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Functions1,054 in github.com/JDAI-CV/FaceX-Zoo

⨍ Functions 1,054◇ Types & classes 307

(self, input_resolution, dim, norm_layer=nn.LayerNorm)

backbone/Swin_Transformer.py:305

(self, dim, input_resolution, depth, num_heads, window_size, mlp_ratio=4., qkv_bias=True, qk_

backbone/Swin_Transformer.py:365

(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None)

backbone/Swin_Transformer.py:426

(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, depths=[2, 2, 6, 2], num_heads=[

backbone/Swin_Transformer.py:489

(self, backbone_type, backbone_conf_file)

backbone/backbone_def.py:31

(self, in_chs, se_ratio=0.25, reduced_base_chs=None, act_layer=nn.ReLU, gate_fn=hard_sigmoid,

backbone/GhostNet.py:55

(self, in_chs, out_chs, kernel_size, stride=1, act_layer=nn.ReLU)

backbone/GhostNet.py:75

(self, inp, oup, kernel_size=1, ratio=2, dw_size=3, stride=1, relu=True)

backbone/GhostNet.py:90

(self, in_chs, mid_chs, out_chs, dw_kernel_size=3, stride=1, act_layer=nn.ReLU, se_ratio=0.)

backbone/GhostNet.py:118

(self, inplace=True)

backbone/ReXNets.py:60

(self, in_channels, channels, t, stride, use_se=True, se_ratio=12, **kwargs)

backbone/ReXNets.py:103

(self, input_ch=16, final_ch=180, width_mult=1.0, depth_mult=1.0, use_se=True, se_ratio=12,

backbone/ReXNets.py:135

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

backbone/MobileFaceNets.py:18

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

backbone/MobileFaceNets.py:30

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

backbone/MobileFaceNets.py:40

(self, embedding_size, out_h, out_w)

backbone/MobileFaceNets.py:69

(self, num_layers, drop_ratio, feat_dim, out_h=7, out_w=7)

backbone/resnest/resnest.py:24

(self, in_channels, channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1), gr

backbone/resnest/splat.py:14

(self, *args, **kwargs)

backbone/resnest/resnet.py:18

Global average pooling over the input's spatial dimensions

backbone/resnest/resnet.py:22

(self, inplanes, planes, stride=1, downsample=None, radix=1, cardinality=1, bottleneck_width=

backbone/resnest/resnet.py:34

Init face model by backbone factorcy and head factory. Args: backbone_factory(object): produce a backbone according to co

training_mode/swin_training/train.py:41

(self, optimizer: torch.optim.Optimizer, t_initial: int, lr

training_mode/swin_training/lr_scheduler.py:54

Init face model by backbone factorcy and head factory. Args: backbone_factory(object): produce a backbone according to co

training_mode/distributed_training/train.py:37

Init face model by backbone factorcy and head factory. Args: backbone_factory(object): produce a backbone according to co

training_mode/siamese-triplet_training/train.py:38

(self, balance=True)

training_mode/siamese-triplet_training/pair_selector.py:32

(self, cpu=True)

training_mode/siamese-triplet_training/pair_selector.py:54

training_mode/siamese-triplet_training/pair_selector.py:83

training_mode/siamese-triplet_training/pair_selector.py:96

(self, margin, negative_selection_fn, cpu=True)

training_mode/siamese-triplet_training/pair_selector.py:141

training_mode/siamese-triplet_training/losses.py:12

(self, margin, pair_selector)

training_mode/siamese-triplet_training/losses.py:49

(self, margin, triplet_selector)

training_mode/siamese-triplet_training/losses.py:76

Init face model by backbone factorcy and head factory. Args: backbone_factory(object): produce a backbone according to co

training_mode/conventional_training/train.py:34

Init face model by backbone factorcy and head factory. Args: backbone_factory(object): produce a backbone according to co

training_mode/conventional_training/train_amp.py:35

utils/AverageMeter.py:6

(self, backbone_factory)

test_protocol/utils/model_loader.py:15

(self, test_set, data_conf_file)

test_protocol/utils/online_val.py:31

test_protocol/utils/extractor/feature_extractor.py:22

(self, feats_root)

test_protocol/utils/extractor/feature_extractor.py:78

Init PairsParser Args: pairs_file(str): the path of the pairs file that was released by official.

test_protocol/lfw/pairs_parser.py:18

(self, pairs_file, test_set)

test_protocol/lfw/pairs_parser.py:178

Init LFWEvaluator. Args: data_loader(object): a test data loader. pairs_parser_factory(object): factory to produce t

test_protocol/lfw/lfw_evaluator.py:19

Init IJBCEvaluator. Args: template_media_list(str): the path of 'ijbc_face_tid_mid.txt' template_pair_list(st

test_protocol/ijbc/ijbc_evaluator.py:18

Init CommonMegaFaceEvaluator by some initial files. Args: Please refer to the init method in parent class.

test_protocol/megaface/megaface_evaluator.py:180

Init CommonMegaFaceEvaluator by some initial files. Args: Please refer to the init method in parent class.

test_protocol/megaface/megaface_evaluator.py:251

(self, feat_dim, num_class, is_am, margin=0.35, mv_weight=1.12, scale=32)

head/MV_Softmax.py:18

(self, feat_dim, num_classes)

head/AdaCos.py:19

(self, feat_dim, num_class, scale=30.0, lamda=70.0)

head/AdaM_Softmax.py:13

(self, feat_dim, num_class, margin=0.5, scale=64)

head/ArcNegFace.py:16

(self, head_type, head_conf_file)

head/head_def.py:29

(self, feat_dim=512, num_class=86876, margin=0.5, scale=64)

head/NPCFace.py:16

(self, feat_dim, num_class, margin_arc=0.35, margin_am=0.0, scale=32)

head/ArcFace.py:15

(self, feat_dim, num_class, margin_am=0.0, scale=32, l_a=10, u_a=110, l_margin=0.45, u_margin=0.8, lamda=20)

head/MagFace.py:15

(self, feat_dim, num_class, margin=0.35, scale=32)

head/AM_Softmax.py:14

(self, feat_dim, num_class, margin=0.25, gamma=256)

head/CircleLoss.py:15

(self, feat_dim=512, queue_size=16384, scale=30.0, loss_type='softmax', margin=0.0)

head/SST_Prototype.py:16

(self, feat_dim, num_class, m = 0.5, s = 64.)

head/CurricularFace.py:19

(self, image_root, image_list_file, crop_eye=False)

data_processor/test_dataset.py:26

(self, data_root, train_file, crop_eye=False)

data_processor/train_dataset.py:51

(self, data_root, train_file, exclude_id_set)

data_processor/train_dataset.py:79

(self, dataset, transform=None, lmdb_f=None, mode=None)

addition_module/DMUE/datasets/bases.py:26

(self, probability=0.5, sl=0.02, sh=0.4, r1=0.3, mean=(0.4914, 0.4822, 0.4465))

addition_module/DMUE/datasets/preprocessing.py:17

(self, dataset, indices=None, num_samples=None)

addition_module/DMUE/datasets/sampler.py:11

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

addition_module/DMUE/models/resnet_ibn_a.py:26

(self, last_stride, block, layers)

addition_module/DMUE/models/resnet_ibn_a.py:66

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

addition_module/DMUE/models/resnet_ibn_multibranch.py:26

(self, num_branches, num_classes, last_stride, block, layers, frozen_stages=-1)

addition_module/DMUE/models/resnet_ibn_multibranch.py:66

addition_module/DMUE/models/make_target_model.py:8

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

addition_module/DMUE/models/resnet_multibranch.py:15

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

addition_module/DMUE/models/resnet_multibranch.py:47

addition_module/DMUE/models/make_model.py:55

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

addition_module/DMUE/models/resnet.py:15

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

addition_module/DMUE/models/resnet.py:47

(self, embedding_size=512, num_class=86876, s=64., m=0.5, easy_margin=True)

addition_module/DMUE/pretrain/loss_def.py:22

(self, embedding_size=512, classnum=51332)

addition_module/DMUE/pretrain/loss_def.py:65

(self, feat_dim, num_class, is_am, margin=0.35, mask=1.12, scale=32)

addition_module/DMUE/pretrain/loss_def.py:90

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

addition_module/DMUE/pretrain/backbones/resnet_ibn_a.py:37

(self, last_stride, block, layers, frozen_stages=-1,num_classes=1000)

addition_module/DMUE/pretrain/backbones/resnet_ibn_a.py:78

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

addition_module/DMUE/pretrain/backbones/resnet.py:17

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

addition_module/DMUE/pretrain/backbones/resnet.py:49

addition_module/DMUE/pretrain/utils/AverageMeter.py:3

(self, data_root, train_file, transform)

addition_module/DMUE/pretrain/utils/dataset.py:28

(self, pretrained=True)

addition_module/DMUE/preprocess/mtcnn/mtcnn.py:58

(self, pretrained=True)

addition_module/DMUE/preprocess/mtcnn/mtcnn.py:107

( self, image_size=160, margin=0, min_face_size=20, thresholds=[0.6, 0.7, 0.7], factor=0.709,

addition_module/DMUE/preprocess/mtcnn/mtcnn.py:197

(self, num_landmarks=68)

addition_module/DMUE/preprocess/face_alignmenet/dataloader.py:26

Args: landmark_dir (string): Path to the mat file with landmarks saved. img_dir (string): Directory with all the imag

addition_module/DMUE/preprocess/face_alignmenet/dataloader.py:229

(self, x_dim=64, y_dim=64, with_r=False, with_boundary=False)

addition_module/DMUE/preprocess/face_alignmenet/core/coord_conv.py:6

(self, x_dim, y_dim, with_r, with_boundary, in_channels, first_one=False, *args, **kwargs)

addition_module/DMUE/preprocess/face_alignmenet/core/coord_conv.py:78

(self, in_channels, out_channels, with_r=False, **kwargs)

addition_module/DMUE/preprocess/face_alignmenet/core/coord_conv.py:145

(self, num_landmarks=68)

addition_module/DMUE/preprocess/face_alignmenet/core/dataloader.py:25

Args: landmark_dir (string): Path to the mat file with landmarks saved. img_dir (string): Directory with all the imag

addition_module/DMUE/preprocess/face_alignmenet/core/dataloader.py:228

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

addition_module/DMUE/preprocess/face_alignmenet/core/models.py:18

(self, in_planes, out_planes)

addition_module/DMUE/preprocess/face_alignmenet/core/models.py:47

(self, num_modules, depth, num_features, first_one=False)

addition_module/DMUE/preprocess/face_alignmenet/core/models.py:93

(self, channels, reduction)

addition_module/face_lightning/KDF/backbone/ResNets.py:21

(self, in_channel, depth, stride)

addition_module/face_lightning/KDF/backbone/ResNets.py:41

(self, in_channel, depth, stride)

addition_module/face_lightning/KDF/backbone/ResNets.py:59

(self, backbone_type, backbone_conf_file)

addition_module/face_lightning/KDF/backbone/backbone_def.py:20

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