EasyOCR-cpp OpenVINO

Custom C++ implementation of EasyOCR with OpenVINO backend

Built and tested on Windows 11, openvino2024.4.0 and OpenCV 4.6

This C++ project implements the pre/post processing to run a OCR pipeline consisting of a text detector CRAFT, and a CRNN based text recognizer. Unlike the EasyOCR python which is API based, this repo provides a set of classes to show how you can integrate OCR in any C++ program for maximum flexibility. The openvinoExample.cpp main program highlights how to utilize all elements of the EasyOCR-cpp pipeline. Because a test program is only provided, make sure to configure your input image within OpenvinoExample.cpp if you only plan to utilize the test program.

Setup with MSVS

Dependencies

Install OpenVINO

Use OpenCV Windows installer and unzip (v4.6) - > OpenCV libs

Make sure to change the location in the Makefile for OpenCV to point to your OpenCV build dir

Set up OpenVINO environment:

C:\Program Files (x86)\Intel\openvino_2024.4.0\setupvars.bat 

Set up OpenCV environment

C:\OpenCV\opencv\build\setup_vars_opencv4.cmd

Create a build directory within the repo, cd to it and run cmake

mkdir build
cd build
cmake  ..

This will generate a solution within the build folder you can open up in Visual Studio. Make sure to use the Release config when building

Running

Configure your recognition model, input image and inference device here. Configure a characters list for your language here By default the openvinoTest program is using the english recognition model, test.jpg as an input image which comes in the repo and running inference on CPU.

Launch from command-line, or within Visual Studio after building. Don't forget to source environment variables for both OpenVINO and OpenCV as described above

Adding more languages support

This repo contains a recognition model for English recognition_model.xml and for the most popular european languages based on latin symbols (German, French, Inalian, Spanish, etc.) recognition_model_latin.xml. Please note that for the inference with OpenVINO both .xml and .bin files are required, they should have the same name and be placed in the same folder, but in a code you can specify only path to the .xml file. For both languages there are corresponding language characters files: english_g2_characters.txt and latin_char.txt.

If you need models for more languages, you can get them already in OpenVINO format following these steps:

1. Create and activate python virtual environment:

   python -m venv env
   env\Scripts\activate
   

2. Install a patched Python EasyOCR version:

   pip install git+https://github.com/avbelova/EasyOCR.git@model-convert-and-save
   

3. Run EasyOCR with the needed language as usuall in Python. For example the following code gets a Chineese recognition model:

   import cv2
   import easyocr
   
   img=cv2.imread("chinese.jpg")
   reader = easyocr.Reader(['ch_sim'], gpu="ov_cpu")
   result = reader.readtext(img, detail = 0)
   print(result)
   

4. Find a recogntion model in OpenVINO format in the directory from where you run EasyOCR in the previous step.
5. Don't forget to obtain a character list for your model.