• model.py : model architecture

• train_srgan.py : run this file to train from scratch or continue training of the SRGAN model

• generate_srgan.py : run this file to generate a 16 times superscaled image from TMC2 image

• evaluation.py : run this file to evaluate our 16 times upsampled data with test ohrc over SSIM evalaution metric

• srgan_config.py : configure training or generating parameters here

• dataset.py : creates batches of tensors from training or testing data using dataloader

• image_quality_assessment.py : code for evaluation metrics

• requirements.txt : environment requirements

• cascade.py : premature version of generate.py

• train_data : strore train data here

• pretrained_weights : strore pretrained weights here

• results : best and latest weights for both generator and discrimniator while training will be saved here

• samples : logs and per epoch weights can be seen here

• g_model weights : g_last.pth.tar
• d_model weights : d_last.pth.tar
• These can be used for the purpose of further training the model over custom dataset.
• g_model weights : g_best.pth.tar

Chandrayan TMC-2 : Apollo-12 and Apollo-16 from ISSDC website NASA LRO: Apollo-12 and Apollo-16 from LROC-NAC website

All three training, testing and evaluation only need to modify the ./srgan_config.py file. For all the bash commands current working directory is expected to be SRGAN-implementation

Modify the srgan_config.py file.

• line 29: mode change to generate.
• line 31: exp_name change to a new experiment name each time training.
• line 102: g_model_weights_path change to ./pretrained_models/generate/g_best.pth.tar.
• the input low resoltion files must be of dimension AxA where A is a multiple of 24
• store the input low resoltion files in the directory ./generate_data/TMC2/dim_1x.
• the corresponding output images can be found in the directory ./generate_data/TMC2/dim_16x.

python generate_srgan.py

Modify the srgan_config.py file.

• line 29: mode change to train.
• line 31: exp_name change to a new experiment name each time training.
• line 47: pretrained_d_model_weights_path change to ./pretrained_models/train/d_last.pth.tar.
• line 48: pretrained_g_model_weights_path change to ./pretrained_models/train/g_last.pth.tar.
• best and last trained weights of both generator and discrimnator would be saved in ./results/{exp_name}.

python train_srgan.py

Modify the srgan_config.py file.

• line 29: mode change to evaluate.

python evaluation.py

• this unzipped folder can also be used to run evaluation over other metrics
• per image size in this folder is 3840x3840 8-bit images

pip install opencv-python numpy tqdm torch torchvision natsort typing scipy
## or
pip install -r requirements.txt