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Functions375 in github.com/10Ring/LAA-Net

⨍ Functions 375◇ Types & classes 71

↓ 1 callersMethodwait_n_get

package_utils/bi_online_generation.py:195

datasets/pipelines/color_transform.py:153

(self, x, mask=None, image_f=None, mask_f=None)

datasets/pipelines/geo_transform.py:90

(self, pred, y)

losses/losses.py:185

Method__contains__

register/register.py:131

Method__getitem__

datasets/face_forensic_binary.py:61

Method__getitem__

datasets/face_forensic_sbi.py:93

Method__getitem__

datasets/common.py:323

Method__getitem__

datasets/face_forensic_hm.py:161

(self, task='training')

logs/logger.py:17

(self, name, build_func=None, parent=None, scope=None)

register/register.py:104

lib/core_function.py:16

(self, optimizer, n_epoch, start_decay, last_epoch=-1, booster=2)

lib/scheduler/linear_decay.py:8

(self, params, base_optimizer, rho=0.05, **kwargs)

lib/optimizers/sam.py:23

(self, cfg, load_imgs=False, **kwargs)

package_utils/geo_landmarks_extraction.py:25

(self, landmarks, face, channels=4)

package_utils/deepfake_mask.py:40

(self, data_record, queue_size=1024, mlprocess=False, number=1, fake_type=None)

package_utils/bi_online_generation.py:145

(self, cfg, **kwargs)

datasets/master.py:14

@params: config: Dataset config split: train/val/test which directs to the split folders

datasets/face_forensic_binary.py:17

(self, cfg, **kwargs)

datasets/celebDF_v2.py:13

(self, cfg, **kwargs)

datasets/dfdc.py:12

@params: config: Dataset config split: train/val/test which directs to the split folders

datasets/face_forensic_sbi.py:22

(self, cfg, **kwargs)

datasets/common.py:25

(self, cfg, **kwargs)

datasets/dfw.py:12

(self, cfg, **kwargs)

datasets/dfdcp.py:12

(self, cfg, **kwargs)

datasets/dfd.py:12

(self, cfg, **kwargs)

datasets/ff.py:13

(self, cfg, **kwargs)

datasets/celebDF_v1.py:13

@params: config: Dataset config split: train/val/test which directs to the split folders

datasets/face_forensic_hm.py:23

(self, clahe: float, colorjitter: float, gaussianblur: floa

datasets/pipelines/color_transform.py:12

(self, resize: list, normalize: float, horizontal_flip: flo

datasets/pipelines/geo_transform.py:20

(self, in_channels, out_channels, kernel_size, stride=1, dilation=1, groups=1, bias=True)

models/networks/efficientNet.py:140

(self, inplanes, planes, stride=1, downsample=None)

models/networks/mrsa_resnet.py:79

(self, block, layers, heads, head_conv

models/networks/mrsa_resnet.py:123

(self,in_channels,out_channels,kernel_size=1,stride=1,padding=0,dilation=1,bias=False)

models/networks/xception.py:37

Constructor Args: num_classes: number of classes

models/networks/xception.py:107

(self, inplanes, planes, stride=1, downsample=None)

models/networks/pose_hrnet.py:52

(self, num_branches, blocks, num_blocks, num_inchannels, num_channels, fuse_method, multi_sca

models/networks/pose_hrnet.py:91

(self, cfg, **kwargs)

models/networks/pose_hrnet.py:265

(self, inplanes, outplanes, stride=1, pool_size=3)

models/networks/common.py:32

(self, channels, reduction)

models/networks/arcface.py:34

(self, in_channel, depth, stride)

models/networks/arcface.py:55

(self, in_channel, depth, stride)

models/networks/arcface.py:74

(self, drop_ratio=0.6, in_planes=512, **kwargs)

models/networks/arcface.py:171

(self, cfg: dict, **kwargs)

models/networks/arcface.py:196

(self, in_c, out_c, kernel=(1, 1), stride=(1, 1), padding=(0, 0), groups=1)

models/networks/arcface.py:215

(self, in_c, out_c, kernel=(1, 1), stride=(1, 1), padding=(0, 0), groups=1)

models/networks/arcface.py:229

(self, in_c, out_c, residual = False, kernel=(3, 3), stride=(2, 2), padding=(1, 1), groups=1)

models/networks/arcface.py:241

(self, c, num_block, groups, kernel=(3, 3), stride=(1, 1), padding=(1, 1))

models/networks/arcface.py:262

(self, embedding_size)

models/networks/arcface.py:274

(self, embedding_size=512, classnum=51332, s=64., m=0.5)

models/networks/arcface.py:313

(self,embedding_size=512,classnum=51332)

models/networks/arcface.py:357

(self, blocks_args=None, global_params=None)

models/networks/pose_efficientNet.py:166

(self, model_name, in_channels=3, **override_params)

models/networks/pose_efficientNet.py:701

(self, reduction='mean')

losses/losses.py:180

(self, cfg, use_target_weight, **kwargs)

losses/losses.py:192

(self, use_target_weight, reduction='mean')

losses/losses.py:240

(self, use_target_weight, cls_lmda=0.2, dst_lmda=0.2, reduction='mean', dist_cal=True, cls_cal=True, **kwargs)

losses/losses.py:268

(self, use_target_weight, cls_lmda=0.2, reduction='mean', cls_cal=True, **kwargs)

losses/losses.py:298

(self, use_target_weight, epsilon=2.0, cls_lmda=0.05, reduction='mean', cls_cal=True, **kwargs)

losses/losses.py:335

register/register.py:128

datasets/face_forensic_binary.py:58

datasets/common.py:319

register/register.py:134

datasets/common.py:327

models/networks/mrsa_resnet.py:117

Function_check_executable

register/misc.py:235

Function_check_py_package

register/misc.py:226

Method_conv_block

(self, inplanes, outplanes, kernel_size, stride=1)

models/networks/mrsa_resnet.py:248

Function_disable

lib/optimizers/sam.py:7

Function_enable

lib/optimizers/sam.py:15

Method_encode_target

(self, target_mask, normalize_max=True)

datasets/common.py:116

Method_encode_target_v2

(self, target_mask, normalize_max=True)

datasets/common.py:228

Method_load_from_path

datasets/master.py:17

Method_load_from_path

datasets/celebDF_v2.py:16

Method_load_from_path

datasets/dfdc.py:15

Method_load_from_path

datasets/common.py:47

Method_load_from_path

datasets/dfw.py:15

Method_load_from_path

datasets/dfdcp.py:15

Method_load_from_path

datasets/dfd.py:15

Method_load_from_path

datasets/celebDF_v1.py:16

Function_neg_loss

Modified focal loss. Exactly the same as CornerNet. Runs faster and costs a little bit more memory Arguments: pred (batch x c x h x w)

losses/losses.py:70

Function_neg_pos_loss

(hm_pred, hm_gt)

losses/losses.py:55

Method_new_encode_target

(self, target_mask, normalize_max=True)

datasets/common.py:170

Method_register

register/register.py:314

Method_reload_data

datasets/face_forensic_hm.py:86

Functionapi_warning_wrapper

register/misc.py:279

(self, img: np.array, **params)

datasets/pipelines/geo_transform.py:155

Methodbuild_mask

package_utils/deepfake_mask.py:74

Methodbuild_mask

package_utils/deepfake_mask.py:98

Methodbuild_mask

package_utils/deepfake_mask.py:127

Methodbuild_mask

package_utils/deepfake_mask.py:169

Functionbuild_model_from_cfg

Build a PyTorch model from config dict(s). Different from ``build_from_cfg``, if cfg is a list, a ``nn.Sequential`` will be built. Args:

models/builder.py:14

register/register.py:195

Functionconcat_list

Concatenate a list of list into a single list. Args: in_list (list): The list of list to be merged. Returns: list: The concate

register/misc.py:180

Functiondebug_writing

(writer, outputs, labels, inputs, iterations)

logs/logger.py:70

Functiondeprecated_api_warning

A decorator to check if some arguments are deprecate and try to replace deprecate src_arg_name to dst_arg_name. Args: name_dict(dict):

register/misc.py:268

Functiondisable_running_stats

lib/optimizers/sam.py:6

Functionenable_running_stats

lib/optimizers/sam.py:14

Encode a list of BlockArgs to a list of strings. Args: blocks_args (list[namedtuples]): A list of BlockArgs namedtuples of block a

models/networks/efficientNet.py:367

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