Unrolled Fourier Disparity Layers

This repository is the pytorch implementation of the method proposed in the paper: B. Le Bon, M. Le Pendu, C. Guillemot. "Unrolled Fourier Disparity Layer Optimization For Scene Reconstruction From Few-Shots Focal Stacks", ICASSP 2023.

Usage

The purpose of this code is to unroll the Fourier Disparity Layers optimization in order to reconstruct a light field or a set of refocus images from focal stack images as measurements.

Training

Preparation

Before launching the training, you need to prepare the following files:

• Training dataset and validation dataset files listing the path to the corresponding dataset folders. For more information on the format, refers to the dataset folder LF_example/ and the LF_datasets_example.txt file
• A yaml configuration file to set up the training parameters. Config/UnrolledADMMFDL_5x5_2fs.yaml is an example of a configuration file.

Command line

The following command line is an example of how to launch the training:

python main.py --training_dataset training_datasets.txt --validation_dataset validation_datasets.txt --config Configs/UnrolledADMMFDL_5x5_2fs.yaml --model_name my_model_name --mode train.

The model my_model_name will be saved in the Models/ directory.

Testing

Preparation

Before launching the testing, you need to prepare the following files:

• A testing dataset file listing the path to the corresponding dataset folders. For more information on the format, refers to the dataset folder LF_example and the LF_datasets_example.txt file
• A yaml configuration file to set up the testing parameters. Config/UnrolledADMMFDL_5x5_2fs.yaml is an example of a configuration file.
• A trained model located in the Models/ repertory.

Command line

The following command line is an example of how to launch the testing to reconstruct a light field:

python main.py --testing_dataset testing_datasets.txt --config Configs/UnrolledADMMFDL_5x5_2fs.yaml --model_name my_model_name --mode test --save_directory save_directory_folder --output_type views

The following command line is an example of how to launch the testing to reconstruction a set of refocus images:

python main.py --testing_dataset testing_datasets.txt --config Configs/UnrolledADMMFDL_5x5_2fs.yaml --model_name my_model_name --mode test --save_directory save_directory_folder --output_type FS

The model my_model_name in the Models/ directory will be used, and the results will be saved in the save_directory_folder folder.