{"repo":"fh2019ustc/DocScanner","free":true,"listed":false,"github":"https://github.com/fh2019ustc/DocScanner","clone":"git clone https://github.com/fh2019ustc/DocScanner.git","description":"The official repo for “DocScanner: Robust Document Image Rectification with Progressive Learning”, IJCV, 2025.","language":"Python","stars":346,"topics":["document-image-processing","document-image-rectification","ocr","document-image-dewarping"],"license":null,"category":"media-processing","readme_excerpt":"🔥 2025.3.24: Good news! Our work has been accepted by International Journal of Computer Vision (IJCV). 🔥 2024.4.28: Good news! The code and pre-trained model of DocScanner are now released! 🚀 Good news! The online demo for DocScanner is now live, allowing for easy image upload and correction. 🔥 Good news! Our new work DocTr++: Deep Unrestricted Document Image Rectification comes out, capable of rectifying various distorted document images in the wild. 🔥 Good news! A comprehensive list of Awesome Document Image Rectification methods is available. DocScanner This is a PyTorch/GPU re-implementation of the paper DocScanner: Robust Document Image Rectification with Progressive Learning. 🚀 Demo (Link) Note ：The model version used in the demo corresponds to \"DocScanner-L\" as described in the paper. 1. Upload the distorted document image to be rectified in the left box. 2. Click the \"Submit\" button. 3. The rectified image will be displayed in the right box. Examples Training - We train the Document Localization Module using the Doc3D dataset. Besides, DTD dataset is exploited for background data enhancement. - We train the Progressive Rectification Module using the Doc3D dataset. Here we use the background-excluded document images for training. Inference 1. Put the pre-trained DocScanner-L to $ROOT/model pretrained/ . 2. Put the distorted images in $ROOT/distorted/ . 3. Run the script and the rectified images are saved in $ROOT/rectified/ by default. Evaluation - Important. In ","default_branch":null,"files":null,"tree":[],"storefront":"/r/fh2019ustc","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/fh2019ustc/DocScanner/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."}