | def viz_log(args, mask, pred_mask, image, iter_num, step, mode='train'):
  function process_mask (line 236) | def process_mask(mask, pred_mask):
  function viz_logs_scale (line 250) | def viz_logs_scale(args, iter_num, mask_128, mask_64, mask_32, mask2, ma...
  function train_log_dump (line 264) | def train_log_dump(args, seg_correct, seg_total, map_loss_sum, mani_lss_...