# R2CNN.pytorch **Repository Path**: Eric3911/R2CNN.pytorch ## Basic Information - **Project Name**: R2CNN.pytorch - **Description**: 旋转目标检测 - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-06-05 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # R2CNN in PyTorch 1.2 Pytorch Implementation of "R2CNN Rotational Region CNN for Orientation Robust Scene Text Detection" [paper](https://arxiv.org/abs/1706.09579) , it is based on facebook's [maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark) ## Installation Check [INSTALL.md](INSTALL.md) for installation instructions. ## Perform training on ICDAR2015 dataset **1. Download [icdar2015](https://rrc.cvc.uab.es/?ch=4&com=downloads) dataset and pretrain model from maskrcnn-bencmark** ```` cd ./tools mkdir datasets ln -s PATH_ICDAR2015 datasets/ICDAR2015 mkdir pretrain cd pretrain wget https://download.pytorch.org/models/maskrcnn/e2e_faster_rcnn_R_50_FPN_1x.pth ```` **2. Convert annotations to COCO style** ```` cd ./tools/ICDAR2015 python convert_icdar_to_coco.py ```` **3. start training** ```` cd ./tools python train_net.py ```` ## Inference on ICDAR 2015 dataset **1. Download [model](https://drive.google.com/file/d/1eIJ7nl0Ei_yn3S7dDXNIhMy3BcZ48VYp/view?usp=sharing) or use your own model** **2. single image inference** ```` cd ./tools python inference_engine.py ```` ![01](tools/ICDAR2015/img_14.jpg) ![02](tools/ICDAR2015/img_60.jpg) ![03](tools/ICDAR2015/img_108.jpg) ## New feature compared with maskrcnn-benchmark - new data structure quad_bbox(x1, y1, x2, y2, x3, y3, x4, y4) is defined to replace bbox(x1, y1, x2, y2) - an extra branch in box_head which regress offsets of 4 points - post processor of rpn is adjusted to detect text objects ## TODO - [x] ## Citations Please consider citing this project in your publications if it helps your research. The following is a BibTeX reference. The BibTeX entry requires the `url` LaTeX package. ``` @misc{r2cnn, author = {Yingying Jiang, Xiangyu Zhu, Xiaobing Wang, Shuli Yang, Wei Li, Hua Wang, Pei Fu, Zhenbo Luo}, title = {R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection}, conference = {ICPR2018} year = {2017}, } ```