Plastic Bottle Detection Model

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This repository contains a YOLOv8 model trained to detect plastic bottles in images. The model was trained on a custom dataset using the Ultralytics YOLOv8 framework. It is relatively small in size so it can be used on a Sony IMX500 image sensor.

Model Details

• Base Model: YOLOv8n
• Training Dataset: Plastic Bottle Image Dataset
• Training Duration: 50 epochs
• Best Performance Metrics:
  • Precision: 0.694 (69.4%)
  • Recall: 0.498 (49.8%)
  • mAP50: 0.496 (49.6%)
  • mAP50-95: 0.339 (33.9%)

Usage

1. Install requirements: bash pip install ultralytics

2. Download the model weights and use them with YOLOv8: from ultralytics import YOLO model = YOLO('best.pt') results = model.predict('your_image.jpg')

Project Structure

• \data.yaml: Dataset configuration file
• \test.pt: Best model weights (available in releases)
• \train.py: Training script