This is the opensourced OCR repository of DAVAR Lab, from Hikvision Research Institute, China.
We begin to maintain this code repository to release the implementations of our recent academic publishments and some re-implementations of previous popular algorithms/modules in OCR.
We also provide some of the ablation experiment comparasions for better reproduction.
Note: Due to the policy limits of the company. All of the codes were re-implemented based on the open-source frameworks, mmdetection-2.11.0 and mmcv-1.3.4, from open-mmlab. The code architecture also refers to mmocr, which means these two frameworks can be well compatible to each other.
To date, davarocr contains the following algorithms:
Text Detection
-
EAST (CVPR 2017)
-
MASK RCNN (ICCV 2017)
-
Text Perceptron Det (AAAI 2020)
Text Recognition
-
Attention (CVPR 2016)
-
CRNN (TPAMI 2017)
-
ACE (CVPR 2019)
-
SPIN (AAAI 2021)
-
RF-Learning (ICDAR 2021)
Text Spotting
-
Text Perceptron E2E (AAAI 2020)
-
MANGO (AAAI 2021)
Information Extraction
- TRIE (ACM MM 2020)
Video Text Spotting
-
YORO (ACM MM 2019)
-
FREE (to be released) (TIP 2021)
Table Recognition
- LGPMA (ICDAR 2021)
Layout Recognition
- VSR (to be released) (ICDAR 2021)
The recommended environment requirements can be found in mmdetection. Follows are the lowest compatible environment.
Basic Env | version |
---|---|
Python | 3.6+ |
cuda | 10.0+ |
cudnn | 7.6.3+ |
pytorch | 1.3.0+ |
torchvision | 0.4.1+ |
opencv | 3.0.0+ |
For some of the algorithms (EAST, Text Perceptron), C++ version opencv are required. If you do not need to use these algorithms, you could temporarily ignore the error about 'opencv.hpp' or remove the related codes temporarily.
To Download the repository and install the davarocr, please follow the instructions:
git clone https://github.com/hikopensource/DAVAR-Lab-OCR.git
cd DAVAR-Lab-OCR/
bash setup.sh
This script will automatically download and install the "mmdetection" and "mmcv-full". You can also manually install them followinging the official instructions
Going to the specific algorithm's directory to see more details.
For the problems existing in the process of installation and researching, we will reasonably collect them and provide corresponding solutions. Please refer to FAQ.md for details.
DavarOCR v0.3.0 was released in 22/09/2021. Please refer to Changelog.md for details and release history.
This project is released under the Apache 2.0 license
The copyright of corresponding contributions of our implementations belongs to Davar-Lab, Hikvision Research Institute, China, and other codes from open source repository follows the original distributive licenses.
See latest news in DAVAR-Lab. If you have any question and suggestion, please feel free to contact us. Contact email: qiaoliang6@hikvision.com, xuyunlu@hikvision.com, chengzhanzhan@hikvision.com.