README.md

---
license: mit
tags:
- license-plate-detection/recognition
- object-detection
- computer-vision
- onnx
datasets:
- lpr-bygdn/lpr-fuskc
metrics:
- mean average precision (mAP50 and mAP50-95)
- recall (R)
- precision (P)
---

# License Plate Detection Model

## Model Description

This model is designed to detect license plates in images. It was trained using the YOLO (You Only Look Once) object detection algorithm and exported to the ONNX format for portability.

## Intended Uses & Limitations

**Intended Uses:**

- Automatic license plate recognition systems
- Traffic monitoring and analysis
- Parking management

**Limitations:**

- The model may not perform well on blurry or low-resolution images.
- It may struggle with license plates that are obscured or damaged.
- It may not be able to detect license plates from all countries or regions.

## Training Data

The model was trained on a dataset of images containing license plates. (Provide details about your dataset if possible)

## Evaluation Results

(Include relevant evaluation metrics, such as precision, recall, etc.)

## Ethical Considerations

This model should be used responsibly and ethically. It is important to consider the potential impacts of its use and to avoid any biases or discrimination.