metadata

title: Diabetic Retinopathy Detection
emoji: 👁️
colorFrom: gray
colorTo: pink
sdk: gradio
sdk_version: 4.32.2
app_file: app.py
pinned: false
license: apache-2.0

Diabetic Retinopathy Detection with AI

Setup

Cloning the repo

git clone https://github.com/SDAIA-KAUST-AI/diabetic-retinopathy-detection.git

Gradio app environment

Install from pip requirements file:

conda create -y -n retinopathy_app python=3.10
conda activate retinopathy_app
pip install -r requirements.txt
python app.py

The app will download 280 MB of files from S3 and launch.

Install manually:

pip install pytorch --index-url  https://download.pytorch.org/whl/cpu
pip install gradio
pip install transformers

Training environment

Create conda environment from YAML:

mamba env create -n retinopathy_train -f environment.yml

Download the data from Kaggle or use kaggle API:

pip install kaggle
kaggle competitions download -c diabetic-retinopathy-detection
mkdir retinopathy_data/
unzip diabetic-retinopathy-detection.zip -d retinopathy_data/

Launch training:

conda activate retinopathy_train
python train.py

The trained model will be put into lightning_logs/.