https://github.com/tuvovan/anl-hdri
High Dynamic Range Image Synthesis via Attention Non-Local Network
https://github.com/tuvovan/anl-hdri
attention-network convolutional-autoencoder convolutional-neural-networks hdr-image hdr-imaging
Last synced: 3 months ago
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High Dynamic Range Image Synthesis via Attention Non-Local Network
- Host: GitHub
- URL: https://github.com/tuvovan/anl-hdri
- Owner: tuvovan
- License: mit
- Created: 2020-09-18T13:18:48.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-06-13T05:25:36.000Z (over 4 years ago)
- Last Synced: 2025-03-26T07:23:13.774Z (7 months ago)
- Topics: attention-network, convolutional-autoencoder, convolutional-neural-networks, hdr-image, hdr-imaging
- Language: Python
- Homepage:
- Size: 3.23 MB
- Stars: 7
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ANLHDR Imaging
High Dynamic Range Image Synthesis via Attention Non-Local Network
## Content
- [ANL-HDRI](#anl-hdri)
- [Getting Started](#getting-tarted)
- [Running](#running)
- [References](#references)
- [Citations](#citation)
## Getting Started
- Clone the repository
### Prerequisites
- Tensorflow 2.2.0+
- Tensorflow_addons
- Python 3.6+
- Keras 2.3.0
- PIL
- numpy
```python
pip install -r requirements.txt
```
## Running
### Training
- Preprocess
- Download the [training data](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/PaperData/SIGGRAPH17_HDR_Trainingset.zip) and [testing data](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/PaperData/SIGGRAPH17_HDR_Testset.zip).
- Run this file to generate data. (Please remember to change path first)
```
python src/create_dataset.py
```
- Train ANL-HDRI
```
python main.py
```
- Test ANL-HDRI
- Download weights [here](https://drive.google.com/file/d/1G94mGLbKSLcvzl9CRs5WY305meG13pWh/view?usp=sharing)
```
python test.py --weight_test_path ANLNet.h5 --test_path Test/EXTRA/001/
```
## 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](https://github.com/tuvovan/ANL-HDRI/blob/master/LICENSE) file for details
## References
[1] Training and Testing dataset - [link](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/)
## Citation
```
@ARTICLE{8989959, author={Tu V.V},
title={High Dynamic Range Image Synthesis via Attention Non-Local Network},
year={2020},
url={github.com/tuvovan/ANL-HDRI},}
```
## Acknowledgments
- My work is done on my sparse time so I should have some mistake or further possible improvement.
- Any ideas on updating or misunderstanding, please send me an email:
- If you find this repo helpful, kindly give me a star.