{"repo":"fh2019ustc/DocTr","free":true,"listed":false,"github":"https://github.com/fh2019ustc/DocTr","clone":"git clone https://github.com/fh2019ustc/DocTr.git","description":"The official code for “DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction”, ACM MM, Oral Paper, 2021.","language":"Python","stars":443,"topics":["document-image-processing","document-image-rectification","document-unwarping","ocr","pytorch-implementation"],"license":null,"category":"media-processing","readme_excerpt":"🚀 Exciting update! We have created a demo for our paper on Hugging Face Spaces, showcasing the capabilities of our DocTr. Check it out here! 🔥 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! Our new work exhibits state-of-the-art performances on the DocUNet Benchmark dataset: DocScanner: Robust Document Image Rectification with Progressive Learning with Repo. 🔥 Good news! A comprehensive list of Awesome Document Image Rectification methods is available. DocTr DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction ACM MM 2021 Oral Any questions or discussions are welcomed! 🚀 Demo (Link) 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. 4. Our demo environment is based on a CPU infrastructure, and due to image transmission over the network, some display latency may be experienced. Training DocTr consists of two main components: a geometric unwarping transformer (GeoTr) and an illumination correction transformer (IllTr). - For geometric unwarping, we train the GeoTr network using the Doc3D and DTD dataset. - For illumination correction, we train the IllTr network based on the DocProj dataset. Inference 1. Download the pretrained models from Google Drive or Baidu Cloud, and put them to $ROOT/model pretrained/ . 2","default_branch":null,"files":null,"tree":[],"storefront":"/r/fh2019ustc","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/fh2019ustc/DocTr/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."}