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https://github.com/nishant2018/malaria-detection
This is a web application built with Flask for detecting malaria in microscopic images of blood samples. It uses a deep learning model trained on TensorFlow/Keras to classify images as either infected (parasitized) or uninfected.
https://github.com/nishant2018/malaria-detection
cnn cnn-classification cnn-keras deep-learning image-classification image-processing supervised-learning
Last synced: 3 days ago
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This is a web application built with Flask for detecting malaria in microscopic images of blood samples. It uses a deep learning model trained on TensorFlow/Keras to classify images as either infected (parasitized) or uninfected.
- Host: GitHub
- URL: https://github.com/nishant2018/malaria-detection
- Owner: Nishant2018
- Created: 2024-04-16T13:27:18.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-06-10T10:44:54.000Z (5 months ago)
- Last Synced: 2024-06-10T12:31:35.793Z (5 months ago)
- Topics: cnn, cnn-classification, cnn-keras, deep-learning, image-classification, image-processing, supervised-learning
- Language: Jupyter Notebook
- Homepage: https://www.kaggle.com/code/endofnight17j03/detecting-malaria-cnn
- Size: 8.87 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Malaria Detection
This is a web application built with Flask for detecting malaria in microscopic images of blood samples. It uses a deep learning model trained on TensorFlow/Keras to classify images as either infected (parasitized) or uninfected.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
## Introduction
Malaria is a life-threatening disease caused by parasites transmitted to humans through the bites of infected mosquitoes. Early detection and treatment are crucial for effective management and prevention of complications. This project aims to provide a tool for automated malaria detection using machine learning.
## Features
- Upload images of blood samples for malaria detection.
- Obtain predictions on whether the sample is infected (parasitized) or uninfected.
- Simple and intuitive web interface.
- Backend powered by Flask, with a deep learning model trained on TensorFlow/Keras.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/malaria-detection.git
cd malaria-detection
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Flask application:
```bash
python app.py
```
4. Open your web browser and navigate to `http://localhost:5000` to access the application.
## Usage
1. Upload an image of a blood sample by clicking the "Choose Image" button.
2. Click the "Predict" button to obtain the malaria detection result.
3. The prediction result will be displayed below the "Predict" button.
## Contributing
Contributions are welcome! If you would like to contribute to this project, feel free to fork the repository and submit a pull request. Please ensure that any contributions adhere to the following guidelines:
- Make sure your code follows PEP 8 guidelines.
- Provide detailed descriptions of the changes made in your pull request.
- Ensure that your changes do not break existing functionality.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
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