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 insideapp.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