Deep HDR Imaging

The Keras Implementation of the Deep HDR Imaging via A Non-Local Network - TIP 2020

Content

• Deep-HDR-Imaging
• Getting Started
• Running
• References
• Citations

Getting Started

• Clone the repository

Prerequisites

• Tensorflow 2.2.0+
• Tensorflow_addons
• Python 3.6+
• Keras 2.3.0
• PIL
• numpy

pipinstall-rrequirements.txt

Running

Training

• Preprocess

  • Download the training data and testing data.

  • Run this file to generate data. (Please remember to change path first)

  python src/create_dataset.py
  

• Train NHDRRNet

  python main.py
  

• Test NHDRRNet

  python test.py
  

Usage

Training

usage: main.py [-h] [--images_path IMAGES_PATH] [--test_path TEST_PATH]
[--lr LR] [--gpu GPU] [--num_epochs NUM_EPOCHS] [--train_batch_size TRAIN_BATCH_SIZE]
[--display_ep DISPLAY_EP] [--checkpoint_ep CHECKPOINT_EP]
[--checkpoints_folder CHECKPOINTS_FOLDER]
[--load_pretrain LOAD_PRETRAIN] [--pretrain_dir PRETRAIN_DIR]
[--filter FILTER] [--kernel KERNEL]
[--encoder_kernel ENCODER_KERNEL]
[--decoder_kernel DECODER_KERNEL]
[--triple_pass_filter TRIPLE_PASS_FILTER]

optional arguments: -h, --help show this help message and exit
--images_path training path
--lr LR
--gpu GPU
--num_epochs NUM of EPOCHS
--train_batch_size training batch size
--display_ep display result every "x" epoch
--checkpoint_ep save weights every "x" epoch
--checkpoints_folder folder to save weight
--load_pretrain load pretrained model
--pretrain_dir pretrained model folder
--filter default filter
--kernel default kernel
--encoder_kernel encoder filter size
--decoder_kernel decoder filter size
--triple_pass_filter number of filter in triple pass

Testing

The weight file was deprecated. Will be updated soon.

usage: test.py [-h] [--test_path TEST_PATH] [--gpu GPU]
[--weight_test_path WEIGHT_TEST_PATH] [--filter FILTER]
[--kernel KERNEL] [--encoder_kernel ENCODER_KERNEL]
[--decoder_kernel DECODER_KERNEL]
[--triple_pass_filter TRIPLE_PASS_FILTER]

optional arguments: -h, --help show this help message and exit
--test_path test path
--weight_test_path weight test path
--filter default filter
--kernel default kernel
--encoder_kernel encoder filter size
--decoder_kernel decoder filter size
--triple_pass_filter number of filter in triple pass

Result

License

This project is licensed under the MIT License - see the LICENSE file for details

References

[1] Deep HDR Imaging via A Non-Local Network - TIP 2020 link

[3] Training and Testing dataset - link

Citation

 @ARTICLE{8989959, author={Q. Yan and L. Zhang and Y. Liu and Y. Zhu and J. Sun and Q. Shi and Y. Zhang}, journal={IEEE Transactions on Image Processing}, title={Deep HDR Imaging via A Non-Local Network}, year={2020}, volume={29}, number={}, pages={4308-4322},}

Acknowledgments

• This work based on the paper mentioned above with few modification:
  • the fixed size of the adaptive average pooling (16 instead of 32 as assigned in the paper)
  • the number of triple pass module is defined as 10 to match the number of 32M as stated in the paper.
• Any ideas on updating or misunderstanding, please send me an email: vovantu.hust@gmail.com
• If you find this repo helpful, kindly give me a star.

Update: I have just released my work on HDR imaging using Attention non-local network. Please check as follow: https://github.com/tuvovan/ANL-HDRI