| --- |
| license: mit |
| datasets: |
| - 0xnu/uk-licence-plate |
| tags: |
| - uk |
| - united-kingdom |
| - transport |
| - transportation |
| - computer-vision |
| - object-detection |
| - license-plate-recognition |
| - ocr |
| language: |
| - en |
| --- |
| |
| ## UKLPR: United Kingdom License Plate Recognition |
|
|
| UKLPR is a computer-vision model architecture purpose-built for detecting, reading, and recognizing United Kingdom license plates. It is optimized for speed and accuracy across diverse UK plate formats. |
|
|
| ### Model Performance |
|
|
| - **Detection Rate**: 100.0% |
| - **Text Extraction Rate**: 100.0% |
| - **Processing Speed**: 8.1 FPS |
| - **Model Size**: YOLOv8 Nano (~12.3MB) |
|
|
| ### Supported Languages |
|
|
| - English (en) |
|
|
| ### Quick Start |
|
|
| #### Installation |
|
|
| ```python |
| pip install ultralytics easyocr opencv-python pillow torch torchvision huggingface_hub |
| ``` |
|
|
| #### Usage |
|
|
| ```python |
| import cv2 |
| import numpy as np |
| from ultralytics import YOLO |
| import easyocr |
| from PIL import Image |
| from huggingface_hub import hf_hub_download |
| import warnings |
| |
| # Suppress warnings |
| warnings.filterwarnings('ignore') |
| |
| # Download models from HuggingFace |
| print("Downloading model from HuggingFace...") |
| model_path = hf_hub_download(repo_id="0xnu/uk-license-plate-recognition", filename="model.onnx") |
| config_path = hf_hub_download(repo_id="0xnu/uk-license-plate-recognition", filename="config.json") |
| |
| # Load models with explicit task specification |
| yolo_model = YOLO(model_path, task='detect') |
| ocr_reader = easyocr.Reader(['en'], gpu=False, verbose=False) |
| |
| # Process image |
| def recognize_license_plate(image_path): |
| # Load image |
| image = cv2.imread(image_path) |
| image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
| |
| # Detect license plates |
| results = yolo_model(image_rgb, conf=0.5, verbose=False) |
| |
| plates = [] |
| for result in results: |
| boxes = result.boxes |
| if boxes is not None: |
| for box in boxes: |
| # Get coordinates |
| x1, y1, x2, y2 = box.xyxy[0].cpu().numpy() |
| |
| # Crop plate |
| plate_crop = image_rgb[int(y1):int(y2), int(x1):int(x2)] |
| |
| # Extract text |
| ocr_results = ocr_reader.readtext(plate_crop) |
| if ocr_results: |
| text = ocr_results[0][1] |
| confidence = float(ocr_results[0][2]) # Convert to native Python float |
| plates.append({'text': text, 'confidence': confidence}) |
| |
| return plates |
| |
| # Usage Example |
| results = recognize_license_plate('sample_car_with_license.jpeg') |
| print(results) |
| ``` |
|
|
| ### Model Architecture |
|
|
| #### Detection Model (YOLOv8n) |
| - **Architecture**: YOLOv8 Nano |
| - **Parameters**: ~3M |
| - **Input Size**: 640x640 pixels |
| - **Output**: Bounding boxes for license plates |
|
|
| #### OCR Model (EasyOCR) |
| - **Engine**: Deep learning-based OCR |
| - **Languages**: English |
| - **Character Set**: Alphanumeric + common symbols |
|
|
| ### Training Details |
|
|
| - **Dataset**: UK License Plate Dataset ([0xnu/uk-licence-plate](https://huggingface.co/datasets/0xnu/uk-licence-plate)) |
| - **Training Epochs**: 10 |
| - **Batch Size**: 16 |
| - **Image Size**: 640x640 |
| - **Optimizer**: AdamW |
| - **Framework**: Ultralytics YOLOv8 |
|
|
| ### Use Cases |
|
|
| - Traffic monitoring systems |
| - Automated parking management |
| - Law enforcement applications |
| - Toll collection systems |
| - Vehicle access control |
|
|
| ### Limitations |
|
|
| - Optimized for United Kingdom license plate formats |
| - Performance may vary with extreme weather conditions |
| - Requires good image quality for optimal text recognition |
| - Real-time performance depends on hardware capabilities |
|
|
| ### License |
|
|
| This project is licensed under the [Modified MIT License](./LICENSE). |
|
|
| ### Citation |
|
|
| If you use this model in your research or product, please cite: |
|
|
| ```bibtex |
| @misc{uklpr2025, |
| title={UKLPR: United Kingdom License Plate Recognition}, |
| author={Finbarrs Oketunji}, |
| year={2025}, |
| publisher={Hugging Face}, |
| howpublished={\url{https://huggingface.co/0xnu/uk-license-plate-recognition}} |
| } |
| ``` |
|
|
| ### Copyright |
|
|
| Copyright (C) 2025 Finbarrs Oketunji. All Rights Reserved. |
