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README.md

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+---
+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-OCRv5 Mobile)
+
+This repository contains a **PP-OCRv5 Mobile** detection model fine-tuned for **Car License Plate Detection**. The model is built using the [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) framework and provides improved accuracy and efficiency over v4.
+
+## Model Details
+- **Model Type**: Text Detection (optimized for license plates)
+- **Algorithm**: DB (Differentiable Binarization)
+- **Architecture**: PP-OCRv5 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_v5 = PaddleOCR(
+    use_textline_orientation=True, 
+    lang='en', 
+    device='cpu', 
+    text_detection_model_dir=str(MODELS_DIR / "ppocr_v5"),
+    text_detection_model_name="PP-OCRv5_mobile_det"
+)
+
+img_path = 'car_image.jpg'
+result = pp_v5.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)