First set a config file in options/train/, then run as following:
python train.py -opt options/train/train_InvDN.yml
First set a config file in options/test/, then run as following:
python test_Real.py -opt options/test/test_InvDN.yml
Pretrained models will be released later.
The code framework follows BasicSR. It mainly consists of four parts - Config
, Data
, Model
and Network
.
Let us take the train command python train.py -opt options/train/train_InvDN.yml
for example. A sequence of actions will be done after this command.
train.py
is called.- Reads the configuration in
options/train/train_InvDN.yml
, including the configurations for data loader, network, loss, training strategies and etc. The config file is processed byoptions/options.py
. - Creates the train and validation data loader. The data loader is constructed in
data/__init__.py
according to different data modes. - Creates the model (is constructed in
models/__init__.py
according to different model types). - Start to train the model. Other actions like logging, saving intermediate models, validation, updating learning rate and etc are also done during the training.
Config: options/
Configure the options for data loader, network structure, model, training strategies and etc.
Data: data/
A data loader to provide data for training, validation and testing.
Model: models/
Construct models for training and testing.
Network: models/modules/
Construct different network architectures.