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github.com/TARTRL/Deepfake_Detection
/ functions
Functions
965 in github.com/TARTRL/Deepfake_Detection
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Functions
965
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Types & classes
181
Method
forward
(self, x, target)
dfd/timm/loss/cross_entropy.py:20
Method
forward
(self, x, target)
dfd/timm/loss/cross_entropy.py:34
Function
get_all_files
(input_dir, suffix=None)
dfd/utils.py:48
Function
get_all_images
(datadirs)
dfd/timm/data/dataset.py:203
Method
get_classifier
(self)
dfd/timm/models/xception.py:177
Method
get_classifier
(self)
dfd/timm/models/pnasnet.py:346
Method
get_classifier
(self)
dfd/timm/models/gluon_xception.py:254
Method
get_classifier
(self)
dfd/timm/models/gluon_xception.py:391
Method
get_classifier
(self)
dfd/timm/models/senet.py:366
Method
get_classifier
(self)
dfd/timm/models/hrnet.py:683
Method
get_classifier
(self)
dfd/timm/models/dpn.py:224
Method
get_classifier
(self)
dfd/timm/models/densenet.py:124
Method
get_classifier
(self)
dfd/timm/models/mobilenetv3.py:117
Method
get_classifier
(self)
dfd/timm/models/inception_v4.py:277
Method
get_classifier
(self)
dfd/timm/models/selecsls.py:131
Method
get_classifier
(self)
dfd/timm/models/nasnet.py:559
Method
get_classifier
(self)
dfd/timm/models/inception_resnet_v2.py:293
Method
get_classifier
(self)
dfd/timm/models/efficientnet.py:311
Method
get_classifier
(self)
dfd/timm/models/efficientnet.py:422
Method
get_classifier
(self)
dfd/timm/models/resnet.py:441
Method
get_classifier_params
(self)
dfd/timm/models/efficientnet.py:350
Method
get_classifier_params
(self)
dfd/timm/models/efficientnet.py:454
Method
get_cycle_length
(self, cycles=0)
dfd/timm/scheduler/cosine_lr.py:103
Method
get_epoch_values
(self, epoch: int)
dfd/timm/scheduler/tanh_lr.py:95
Method
get_epoch_values
(self, epoch: int)
dfd/timm/scheduler/cosine_lr.py:91
Method
get_epoch_values
(self, epoch: int)
dfd/timm/scheduler/step_lr.py:47
Function
get_filename
(filepath)
dfd/utils.py:83
Function
get_outdir
(path, *paths, inc=False)
dfd/timm/utils.py:189
Function
get_proper_gpu
(gpu_number, minimum_memory_per_gpu)
dfd/utils.py:14
Method
get_update_values
(self, num_updates: int)
dfd/timm/scheduler/tanh_lr.py:101
Method
get_update_values
(self, num_updates: int)
dfd/timm/scheduler/cosine_lr.py:97
Method
get_update_values
(self, num_updates: int)
dfd/timm/scheduler/step_lr.py:53
Function
gluon_inception_v3
(pretrained=False, num_classes=1000, in_chans=3, **kwargs)
dfd/timm/models/inception_v3.py:110
Function
gluon_resnet101_v1b
Constructs a ResNet-101 model.
dfd/timm/models/gluon_resnet.py:96
Function
gluon_resnet101_v1c
Constructs a ResNet-101 model.
dfd/timm/models/gluon_resnet.py:133
Function
gluon_resnet101_v1d
Constructs a ResNet-101 model.
dfd/timm/models/gluon_resnet.py:172
Function
gluon_resnet101_v1e
Constructs a ResNet-101 model.
dfd/timm/models/gluon_resnet.py:211
Function
gluon_resnet101_v1s
Constructs a ResNet-101 model.
dfd/timm/models/gluon_resnet.py:250
Function
gluon_resnet152_v1b
Constructs a ResNet-152 model.
dfd/timm/models/gluon_resnet.py:108
Function
gluon_resnet152_v1c
Constructs a ResNet-152 model.
dfd/timm/models/gluon_resnet.py:146
Function
gluon_resnet152_v1d
Constructs a ResNet-152 model.
dfd/timm/models/gluon_resnet.py:185
Function
gluon_resnet152_v1e
Constructs a ResNet-152 model.
dfd/timm/models/gluon_resnet.py:224
Function
gluon_resnet152_v1s
Constructs a ResNet-152 model.
dfd/timm/models/gluon_resnet.py:263
Function
gluon_resnet18_v1b
Constructs a ResNet-18 model.
dfd/timm/models/gluon_resnet.py:60
Function
gluon_resnet34_v1b
Constructs a ResNet-34 model.
dfd/timm/models/gluon_resnet.py:72
Function
gluon_resnet50_v1b
Constructs a ResNet-50 model.
dfd/timm/models/gluon_resnet.py:84
Function
gluon_resnet50_v1c
Constructs a ResNet-50 model.
dfd/timm/models/gluon_resnet.py:120
Function
gluon_resnet50_v1d
Constructs a ResNet-50 model.
dfd/timm/models/gluon_resnet.py:159
Function
gluon_resnet50_v1e
Constructs a ResNet-50-V1e model. No pretrained weights for any 'e' variants
dfd/timm/models/gluon_resnet.py:198
Function
gluon_resnet50_v1s
Constructs a ResNet-50 model.
dfd/timm/models/gluon_resnet.py:237
Function
gluon_resnext101_32x4d
Constructs a ResNeXt-101 model.
dfd/timm/models/gluon_resnet.py:290
Function
gluon_resnext101_64x4d
Constructs a ResNeXt-101 model.
dfd/timm/models/gluon_resnet.py:304
Function
gluon_resnext50_32x4d
Constructs a ResNeXt50-32x4d model.
dfd/timm/models/gluon_resnet.py:276
Function
gluon_senet154
Constructs an SENet-154 model.
dfd/timm/models/gluon_resnet.py:361
Function
gluon_seresnext101_32x4d
Constructs a SEResNeXt-101-32x4d model.
dfd/timm/models/gluon_resnet.py:332
Function
gluon_seresnext101_64x4d
Constructs a SEResNeXt-101-64x4d model.
dfd/timm/models/gluon_resnet.py:346
Function
gluon_seresnext50_32x4d
Constructs a SEResNeXt50-32x4d model.
dfd/timm/models/gluon_resnet.py:318
Function
gluon_xception65
Modified Aligned Xception-65
dfd/timm/models/gluon_xception.py:447
Function
gluon_xception71
Modified Aligned Xception-71
dfd/timm/models/gluon_xception.py:459
Function
hrnet_w18
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:773
Function
hrnet_w18_small
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:763
Function
hrnet_w18_small_v2
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:768
Function
hrnet_w30
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:778
Function
hrnet_w32
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:783
Function
hrnet_w40
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:788
Function
hrnet_w44
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:793
Function
hrnet_w48
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:798
Function
hrnet_w64
(pretrained=True, **kwargs)
dfd/timm/models/hrnet.py:803
Function
ig_resnext101_32x16d
Constructs a ResNeXt-101 32x16 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits o
dfd/timm/models/resnet.py:727
Function
ig_resnext101_32x32d
Constructs a ResNeXt-101 32x32 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits o
dfd/timm/models/resnet.py:741
Function
ig_resnext101_32x48d
Constructs a ResNeXt-101 32x48 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits o
dfd/timm/models/resnet.py:755
Function
ig_resnext101_32x8d
Constructs a ResNeXt-101 32x8 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits of
dfd/timm/models/resnet.py:713
Function
inception_resnet_v2
r"""InceptionResnetV2 model architecture from the `"InceptionV4, Inception-ResNet..." <https://arxiv.org/abs/1602.07261>` paper.
dfd/timm/models/inception_resnet_v2.py:330
Function
inception_v3
(pretrained=False, num_classes=1000, in_chans=3, **kwargs)
dfd/timm/models/inception_v3.py:70
Function
inception_v4
(pretrained=False, num_classes=1000, in_chans=3, **kwargs)
dfd/timm/models/inception_v4.py:299
Function
invert
(img, **__)
dfd/timm/data/auto_augment.py:126
Method
iter_bak
(self)
dfd/timm/data/loader.py:158
Function
list_models
Return list of available model names, sorted alphabetically Args: filter (str) - Wildcard filter string that works with fnmatch
dfd/timm/models/registry.py:45
Function
list_modules
Return list of module names that contain models / model entrypoints
dfd/timm/models/registry.py:79
Method
load_state_dict
(self, state_dict)
dfd/timm/scheduler/plateau_lr.py:49
Method
load_state_dict
(self, state_dict: Dict[str, Any])
dfd/timm/scheduler/scheduler.py:58
Function
main
(rank, args, args_text)
dfd/runners/train.py:256
Function
mixnet_l
Creates a MixNet Large model.
dfd/timm/models/efficientnet.py:1637
Function
mixnet_m
Creates a MixNet Medium model.
dfd/timm/models/efficientnet.py:1628
Function
mixnet_s
Creates a MixNet Small model.
dfd/timm/models/efficientnet.py:1619
Function
mixnet_xl
Creates a MixNet Extra-Large model. Not a paper spec, experimental def by RW w/ depth scaling.
dfd/timm/models/efficientnet.py:1646
Function
mixnet_xxl
Creates a MixNet Double Extra Large model. Not a paper spec, experimental def by RW w/ depth scaling.
dfd/timm/models/efficientnet.py:1656
Method
mixup_enabled
(self)
dfd/timm/data/loader.py:201
Method
mixup_enabled
(self)
dfd/timm/data/loader.py:280
Method
mixup_enabled
(self)
dfd/timm/data/loader.py:360
Function
mnasnet_050
MNASNet B1, depth multiplier of 0.5.
dfd/timm/models/efficientnet.py:980
Function
mnasnet_075
MNASNet B1, depth multiplier of 0.75.
dfd/timm/models/efficientnet.py:987
Function
mnasnet_140
MNASNet B1, depth multiplier of 1.4
dfd/timm/models/efficientnet.py:1007
Function
mnasnet_a1
MNASNet A1 (w/ SE), depth multiplier of 1.0.
dfd/timm/models/efficientnet.py:1035
Function
mnasnet_b1
MNASNet B1, depth multiplier of 1.0.
dfd/timm/models/efficientnet.py:1001
Function
mnasnet_small
MNASNet Small, depth multiplier of 1.0.
dfd/timm/models/efficientnet.py:1048
Function
mobilenetv2_100
MobileNet V2
dfd/timm/models/efficientnet.py:1055
Function
mobilenetv3_large_075
MobileNet V3
dfd/timm/models/mobilenetv3.py:365
Function
mobilenetv3_large_100
MobileNet V3
dfd/timm/models/mobilenetv3.py:372
Function
mobilenetv3_rw
MobileNet V3
dfd/timm/models/mobilenetv3.py:394
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