Malaria Detection App

This repository contains the source code for the Malaria Detection App, which is a web application for detecting malaria-infected cells in blood smear images using a YOLO-based object detection model. The app allows users to upload images, processes them using a machine learning model, and provides detection results.

Repository Structure

malaria_interface/
├── main.py              # Main FastAPI application
├── models/
│   └── best.pt          # YOLO model file
├── requirements.txt     # Python dependencies
├── static/              # Static assets (CSS, images)
│   ├── styles.css
│   └── images/
│       └── sample_image.jpg
├── templates/           # HTML templates for the web app
│   ├── index.html
│   └── model-info.html
└── README.md            # This README file

Model Information

The Malaria Detection App uses a YOLO (You Only Look Once) model, which is designed for real-time object detection. The model has been trained on a large dataset of blood smear images to accurately identify and classify malaria-infected cells such as trophozoites and WBCs.

How It Works

• The uploaded image is processed by the YOLO model to identify regions of interest.
• Detected regions are highlighted and presented with confidence scores.
• The app showcases the top 4 detected regions, if available.

For more detailed information, see the Model Info page of the app.

License

This project is licensed under the MIT License. See the LICENSE file for more details.