An open source solution for creating end-end web app for employing the power of deep learning in various clinical scenarios like implant detection, pneumonia detection, brain mri segmentation etc.

• Please give your PR for the test branch unless requested otherwise by the project maintainer
• Name your PR appropiately
• Ensure that you had already raised an issue for this PR and the project maintainer had approved and assigned you
• In the PR description, typically the following are expected:
  • Dataset Used:
  • Dataset Size:
  • Dataset Source:
  • Link to Colab Notebook: Please ensure you give access for view to anyone with link
  • Your Exploratory Data Analysis [Snapshots of the relevant ones and your inference from that]
  • Any Pre-Processing methods used. [Elaborate on them]
  • Your framework to train
  • Different methods used for training
  • Test/Train Split
  • Results: Please do not simply state test accuracy. Other perfomance metrics like F1 score,etc are expected
  • ** Draw a table to show the comparitive analysis of the performance of the different methods you used
  • Conclusion: Which method you think is best and why?
• A copy of the notebook used for your training is expected inside the notebooks/ directory.
• Please name the notebook as name_of_the_problem_your_github_username
• The model files are expected to be inside a models\name_of_your_problem\ directory
• If you are using TensorFlow 2.0, please give both the h5 as well as saved_model file
• Once your PR, gets approved uptil this, proceed with a follow up pr to integrate it inside the streamlit app. Refer this if you are unaware of how to use streamlit and host it
• For the streamlit app, it would be a good practice if you define the function for classification/prediction/regression inside a separate python file say your_problem_name.py and import it inside app.py ( Believe me this would save a lot of time otherwise wasted in debugging)
• For the second PR, you are expected to do the above changes and provide screenshots/a small clip of the working model of the app after integrating your model from the previous PR
• For the second PR, it should be one the test branch only, later the project maintainers will merge it with the master branch for a stable release
• For PRs, related to frontend please give it to the frontend branch
• Once accepted, give a follow up PR to the test branch to render your html,css files for a page using streamlit
• As stated above you are expected to give screenshots, descriptions and other details for the PR

Entire App on Heroku: https://auto-vaidya.herokuapp.com/ Frontend on Netlify: autovaidya.netlify.app