Instructions to use makhresearch/persian-license-plate-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use makhresearch/persian-license-plate-detector with ultralytics:
from ultralytics import YOLOvv5 model = YOLOvv5.from_pretrained("makhresearch/persian-license-plate-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
๐ฎ๐ท Persian License Plate Detector - YOLOv5 (yolo12x)
This model (yolo12x) is trained to detect Iranian vehicle license plates in images. It uses the YOLOv5 architecture and is optimized for real-world Persian plates under various conditions.
๐ง Model Details
- Architecture: YOLOv5
- Training Data: 30,000+ images of Iranian cars with annotated license plates
- Classes: 1 (
license_plate) - File:
best.pt
๐ฆ Files in This Repository
best.ptโ YOLOv5 model weights (PyTorch format)app.pyโ Gradio app to test the model in-browserPersian_License_Plate_Images/โ Example images for demonstration (upload some!)README.mdโ This model card
๐ผ๏ธ Example
from ultralytics import YOLO
model = YOLO("best.pt")
results = model("car.jpg")
results[0].show()
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