https://github.com/zhkkke/harmonizer

High-Resolution Image/Video Harmonization [ECCV 2022]
https://github.com/zhkkke/harmonizer

image-enhancement image-harmonization video-enhancement video-harmonization

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High-Resolution Image/Video Harmonization [ECCV 2022]

• Host: GitHub
• URL: https://github.com/zhkkke/harmonizer
• Owner: ZHKKKe
• Created: 2022-07-04T08:57:09.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2023-01-23T10:09:10.000Z (almost 2 years ago)
• Last Synced: 2024-12-17T10:06:02.874Z (9 days ago)
• Topics: image-enhancement, image-harmonization, video-enhancement, video-harmonization
• Language: Python
• Homepage:
• Size: 52.4 MB
• Stars: 328
• Watchers: 11
• Forks: 34
• Open Issues: 11
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
Harmonizer: High-Resolution Image/Video Harmonization


Harmonizer: Learning to Perform White-Box

Image and Video Harmonization (ECCV 2022)




  Paper |

  Demo |

  Code |

  License |

  Citation |

  Contact





  Harmonizer Result Video |

  Enhancer Result Video





Harmonizer is a lightweight (20MB) model enabled image/video harmonization up to 8K resolution.

With GPUs, Harmonizer has real-time performance at Full HD resolution.





Enhancer is a model applied the Harmonizer architecture for image/video color enhancement.



---

## Demo

In our demos, the Harmonizer model is trained on the *iHarmony4* dataset, while the Enhancer model is trained on the *FiveK + HDRPlus* datasets.

### Online Demo

Try our online demos for fun without code!

| Image Harmonization | Image Enhancement |

| :---: | :---: |

| [Online Demo](https://zhke.io/?harmonizer_demo) | [Online Demo](https://zhke.io/?enhancer_demo) |



### Offline Demo

We provide offline demos for image/video harmonization/enhancement.

| Image Harmonization | Video Harmonization | Image Enhancement | Video Enhancement |

| :---: | :---: | :---: | :---: |

| [Offline Demo](demo/image_harmonization) | [Offline Demo](demo/video_harmonization) | [Offline Demo](demo/image_enhancement) | [Offline Demo](demo/video_enhancement) |

## Code

### Training

The training code is released in the folder `./src/train`.  

Refer to [README.md](src/train/README.md) for more details about training.

### Validation

We provide PyTorch validation code to reproduce the iHarmony4 results reported in our [paper](https://arxiv.org/abs/2207.01322), please:

1. Download the Harmonizer model pre-trained on the iHarmony4 dataset from [this link](https://drive.google.com/file/d/15XGPQHBppaYGnhsP9l7iOGZudXNw1WbA/view?usp=sharing) and put it in the folder `./pretrained`.

2. Download the four subsets of iHarmony4 from [this repository](https://github.com/bcmi/Image-Harmonization-Dataset-iHarmony4) and put them in the folder `./dataset/harmonization/iHarmony4`.

3. Install python requirements. In the root path of this repository, run: 

    ```

    pip install -r src/requirements.txt

    ```

5. For validation, in the root path of this repository, run:

    ```

    python -m src.val_harmonizer \

           --pretrained ./pretrained/harmonizer \

           --datasets HCOCO HFlickr HAdobe5k Hday2night \

           --metric-size 256

    ```

    - You can change `--datasets` to validate a specific subset.  

    - You can remove `--metric-size` to calculate the metrics without resizing the outputs.

    - The metric values may slightly different from our [paper](https://arxiv.org/abs/2207.01322) due to the dependency versions.

## License

This project is released under the [Creative Commons Attribution NonCommercial ShareAlike 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode) license.

## Citation

If this work helps your research, please consider to cite:

```bibtex

@InProceedings{Harmonizer,

  author = {Zhanghan Ke and Chunyi Sun and Lei Zhu and Ke Xu and Rynson W.H. Lau},

  title = {Harmonizer: Learning to Perform White-Box Image and Video Harmonization},

  booktitle = {European Conference on Computer Vision (ECCV)},

  year = {2022},

}

```

## Contact

This repository is maintained by Zhanghan Ke ([@ZHKKKe](https://github.com/ZHKKKe)).  

For questions, please contact `[email protected]`.