/MediCare-Prime

Prediction or detection of various medical ailments

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

MediCare-Prime

Prediction or detection of various medical ailments. Deployed locally using Flask 2.0.

Setup

Assuming you have Ananconda or Miniconda3 already working, create a tensorflow conda environment and install a few libraries into it, and then we're ready to go.

  • Install the current release of CPU-only TensorFlow, recommended for beginners:
conda create -n tf tensorflow
conda activate tf
  • Or, to install the current release of GPU TensorFlow on Linux or Windows:
conda create -n tf-gpu tensorflow-gpu
conda activate tf-gpu
  • Cd into your newly created environment (from command line or terminal)
cd C:\...\path-to-your-conda-environment\
  • Installing modules we will need Though your virtual env will have all required modules, here are some extra ones required to setup this project locally
pip install flask
pip install pillow

Running the code

  • Fork and clone the project.
git clone https://github.com/IIITKalyaniFOSC/MediCare-Prime
  • Cd into your cloned repo (folder with the same name as the repo on your system)
cd C:\...\path-to-your-cloned-repo\
  • After making sure your tf conda environment we just created above, is activated, run the app.py file
python app.py

Succesfull installation and running will give you a link you can visit locally. For any exceptions, kindly recheck the entire process and try again, or feel free to create an issue.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

✨ Contributors

License

GPL