---
license: apache-2.0
tags:
- paddlepaddle
- ocr
- car-plate-detection
- ppocr
- computer-vision
- object-detection
datasets:
- andrewmvd/car-plate-detection
---

# Car License Plate Detection (PP-OCRv4 Mobile)

This repository contains a **PP-OCRv4 Mobile** detection model fine-tuned for **Car License Plate Detection**. The model is built using the [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) framework and is optimized for mobile and edge deployment.

## Model Details
- **Model Type**: Text Detection (optimized for license plates)
- **Algorithm**: DB (Differentiable Binarization)
- **Architecture**: PP-OCRv4 Mobile
- **Backbone**: PPLCNetV3
- **Training Epochs**: 10
- **Input Shape**: [3, 640, 640]

## Dataset
The model was trained on the [Car License Plate Detection](https://www.kaggle.com/datasets/andrewmvd/car-plate-detection) dataset from Kaggle, which consists of images with bounding box annotations for license plates.

## How to Use

### 1. Installation
To use this model, you need to install `paddlepaddle` and `paddleocr`:

```bash
pip install paddlepaddle paddleocr
```

### 2. Inference Code
You can use the following snippet to run detection on an image:

```python
from paddleocr import PaddleOCR
from pathlib import Path

# Path to the directory containing the downloaded model files
MODELS_DIR = Path("path/to/models")

# Initialize the OCR engine
pp_v4 = PaddleOCR(
    use_textline_orientation=True, 
    lang='en', 
    device='cpu', 
    text_detection_model_dir=str(MODELS_DIR / "ppocr_v4"),
    text_detection_model_name="PP-OCRv4_mobile_det"
)

img_path = 'car_image.jpg'
result = pp_v4.ocr(img_path, det=True, rec=False)

# Visualize results
for line in result:
    for box in line:
        print(f"Detected License Plate Box: {box}")
```

## Repository Structure
- `config.yml`: Training configuration.
- `inference.pdiparams`: Model weights for inference.
- `inference.yml`: Inference-specific configuration.
- `best_accuracy.pdparams`: Best model weights during training.
- `run_summary.json`: Summary of the training run.

## Credits
- **Original Dataset**: [Andrew MVD (Kaggle)](https://www.kaggle.com/andrewmvd)
- **Framework**: [PaddleOCR (Baidu)](https://github.com/PaddlePaddle/PaddleOCR)