包含一些常用的修复图像质量指标（例如，L1、L2、SSIM、PSNR和LPIPS）.zip

# I am not maintaining this repo anymore. Please refer to [this repo](https://github.com/SayedNadim/Image-Quality-Evaluation-Metrics) for updated version. Thank you. ## Inpainting Evaluation Metrics (On-going) The goal of this repo is to provide a common evaluation script for image inpainting tasks. It contains some commonly used image quality metrics for inpainting (e.g., L1, L2, SSIM, PSNR and [LPIPS](https://github.com/richzhang/PerceptualSimilarity)). Pull requests and corrections/suggestions will be cordially appreciated. ### Please Note - Images are scaled to [0,1]. If you need to change the data range, please make sure to change the data range in SSIM and PSNR. - Number of generated images and ground truth images have to be exactly same. - I have resized the images to be (`256,256`). You can change the resolution based on your needs. - Please make sure that all the images (generated and gt images) are in the corresponding folders. Currently,it can not calculate metrics if there are sub-folders. I will update the code to calculate for sub-folders as well. - LPIPS is a bit slow. So, if you have lots of images, it might take a lot of time. (For ~1000 images, it took around ~15-20 minutes on my personal setup (1 TitanXP). Other metrics are fast and took around ~20 seconds to compute.) ### Requirements - PyTorch ( `>= 1.0` ) - Python ( `>=3.5` ) - [PyTorch Image Quality (PIQ)](https://github.com/photosynthesis-team/piq) ( `$ pip install piq` ) ### Usage - Usable Arguments - `--input_path` - path to your generated images (required). - `--gt_path` - path to your ground truth images (required). - `--batch_size` - batch size you want to use (Default to 4). - `--image_width` - width of the image (both generated image and ground truth images will be resized to this width. Default to 256). - `--image_height` - width of the image (both generated image and ground truth images will be resized to this width. Default to 256). - `--threads` - threads to be used for multi-processing (Default to 4). - Please provide paths of the folders (i.e., folder of generated images and folder of ground truth images). `python main.py --input_path path/to/generated/images --gt_path path/to/ground/truth/images` - If you need to save it in a `.txt` file, then simply run `python main.py --input_path path/to/generated/images --gt_path path/to/ground/truth/images >> results.txt` ### To-do - [x] L1 - [x] L2 - [x] SSIM - [x] PSNR - [x] LPIPS - [ ] FID - [ ] IS ### Acknowledgement Thanks to [PhotoSynthesis Team](https://github.com/photosynthesis-team/piq) for the wonderful implementation of the metrics. Please cite accordingly if you use PIQ for the evaluation. Cheers!!