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github.com/10Ring/LAA-Net
/ types & classes
Types & classes
71 in github.com/10Ring/LAA-Net
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Functions
375
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Types & classes
71
↓ 12 callers
Class
AverageMeter
Computes and stores the average and current value
lib/core_function.py:14
↓ 12 callers
Class
Block
models/networks/xception.py:49
↓ 5 callers
Class
Conv_block
models/networks/arcface.py:214
↓ 5 callers
Class
SeparableConv2d
models/networks/xception.py:36
↓ 4 callers
Class
BinaryCrossEntropy
losses/losses.py:179
↓ 4 callers
Class
Depth_Wise
models/networks/arcface.py:240
↓ 4 callers
Class
MemoryEfficientSwish
models/networks/efficientNet.py:427
↓ 4 callers
Class
Registry
A registry to map strings to classes or functions. Registered object could be built from registry. Meanwhile, registered functions could be ca
register/register.py:72
↓ 3 callers
Class
InceptionBlock
models/networks/common.py:31
↓ 3 callers
Class
Logger
logs/logger.py:16
↓ 3 callers
Class
Residual
models/networks/arcface.py:261
↓ 2 callers
Class
Bottleneck
A named tuple describing a ResNet block.
models/networks/arcface.py:97
↓ 2 callers
Class
Flatten
models/networks/arcface.py:22
↓ 2 callers
Class
LandmarkUtility
package_utils/geo_landmarks_extraction.py:24
↓ 2 callers
Class
Linear_block
models/networks/arcface.py:228
↓ 2 callers
Class
MBConvBlock
Mobile Inverted Residual Bottleneck Block. Args: block_args (namedtuple): BlockArgs, defined in utils.py. global_params (namedtupl
models/networks/pose_efficientNet.py:46
↓ 2 callers
Class
Swish
models/networks/efficientNet.py:36
↓ 1 callers
Class
BIOnlineGeneration
package_utils/bi_online_generation.py:144
↓ 1 callers
Class
HighResolutionModule
models/networks/pose_hrnet.py:90
↓ 1 callers
Class
JointsMSELoss
losses/losses.py:239
↓ 1 callers
Class
LinearDecayLR
lib/scheduler/linear_decay.py:7
↓ 1 callers
Class
PoseHighResolutionNet
models/networks/pose_hrnet.py:264
↓ 1 callers
Class
RandomDownScale
datasets/sbi/utils.py:23
↓ 1 callers
Class
RandomErasing
datasets/pipelines/geo_transform.py:128
↓ 1 callers
Class
SAM
lib/optimizers/sam.py:22
↓ 1 callers
Class
SELayer
models/networks/common.py:60
↓ 1 callers
Class
SEModule
models/networks/arcface.py:33
↓ 1 callers
Class
components
Component model mask
package_utils/deepfake_mask.py:96
↓ 1 callers
Class
dfl_full
DFL facial mask
package_utils/deepfake_mask.py:72
↓ 1 callers
Class
extended
Extended mask Based on components mask. Attempts to extend the eyebrow points up the forehead
package_utils/deepfake_mask.py:123
↓ 1 callers
Class
facehull
Basic face hull mask
package_utils/deepfake_mask.py:167
Class
Am_softmax
models/networks/arcface.py:355
Class
Arcface
models/networks/arcface.py:311
Class
BaseLoss
losses/losses.py:130
Class
BasicBlock
models/networks/mrsa_resnet.py:40
Class
BasicBlock
models/networks/pose_hrnet.py:17
Class
BinaryFaceForensic
datasets/face_forensic_binary.py:16
Class
BlockDecoder
Block Decoder for readability, straight from the official TensorFlow repository.
models/networks/efficientNet.py:292
Class
Bottleneck
models/networks/mrsa_resnet.py:76
Class
Bottleneck
models/networks/pose_hrnet.py:49
Class
CDFV1
datasets/celebDF_v1.py:12
Class
CDFV2
datasets/celebDF_v2.py:12
Class
ColorJitterTransform
datasets/pipelines/color_transform.py:11
Class
CombinedFocalLoss
nn.Module warpper for focal loss
losses/losses.py:190
Class
CombinedHeatmapBinaryLoss
losses/losses.py:297
Class
CombinedLoss
losses/losses.py:267
Class
CombinedPolyLoss
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
losses/losses.py:331
Class
CommonDataset
datasets/common.py:24
Class
Conv2dDynamicSamePadding
2D Convolutions like TensorFlow, for a dynamic image size. The padding is operated in forward function by calculating dynamically.
models/networks/efficientNet.py:123
Class
Conv2dStaticSamePadding
2D Convolutions like TensorFlow's 'SAME' mode, with the given input image size. The padding mudule is calculated in construction function, then
models/networks/efficientNet.py:156
Class
DFD
datasets/dfd.py:11
Class
DFDC
datasets/dfdc.py:11
Class
DFDCP
datasets/dfdcp.py:11
Class
DFW
datasets/dfw.py:11
Class
EfficientNet
EfficientNet model. Most easily loaded with the .from_name or .from_pretrained methods. Args: blocks_args (list[namedtuple]): A lis
models/networks/pose_efficientNet.py:149
Class
FF
datasets/ff.py:12
Class
GeometryTransform
datasets/pipelines/geo_transform.py:19
Class
HeatmapFaceForensic
datasets/face_forensic_hm.py:22
Class
Mask
Parent class for masks the output mask will be <mask_type>.mask channels: 1, 3 or 4: 1 - Returns a single channel
package_utils/deepfake_mask.py:32
Class
MasterDataset
datasets/master.py:13
Class
MobileFaceNet
models/networks/arcface.py:273
Class
PoseEfficientNet
models/networks/pose_efficientNet.py:700
Class
PoseResNet
models/networks/mrsa_resnet.py:122
Class
ResNet
models/networks/arcface.py:131
Class
SBIFaceForensic
datasets/face_forensic_sbi.py:21
Class
SimpleClassificationDF
models/networks/arcface.py:195
Class
SimpleClassificationHead
models/networks/arcface.py:170
Class
SwishImplementation
models/networks/efficientNet.py:380
Class
Xception
Xception optimized for the ImageNet dataset, as specified in https://arxiv.org/pdf/1610.02357.pdf
models/networks/xception.py:102
Class
bottleneck_IR
models/networks/arcface.py:54
Class
bottleneck_IR_SE
models/networks/arcface.py:73