This is a machine learning project for predicting the presence of cataracts in eye images. The project is built using Flask web framework and is deployed as a web application.
The dataset used in this project is obtained from Kaggle. It contains a total of 1628 eye images, with 804 images showing cataracts and 824 images without cataracts.
The machine learning model used in this project is a Convolutional Neural Network (CNN) built using TensorFlow. The model is trained on the dataset to predict the presence of cataracts in eye images.
The Flask web application allows users to upload an eye image and receive a prediction of the presence of cataracts. The user interface is built using HTML, CSS, and JavaScript.
To run the project locally, follow these steps:
- Clone the repository to your local machine.
- Install the required packages using pip install -r requirements.txt.
- Navigate to the project directory and run python app.py to start the Flask server.
- Open your web browser and go to http://localhost:5000.
Contributions to this repository are welcome and encouraged. To contribute, please follow these steps:
- Fork the repository to your own GitHub account.
- Clone the forked repository to your local machine.
- Create a new branch for your changes.
- Make changes to the code as desired.
- Commit your changes and push them to your forked repository.
- Submit a pull request to the original repository.
This repository is licensed under the MIT license. See the LICENSE file for details.