GSOC community bonding week 1: The Project Overview

"Automatic labeling of radiology images" [ Project ]

I will be developing a stand alone web app. The web app will be able to segment, annotate and classify the uploaded X-ray through different deep learning algorithms such as GradCam and yoloV3. Now the architecture that I have proposed is a server client Restful architecture. The backend will be done in Django and Tensorflow serving( the machine learning framework of choice is Tensorflow2.1 ) and the frontend in Reactjs. The final goal is to make a beautiful web app that is scalable, responsive and beautiful. Here is a diagram of the architecture that we will be building:

Project 
[ Project architecture ]


"Community bonding week 1" [ Work ]


As first weeks at any organisation goes, I read up the forums and tried to get insights on the community. I also set up my development environment. I updated my visual studio code and cuda toolkit to 10.2. Enjoyed the fact that I got selected for GSOC 2020.

"What can be expected from this series of blogs" [ Road Map ]


The project as you can see has a lot of potential and is fairly complex. I will try my best to explain every step in a tutorial fashion through my forthcoming blogs. We will be building this webapp from scratch. I will be sharing illustrations, screenshots and code snippets to explain as much as I can. It will be fun if you stick around.


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