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github.com/Ha0Tang/AttentionGAN
/ types & classes
Types & classes
48 in github.com/Ha0Tang/AttentionGAN
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Functions
242
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Types & classes
48
↓ 6 callers
Class
ImagePool
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 callers
Class
UnetSkipConnectionBlock
Defines the Unet submodule with skip connection. X -------------------identity---------------------- |-- downsampling -- |submodule| -
AttentionGAN-geo/networks.py:642
↓ 6 callers
Class
UnetSkipConnectionBlock
Defines the Unet submodule with skip connection. X -------------------identity---------------------- |-- downsampling -- |submodule| -
models/networks.py:642
↓ 4 callers
Class
Generator
AttentionGAN-v1/models.py:6
↓ 2 callers
Class
Discriminator
AttentionGAN-v1/models.py:82
↓ 2 callers
Class
Discriminator
Discriminator network with PatchGAN.
AttentionGAN-v1-multi/model.py:74
↓ 2 callers
Class
Generator
Generator network.
AttentionGAN-v1-multi/model.py:22
↓ 2 callers
Class
ImageDataset
AttentionGAN-v1/datasets.py:9
↓ 2 callers
Class
LambdaLR
AttentionGAN-v1/utils.py:108
↓ 2 callers
Class
NLayerDiscriminator
Defines a PatchGAN discriminator
AttentionGAN-geo/networks.py:712
↓ 2 callers
Class
NLayerDiscriminator
Defines a PatchGAN discriminator
models/networks.py:712
↓ 2 callers
Class
ReplayBuffer
AttentionGAN-v1/utils.py:86
↓ 2 callers
Class
ResnetGenerator
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 callers
Class
ResnetGenerator
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 callers
Class
UnetGenerator
Create a Unet-based generator
AttentionGAN-geo/networks.py:610
↓ 2 callers
Class
UnetGenerator
Create a Unet-based generator
models/networks.py:610
↓ 1 callers
Class
CelebA
Dataset class for the CelebA dataset.
AttentionGAN-v1-multi/data_loader.py:10
↓ 1 callers
Class
CustomDatasetDataLoader
Wrapper class of Dataset class that performs multi-threaded data loading
data/__init__.py:62
↓ 1 callers
Class
HTML
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 callers
Class
Identity
AttentionGAN-geo/networks.py:14
↓ 1 callers
Class
Identity
models/networks.py:14
↓ 1 callers
Class
ImageFolder
data/image_folder.py:39
↓ 1 callers
Class
Logger
AttentionGAN-v1/utils.py:24
↓ 1 callers
Class
Logger
Tensorboard logger.
AttentionGAN-v1-multi/logger.py:4
↓ 1 callers
Class
PixelDiscriminator
Defines a 1x1 PatchGAN discriminator (pixelGAN)
AttentionGAN-geo/networks.py:760
↓ 1 callers
Class
PixelDiscriminator
Defines a 1x1 PatchGAN discriminator (pixelGAN)
models/networks.py:760
↓ 1 callers
Class
ResidualBlock
Residual Block with instance normalization.
AttentionGAN-v1-multi/model.py:7
↓ 1 callers
Class
ResnetBlock
AttentionGAN-v1/models.py:58
↓ 1 callers
Class
ResnetBlock
Define a Resnet block
AttentionGAN-geo/networks.py:550
↓ 1 callers
Class
ResnetBlock
Define a Resnet block
models/networks.py:550
↓ 1 callers
Class
ResnetGenerator_our
AttentionGAN-geo/networks.py:379
↓ 1 callers
Class
ResnetGenerator_our
models/networks.py:379
↓ 1 callers
Class
Solver
Solver for training and testing StarGAN.
AttentionGAN-v1-multi/solver.py:13
↓ 1 callers
Class
TestOptions
This class includes test options. It also includes shared options defined in BaseOptions.
options/test_options.py:4
↓ 1 callers
Class
TrainOptions
This class includes training options. It also includes shared options defined in BaseOptions.
options/train_options.py:4
↓ 1 callers
Class
Visualizer
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 callers
Class
resnet_block
AttentionGAN-geo/networks.py:520
↓ 1 callers
Class
resnet_block
models/networks.py:520
Class
AttentionGANModel
AttentionGAN-geo/attention_gan_model.py:8
Class
AttentionGANModel
models/attention_gan_model.py:8
Class
BaseDataset
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
Class
BaseModel
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
Class
BaseOptions
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
Class
CycleGAN1Model
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
Class
GANLoss
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
Class
GANLoss
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
Class
GetData
A Python script for downloading CycleGAN or pix2pix datasets. Parameters: technique (str) -- One of: 'cyclegan' or 'pix2pix'. ver
util/get_data.py:11
Class
UnalignedDataset
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