Vireon - Malaria Cell Detection and Classification from Microscopic Images

This project uses a YOLOv10 model to detect and classify different types of malaria cells in microscope images.

Project Structure

• main.py – script for training the YOLO model on your custom dataset.
• data.yaml – configuration file with dataset paths and class list.
• vireon/weights/best.pt – trained YOLO model weights.
• vireon/ – folder containing results, plots, and sample images.

Requirements

• Python 3.8+
• ultralytics (YOLO)
• Data files in YOLO format

Install dependencies:

pip install ultralytics

Training

Make sure data.yaml points to the correct train and validation image folders. Then run:

python main.py

Configuration

Training parameters can be adjusted in main.py.

Results

The vireon/ folder contains:

• plots (F1_curve.png, PR_curve.png, etc.)
• confusion matrices (confusion_matrix.png)
• sample images with predictions

License

For personal, educational, and research use.