GSoC Week 8

 This week I worked on three things

- Refactoring the model selection code base to move from endpoint redirection to calling the actual methods by importing them

- Added test cases for model selection and fix issue with docker image

- Progressing on integrating the mammography breast cancer classification model


Refactoring the model selection code base

The model selection code base was implemented initially where it looks at the imaging information and redirects to the appropriate model endpoint. Something like this,






The problem faced with this way of implementing it, the base url was hardcoded and pointed to localhost. Mind that only if systems had set their localhost in their hosts file this would work and hence it was not system agnostic. This was causing my model selection test cases run in my local but not in the gitlab ci/cd pipeline. The other thing I read was in RESTful services this sort of redirection is generally not a good design since in RESTful each endpoint is considered stateless.

I refactored the code in multiple places to finally bring it to this,


Adding test cases and docker issues

After refactoring the model selection method I added the test case. A new issue occurred where the docker image miniconda3 used in the application, when run failed to install the requirements. On digging deeper I found out the docker image for miniconda3 had been modified and a newer version was released. The docker configuration in the codebase was not configured to stick to a particular version which meant it always pulled the latest available.

I fixed this by adding the docker image version in places required. It took time to fix this issue since I was new to the GitLab CI/CD platform.

Mammography breast cancer model integration

This week I worked on integrating the Mammography breast cancer model. This model will be integrated as a separate endpoint "classifier" differentiation from our "bounding-box" endpoint. This is because the mammography model will be a label classifier only. I took to kaggle's RSNA mammography breast cancer classification competition and looked at top performing solutions that I can integrate. Before that I had to code and setup the classifier endpoint. I and more or less done with that and now I'll have to develop the model and integrate it.






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