Diabetic Retinopathy Prediction 🚀

Overview

The objective of this project is to develop a computer vision application capable of detecting signs of diabetes and diabetic retinopathy from retinal images. By leveraging advanced image processing techniques and machine learning algorithms, the system aims to assist healthcare professionals in early diagnosis and monitoring of diabetic patients.

Example

Workflows

1. Update config.yaml
2. Update secrets.yaml [Optional]
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline

Dataset

Here, I have used two datasets.

1. For diabetes prediction this
2. For diabetic retinopathy detection this

You can use your own dataset. Just replace the URL of the dataset in config/config.yaml/data_ingestion/ml_data_source_url and config/config.yaml/data_ingestion/source_URL

Steps to run

STEP 00 : Clone the repository

https://github.com/utpalpaul108/Diabetic-Retinopathy-Prediction

STEP 01 : Create a virtial environment after opening the repository

Using Anaconda Virtual Environments

conda create -n venv python=3.10 -y
conda activate venv

Or for Linux operating system, you can use that

python3.10 -m venv venv
source venv/bin/activate

STEP 02 : Install the requirements

pip install -r requirements.txt

Finally, run the following command to run your application:

python app.py

STEP 03 : Run the application

Now,open up your local host with a port like that on your web browser.

http://localhost:8080

STEP 04 : Train the model

Before predicting, you have to train the models with your own dataset.

http://localhost:8080/train-diabetes-prediction-model
http://localhost:8080/train-diabetic-retinopathy-prediction-model

After completing the training, you can now predict the signs of diabetes and diabetic retinopathy from retinal images.

http://localhost:8080