ultralytics
YOLOv8
Object Detection
Computer Vision
License Plate Detection
Ultralytics
Real-time Detection
Instructions to use 66777yui/yolov8-license-plate-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use 66777yui/yolov8-license-plate-detection with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("66777yui/yolov8-license-plate-detection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
π YOLOv8 License Plate Detection Model
This repository contains a YOLOv8 object detection model trained to detect license plates in real-world images. The model was trained using the Ultralytics YOLOv8 framework and can be deployed for real-time applications such as surveillance, traffic monitoring, and vehicle identification.
π§ Model Details
- Architecture: YOLOv8n (Nano variant)
- Framework: Ultralytics YOLOv8
- Task: Object Detection
- Classes: 1 (
license_plate) - Input resolution: 640Γ640
- File:
best.pt
π§ How to Use
Install dependencies first:
pip install ultralytics
Example usage:
from ultralytics import YOLO
# Load model from HF
model = YOLO("koushik-ai/yolov8-license-plate-detection/best.pt")
# Run inference
results = model("your_image.jpg")
# Show results
results[0].show()
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