{"repo":"aiff22/PyNET-PyTorch","free":true,"listed":false,"github":"https://github.com/aiff22/PyNET-PyTorch","clone":"git clone https://github.com/aiff22/PyNET-PyTorch.git","description":"Generating RGB photos from RAW image files with PyNET (PyTorch)","language":"Python","stars":391,"topics":["pynet","pytorch-implementation","image-enhancement","image-processing","image-reconstruction","deep-learning","raw-to-rgb","computer-vision","mobile","photography"],"license":null,"category":"machine-learning","readme_excerpt":"Replacing Mobile Camera ISP with a Single Deep Learning Model 1. Overview [[Paper]](https://arxiv.org/pdf/2002.05509.pdf) [[TensorFlow Implementation]](https://github.com/aiff22/PyNET) [[Project Webpage]](https://aiff22.github.io/pynet.html) :warning: This is an alternative PyTorch implementation of the paper. The original codes and pre-trained models can be found here. This repository provides PyTorch implementation of the RAW-to-RGB mapping approach and PyNET CNN presented in this paper. The model is trained to convert RAW Bayer data obtained directly from mobile camera sensor into photos captured with a professional Canon 5D DSLR camera, thus replacing the entire hand-crafted ISP camera pipeline. The provided pre-trained PyNET model can be used to generate full-resolution 12MP photos from RAW (DNG) image files captured using the Sony Exmor IMX380 camera sensor. More visual results of this approach for the Huawei P20 and BlackBerry KeyOne smartphones can be found here. 2. Prerequisites - Python: scipy, numpy, imageio and pillow packages - PyTorch + TorchVision libraries - Nvidia GPU 3. First steps - Download the pre-trained PyNET model (PSNR: 21.17, MS-SSIM: 0.8623) and put it into models/original/ folder. - Download Zurich RAW to RGB mapping dataset and extract it into raw images/ folder. This folder should contain three subfolders: train/ , test/ and full resolution/ Please note that Google Drive has a quota limiting the number of downloads per day. To avoid it, you can l","default_branch":null,"files":null,"tree":[],"storefront":"/r/aiff22","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/aiff22/PyNET-PyTorch/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}