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Types & classes48 in github.com/Ha0Tang/AttentionGAN

↓ 6 callersClassImagePool
This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of
util/image_pool.py:5
↓ 6 callersClassUnetSkipConnectionBlock
Defines the Unet submodule with skip connection. X -------------------identity---------------------- |-- downsampling -- |submodule| -
AttentionGAN-geo/networks.py:642
↓ 6 callersClassUnetSkipConnectionBlock
Defines the Unet submodule with skip connection. X -------------------identity---------------------- |-- downsampling -- |submodule| -
models/networks.py:642
↓ 4 callersClassGenerator
AttentionGAN-v1/models.py:6
↓ 2 callersClassDiscriminator
AttentionGAN-v1/models.py:82
↓ 2 callersClassDiscriminator
Discriminator network with PatchGAN.
AttentionGAN-v1-multi/model.py:74
↓ 2 callersClassGenerator
Generator network.
AttentionGAN-v1-multi/model.py:22
↓ 2 callersClassImageDataset
AttentionGAN-v1/datasets.py:9
↓ 2 callersClassLambdaLR
AttentionGAN-v1/utils.py:108
↓ 2 callersClassNLayerDiscriminator
Defines a PatchGAN discriminator
AttentionGAN-geo/networks.py:712
↓ 2 callersClassNLayerDiscriminator
Defines a PatchGAN discriminator
models/networks.py:712
↓ 2 callersClassReplayBuffer
AttentionGAN-v1/utils.py:86
↓ 2 callersClassResnetGenerator
Resnet-based generator that consists of Resnet blocks between a few downsampling/upsampling operations. We adapt Torch code and idea from Justin
AttentionGAN-geo/networks.py:319
↓ 2 callersClassResnetGenerator
Resnet-based generator that consists of Resnet blocks between a few downsampling/upsampling operations. We adapt Torch code and idea from Justin
models/networks.py:319
↓ 2 callersClassUnetGenerator
Create a Unet-based generator
AttentionGAN-geo/networks.py:610
↓ 2 callersClassUnetGenerator
Create a Unet-based generator
models/networks.py:610
↓ 1 callersClassCelebA
Dataset class for the CelebA dataset.
AttentionGAN-v1-multi/data_loader.py:10
↓ 1 callersClassCustomDatasetDataLoader
Wrapper class of Dataset class that performs multi-threaded data loading
data/__init__.py:62
↓ 1 callersClassHTML
This HTML class allows us to save images and write texts into a single HTML file. It consists of functions such as <add_header> (add a text head
util/html.py:6
↓ 1 callersClassIdentity
AttentionGAN-geo/networks.py:14
↓ 1 callersClassIdentity
models/networks.py:14
↓ 1 callersClassImageFolder
data/image_folder.py:39
↓ 1 callersClassLogger
AttentionGAN-v1/utils.py:24
↓ 1 callersClassLogger
Tensorboard logger.
AttentionGAN-v1-multi/logger.py:4
↓ 1 callersClassPixelDiscriminator
Defines a 1x1 PatchGAN discriminator (pixelGAN)
AttentionGAN-geo/networks.py:760
↓ 1 callersClassPixelDiscriminator
Defines a 1x1 PatchGAN discriminator (pixelGAN)
models/networks.py:760
↓ 1 callersClassResidualBlock
Residual Block with instance normalization.
AttentionGAN-v1-multi/model.py:7
↓ 1 callersClassResnetBlock
AttentionGAN-v1/models.py:58
↓ 1 callersClassResnetBlock
Define a Resnet block
AttentionGAN-geo/networks.py:550
↓ 1 callersClassResnetBlock
Define a Resnet block
models/networks.py:550
↓ 1 callersClassResnetGenerator_our
AttentionGAN-geo/networks.py:379
↓ 1 callersClassResnetGenerator_our
models/networks.py:379
↓ 1 callersClassSolver
Solver for training and testing StarGAN.
AttentionGAN-v1-multi/solver.py:13
↓ 1 callersClassTestOptions
This class includes test options. It also includes shared options defined in BaseOptions.
options/test_options.py:4
↓ 1 callersClassTrainOptions
This class includes training options. It also includes shared options defined in BaseOptions.
options/train_options.py:4
↓ 1 callersClassVisualizer
This class includes several functions that can display/save images and print/save logging information. It uses a Python library 'visdom' for disp
util/visualizer.py:52
↓ 1 callersClassresnet_block
AttentionGAN-geo/networks.py:520
↓ 1 callersClassresnet_block
models/networks.py:520
ClassAttentionGANModel
AttentionGAN-geo/attention_gan_model.py:8
ClassAttentionGANModel
models/attention_gan_model.py:8
ClassBaseDataset
This class is an abstract base class (ABC) for datasets. To create a subclass, you need to implement the following four functions: -- <__init
data/base_dataset.py:13
ClassBaseModel
This class is an abstract base class (ABC) for models. To create a subclass, you need to implement the following five functions: -- <__ini
models/base_model.py:8
ClassBaseOptions
This class defines options used during both training and test time. It also implements several helper functions such as parsing, printing, and sa
options/base_options.py:9
ClassCycleGAN1Model
This class implements the CycleGAN model, for learning image-to-image translation without paired data. The model training requires '--dataset
models/attention_gan1_model.py:8
ClassGANLoss
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the in
AttentionGAN-geo/networks.py:213
ClassGANLoss
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the in
models/networks.py:213
ClassGetData
A Python script for downloading CycleGAN or pix2pix datasets. Parameters: technique (str) -- One of: 'cyclegan' or 'pix2pix'. ver
util/get_data.py:11
ClassUnalignedDataset
This dataset class can load unaligned/unpaired datasets. It requires two directories to host training images from domain A '/path/to/data/tr
data/unaligned_dataset.py:8