| --- |
| 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) |
|
|
