This project uses YOLO-NAS and EasyOCR to detect license plates and perform Optical Character Recognition (OCR) on them. The project includes both image and video processing capabilities, and has been deployed as a Streamlit web application. This is an update to a previous project, Optical-Character-Recognition-WebApp
- Real-time license plate detection using YOLO-NAS
- Optical Character Recognition (OCR) using EasyOCR
- Interactive user interface built with Streamlit
The dataset used for training and testing the YOLO-NAS model contains 484 annotated images of cars with license plates. The images were sourced from "Brave Images", "Google Images", and "https://flickr.com/". The annotations were made using RoboFlow.
This project builds upon an earlier version that used YOLO-v5 and InceptionResNetV2 . The major changes and updates in this version include:
- Transition from YOLO-v5 to YOLO-NAS for license plate detection
- Replacement of pytesseract with EasyOCR for more accurate text extraction
- Training the YOLO-NAS model for 15 epochs using Google Colab
- Deployment as a Streamlit web application
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'PPYoloELoss/loss_cls': 0.9181855
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'PPYoloELoss/loss_iou': 0.17447565
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'PPYoloELoss/loss_dfl': 0.9500977
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'PPYoloELoss/loss': 1.8294234
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'[email protected]': 0.02825159952044487
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'[email protected]': 1.0
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'[email protected]': 0.9623407125473022
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'[email protected]': 0.05495075136423111
- Clone the repository:
git clone https://github.com/JacobJ215/YOLO-NAS-OCR-WebApp/tree/main"
cd YOLO-NAS-OCR-WebApp
- Install the required dependencies:
pip install -r requirements.txt
- Run the Streamlit app:
streamlit run app.py
The web application provides two main modes: Run on Image: Upload an image containing a license plate, and the application will perform real-time detection and OCR, displaying the extracted text from the license plate.
Run on Video: Upload a video with license plates, and the application will perform real-time detection and OCR on the video frames, showing the extracted text and the frame rate.
Inspired by https://github.com/MuhammadMoinFaisal
The YOLO-NAS model used in this project is based on Super-Gradients Repository.
EasyOCR is an excellent OCR library developed by Jaided AI.