Functions — github.com/VDIGPKU/CMUA-Watermark

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Functions574 in github.com/VDIGPKU/CMUA-Watermark

⨍ Functions 574◇ Types & classes 111

Save a numpy image to the disk Parameters: image_numpy (numpy array) -- input numpy array image_path (str) -- the path o

AttentionGAN/util/util.py:49

↓ 36 callersMethodstep

(self, epoch)

AttentionGAN/AttentionGAN-v1/utils.py:115

↓ 35 callersMethodload

(self, path)

AttGAN/attgan.py:270

↓ 21 callersMethodsave

(self, path)

AttGAN/attgan.py:261

↓ 15 callersMethodcreate_labels

Generate target domain labels for debugging and testing.

stargan_solver.py:208

↓ 15 callersMethodcreate_labels

Generate target domain labels for debugging and testing.

stargan/solver.py:208

↓ 15 callersMethodlabel2onehot

Convert label indices to one-hot vectors.

stargan_solver.py:201

↓ 15 callersMethodlabel2onehot

Convert label indices to one-hot vectors.

stargan/solver.py:201

↓ 12 callersMethod__init__

(self, hyperparameters)

HiSD/core/networks.py:20

↓ 12 callersMethodrestore_model

Restore the trained generator and discriminator.

stargan_solver.py:117

↓ 12 callersMethodsave

save the current content to the HMTL file

AttentionGAN/util/html.py:68

↓ 10 callersMethoddenorm

Convert the range from [-1, 1] to [0, 1].

stargan_solver.py:182

↓ 10 callersMethoddenorm

Convert the range from [-1, 1] to [0, 1].

stargan/solver.py:182

↓ 10 callersMethodeval

(self)

AttGAN/attgan.py:257

↓ 10 callersMethodrestore_model

Restore the trained generator and discriminator.

stargan/solver.py:117

↓ 9 callersFunctioncheck_attribute_conflict

(att_batch, att_name, att_names)

AttGAN/data.py:109

↓ 9 callersMethodforward_blur

(self, x, c, blur_layer)

stargan/model.py:79

↓ 9 callersMethodscalar_summary

Add scalar summary.

stargan/logger.py:11

↓ 8 callersMethod__init__

Initialize the GANLoss class. Parameters: gan_mode (str) - - the type of GAN objective. It currently supports vanilla, lsgan, an

AttentionGAN/AttentionGAN-geo/networks.py:220

↓ 8 callersMethod__init__

Initialize the GANLoss class. Parameters: gan_mode (str) - - the type of GAN objective. It currently supports vanilla, lsgan, an

AttentionGAN/models/networks.py:220

↓ 8 callersMethodclassification_loss

Compute binary or softmax cross entropy loss.

stargan_solver.py:234

↓ 8 callersMethodclassification_loss

Compute binary or softmax cross entropy loss.

stargan/solver.py:234

↓ 8 callersMethoddecode

(self, e)

HiSD/core/networks.py:132

↓ 8 callersFunctionget_images

(filename)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/inception_score.py:57

↓ 8 callersMethodreset_grad

Reset the gradient buffers.

stargan_solver.py:177

↓ 8 callersMethodreset_grad

Reset the gradient buffers.

stargan/solver.py:177

↓ 7 callersMethodeval

Make models eval mode during test time

AttentionGAN/models/base_model.py:91

↓ 7 callersMethodtranslate

(self, e, s, i)

HiSD/core/networks.py:142

↓ 6 callersFunction_set

(att, value, att_name)

AttGAN/data.py:114

↓ 6 callersMethoddenorm

Convert the range from [-1, 1] to [0, 1].

attentiongan_solver.py:127

↓ 6 callersMethoddenorm

Convert the range from [-1, 1] to [0, 1].

AttentionGAN/AttentionGAN_v1_multi/solver.py:127

↓ 6 callersMethodforward

(self, x, s, y, i)

HiSD/core/networks.py:41

↓ 6 callersFunctionget_kid

(kcd, batch_size, images1, images2, inception_images, real_activation, fake_activation, activations)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:341

↓ 6 callersMethodperturb

Vanilla Attack.

attacks.py:50

↓ 6 callersMethodquery

Return an image from the pool. Parameters: images: the latest generated images from the generator Returns images from th

AttentionGAN/util/image_pool.py:23

↓ 6 callersMethodset_requires_grad

Set requies_grad=Fasle for all the networks to avoid unnecessary computations Parameters: nets (network list) -- a list of netwo

AttentionGAN/models/base_model.py:218

↓ 5 callersFunction_get

(att, att_name)

AttGAN/data.py:110

↓ 5 callersFunctionfind_model

(path, epoch='latest')

AttGAN/utils.py:12

↓ 5 callersMethodperturb

Vanilla Attack.

stargan/attacks.py:40

↓ 5 callersFunctionprepare

()

model_data_prepare.py:95

↓ 4 callersMethod__init__

(self, dim)

AttGAN/nn.py:58

↓ 4 callersMethodcreate_labels

Generate target domain labels for debugging and testing.

attentiongan_solver.py:153

↓ 4 callersMethodcreate_labels

Generate target domain labels for debugging and testing.

AttentionGAN/AttentionGAN_v1_multi/solver.py:153

↓ 4 callersMethodcreate_visdom_connections

If the program could not connect to Visdom server, this function will start a new server at port < self.port >

AttentionGAN/util/visualizer.py:97

↓ 4 callersFunctioncv2_to_PIL

(image)

stargan/noise.py:11

↓ 4 callersMethodforward

(self, input)

AttentionGAN/AttentionGAN-v1/models.py:49

↓ 4 callersFunctionget_config

(config)

HiSD/core/utils.py:48

↓ 4 callersFunctionget_inception_activations

(batch_size, images, inception_images, activations)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:319

↓ 4 callersMethodgradient_penalty

Compute gradient penalty: (L2_norm(dy/dx) - 1)**2.

stargan_solver.py:187

↓ 4 callersMethodgradient_penalty

Compute gradient penalty: (L2_norm(dy/dx) - 1)**2.

stargan/solver.py:187

↓ 4 callersMethodinterpolate

(a, b=None)

AttGAN/attgan.py:206

↓ 4 callersMethodpreload

(self)

HiSD/core/utils.py:129

↓ 4 callersFunctionprint_network

(net)

AttentionGAN/AttentionGAN-v1/utils.py:11

↓ 4 callersMethodprint_network

Print out the network information.

stargan_solver.py:108

↓ 4 callersMethodprint_network

Print out the network information.

stargan/solver.py:108

↓ 4 callersMethodsample

(self, x, x_trg, j, j_trg, i)

HiSD/core/trainer.py:177

↓ 4 callersMethodtest_universal_model_level

Universal Attack by Huang Hao

stargan_solver.py:1333

↓ 4 callersMethodtest_universal_model_level_attack

Universal Attack by Huang Hao

stargan_solver.py:1311

↓ 4 callersMethodupdate_lr

Decay learning rates of the generator and discriminator.

stargan_solver.py:170

↓ 4 callersMethodupdate_lr

Decay learning rates of the generator and discriminator.

stargan/solver.py:170

↓ 3 callersMethod__init__

(self, conv_dim=64, c_dim=5, repeat_num=6)

stargan/model.py:29

↓ 3 callersMethod__init__

(self, kernel)

stargan/defenses/smoothing.py:54

↓ 3 callersMethod__init__

(self, kernel)

AttGAN/defenses/smoothing.py:54

↓ 3 callersFunctionadd_activation

(layers, fn)

AttGAN/nn.py:42

↓ 3 callersMethodadd_header

Insert a header to the HTML file Parameters: text (str) -- the header text

AttentionGAN/util/html.py:39

↓ 3 callersMethodadd_images

add images to the HTML file Parameters: ims (str list) -- a list of image paths txts (str list) -- a list of image

AttentionGAN/util/html.py:48

↓ 3 callersMethodencode

(self, x)

HiSD/core/networks.py:128

↓ 3 callersFunctionevaluate_multiple_models

(args_attack, test_dataloader, attgan, attgan_args, solver, attentiongan_solver, transform, F, T, G, E, refere

evaluate.py:28

↓ 3 callersMethodextract

(self, x, i)

HiSD/core/networks.py:136

↓ 3 callersMethodget

Download a dataset. Parameters: save_path (str) -- A directory to save the data to. dataset (str) -- (opt

AttentionGAN/util/get_data.py:79

↓ 3 callersFunctionget_fid

(fcd, batch_size, images1, images2, inception_images, real_activation, fake_activation, activations)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:332

↓ 3 callersFunctioninception_activations

(images, num_splits=1)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:303

↓ 3 callersMethodlabel2onehot

Convert label indices to one-hot vectors.

attentiongan_solver.py:146

↓ 3 callersMethodlabel2onehot

Convert label indices to one-hot vectors.

AttentionGAN/AttentionGAN_v1_multi/solver.py:146

↓ 3 callersFunctionmake_dataset

(dir, max_dataset_size=float("inf"))

AttentionGAN/data/image_folder.py:23

↓ 3 callersMethodmap

(self, z, i, j)

HiSD/core/networks.py:139

↓ 3 callersMethodnext

(self)

HiSD/core/utils.py:143

↓ 3 callersMethodsave_networks

Save all the networks to the disk. Parameters: epoch (int) -- current epoch; used in the file name '%s_net_%s.pth' % (epoch, name

AttentionGAN/models/base_model.py:143

↓ 3 callersMethodtrain

(self)

AttGAN/attgan.py:253

↓ 3 callersMethodupdate

(self, x, y, i, j, j_trg)

HiSD/core/trainer.py:133

↓ 2 callersMethod__init__

(self, args)

AttGAN/attgan.py:129

↓ 2 callersMethod__init__

(self, data_path, attr_path, image_size, selected_attrs)

AttGAN/data.py:17

↓ 2 callersMethod__init__

(self, num_features, eps=1e-5, momentum=0.997, using_moving_average=True)

AttGAN/switchable_norm.py:10

↓ 2 callersMethod__init__

(self, input_nc=3, output_nc=4, ngf=64, norm_layer=nn.BatchNorm2d, use_dropout=False, n_blocks=6)

AttentionGAN/AttentionGAN-v1/models.py:7

↓ 2 callersMethod__init__

(self, conv_dim=64, c_dim=5, repeat_num=6)

AttentionGAN/AttentionGAN_v1_multi/model.py:24

↓ 2 callersFunction_is_even

(x)

stargan/defenses/smoothing.py:141

↓ 2 callersFunction_is_even

(x)

AttGAN/defenses/smoothing.py:141

↓ 2 callersMethod_print

(self, text)

AttentionGAN/util/get_data.py:35

↓ 2 callersFunction_symmetric_matrix_square_root

Compute square root of a symmetric matrix. Note that this is different from an elementwise square root. We want to compute M' where M' = sqrt(

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:17

↓ 2 callersFunctionactivations2distance

(fcd, real_activation, fake_activation, act1, act2)

AttentionGAN/scripts/GAN_Metrics-Tensorflow/frechet_kernel_Inception_distance.py:328

↓ 2 callersFunctionadd_normalization_2d

(layers, fn, n_out)

AttGAN/nn.py:29

↓ 2 callersFunctionadd_scalar_dict

(writer, scalar_dict, iteration, directory=None)

AttGAN/helpers.py:37

↓ 2 callersMethodbackward_D_basic

Calculate GAN loss for the discriminator Parameters: netD (network) -- the discriminator D real (tensor array) --

AttentionGAN/AttentionGAN-geo/attention_gan_model.py:105

↓ 2 callersMethodbackward_D_basic

Calculate GAN loss for the discriminator Parameters: netD (network) -- the discriminator D real (tensor array) --

AttentionGAN/models/attention_gan_model.py:99

↓ 2 callersMethodbackward_D_basic

Calculate GAN loss for the discriminator Parameters: netD (network) -- the discriminator D real (tensor array) --

AttentionGAN/models/attention_gan1_model.py:127

↓ 2 callersMethodclassification_loss

Compute binary or softmax cross entropy loss.

attentiongan_solver.py:179

↓ 2 callersMethodclassification_loss

Compute binary or softmax cross entropy loss.

AttentionGAN/AttentionGAN_v1_multi/solver.py:179

↓ 2 callersMethodcompute_grad2

(self, d_out, x_in)

HiSD/core/networks.py:83

↓ 2 callersMethodcompute_visuals

Calculate additional output images for visdom and HTML visualization

AttentionGAN/models/base_model.py:108

↓ 2 callersFunctioncreate_dataset

Create a dataset given the option. This function wraps the class CustomDatasetDataLoader. This is the main interface between this package

AttentionGAN/data/__init__.py:47

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