|
Download PolyuColor/README.md from createcolor/NPRC24: direct link, hf CLI and curl.
- Browser
- Download file 2.42 kB
-
https://huggingface.co/createcolor/NPRC24/resolve/main/PolyuColor/README.md
- Command line
-
hf download hf://createcolor/NPRC24/PolyuColor/README.md
-
curl -L -o README.md https://huggingface.co/createcolor/NPRC24/resolve/main/PolyuColor/README.md
2.42 kB
| # Team: **play1play** | |
| for 'Night Photography Rendering Challenge' | |
| This repo contains the source code of [Night Photography Rendering Challenge 2024](https://nightimaging.org/). | |
| ## How to run | |
| ### Run without Docker | |
| - Install python >= 3.9 | |
| - Install the required packages: `pip install -r requirements.txt` | |
| - Put the test images in the `data` folder or specify the input image path with `-p` option. | |
| - Run the script: | |
| ``` | |
| python run.py -p <input_image_path> -o <output_image_path> | |
| ``` | |
| - The output images will be saved in the `output` folder or specifiy the output path with `-o` option. | |
| ### Run with Docker | |
| - Build the docker image from beginning (optional): | |
| ``` | |
| docker build -t play1play . | |
| ``` | |
| - Run the docker container with gpu on linux: | |
| ``` | |
| docker run -it --rm --gpus=all -v $(pwd)/data:/data play1play ./run.sh | |
| ``` | |
| `Do not forget to to --gpus flag, our model requires GPU to run.` | |
| ## Update | |
| *2024.3.21:* | |
| Final version v3.0 is released for 3rd validation! | |
| Key features: | |
| - Utilize the patch-based and calibration-based white-balance algorithm to improve the image quality. | |
| - Modify the resizing strategy to improve the image quality. | |
| *2024.3.16:* | |
| Release v2.0 for 3rd validation! | |
| Key features: | |
| - Increase the overall saturation and brightness of the image. | |
| - Add more contrast to the image. | |
| - Add more dynamic range to the image. | |
| Algorithm changes: | |
| - Add luma shading correction (LSC) module | |
| - Add auto-contrast module (dynamic gamma) | |
| - LSC, LTM, auto-contrast module can dynamiclly adjust the parameters based on the camera gain from the metadata. | |
| - Add another white-balance process at the end of the pipeline to further improve the image quality. | |
| Key algorithm parameter explanation: | |
| - k_th: defines the threshold for the noise level, higher means tolerant to noise, lower means more sensitive to noise. For this sensor, default is 2.5e-3. `Note that this paramerts are shared by all the modules, and hence defined as the member varibale in RawProcessingPipelineDemo class.` | |
| - s of local_tone_mapping: defines how to apply the gain map to different image channels. Higher means more saturated, lower means less saturated. Default is 0.7. `Currently, s is automatically adjusted based on the camera gain from the metadata.` | |
| *2024.3.7:* | |
| release v1.0 for 3rd validation! | |
| ---- | |
| ## Version-1 | |
| - TMO-ratio50 | |
| ----- | |
| ## Version-2 | |
| - TMO: ratio50 | |
| - Gamma: 1.5 | |
| - Contrast:[low=2,high=0.2] | |
| - Post-AWB: GI | |