Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch
Automatic Number Plate Recognition (ANPR) is the process of reading the characters on the plate with various optical character recognition (OCR) methods by separating the plate region on the vehicle image obtained from automatic plate recognition.
The dataset I use for license plate detection:
https://www.kaggle.com/datasets/andrewmvd/car-plate-detection
Clone repo and install requirements.txt in a Python>=3.7.0 environment.
git clone https://github.com/mftnakrsu/Automatic-number-plate-recognition-YOLO-OCR.git # clone
cd Automatic-number-plate-recognition-YOLO-OCR
pip install -r requirements.txt # install
After the req libraries are installed, you can run the project by main.py.
python main.py
The pipeline in the project is as follows:
A streamlit based implementation of Automatic Number Plate Recognition for cars and other vehicles using images or live camera feed.
The entire code for the webapp can be found here.
https://www.researchgate.net/publication/319198085_License_Number_Plate_Recognition_System_using_Entropy_basedFeatures_Selection_Approach_with_SVM/figures?lo=1&utm_source=google&utm_medium=organic