GSOC Coding: Week 9

"Previously on LibreHealth GSOC 2020" [ Recap ]

The demo backend and frontend was connected and they are working. Added support for UNET for segmentation.

"UNET model served" [ Work ]

I have served the model and updated the frontend and backend accordingly. Everything on the DevOps side is working fine. But the segmentation output is coming out gibberish. I'am currently trying to figure out what is happening wrong.

"Next week" [ On LibreHealth ]

1) Complete the Segmentation integration.
2) Start looking into OHIF viewer.

Comments

Post a Comment

Popular posts from this blog

Final Submission

Image
  "Problem statement" Our app is geared towards improving the dataset in Radiology domain. We provide gui interface to visualise the inferences and modify the inference output. This helps in increasing and improving the dataset. To summarise ML domain in Andrej Karpathy's words "Data is king" and we are making the data even better. "Dataset"  The dataset that we worked on is NIH 14 Chest-xrays . The dataset has 112,000 images of over 30,000 distinct patients. But for Object detection it has annotation data for just 900 images. Which to train for medical purpose is just unusable. So we decided we will start with this dataset. "Web App flow"   [ Frontend ] Here is the flow of the app: Sign Up/ Sign In Get Image and start annotations: Things we can do: Select the Deep Learning model from which you want your annotations from Add more bounding boxes Remove bounding boxes Change the label of bounding boxes Add more labels to the label list Switc
Read more

GSOC community bonding week 3: Change of plans

Image
" Previously on LibreHealth GSOC 2020 "   [ Recap ] After forking the repository and writing the Backend, it looked like every thing was going fine the papers were awesome and everything was going well. " The new Changes"     [ Change of plans ] The new project in its essence in is very different but technology and implementation wise it is not that big of a change. See I thought we were building a webapp for people to diagnose diseases. Well, that is not at all true. We are building a webapp that annotates diseases with bounding boxes to assist doctors during annotation period. To be a helping hand. " The new Architecture"      [ Scale ] The architecture will remain largely the same. But we are taking into account in a real world scenario multiple people will be doing annotations job so, it would be waste if we did inference for each doctor when they for images. We can speed it up. Here is what we will do. " The frontend"      [ BBoxes ] The fr
Read more

GSOC community bonding week 2: The Paper...s

" Previously on LibreHealth GSOC 2020 "   [ Recap ] Kislay had celebrated his selection, told all about it to the friends and family, before he embarked on this journey, like a good traveller he has packed up, while in this context it was updating drivers, installing ubuntu and saying good bye to windows for some time. It was then he understood the quote " I get ideas about what's essential when I'm packing my suitcase" by Diane von Furstenberg. Now: " Django "   [ Gitlab ] I have created a new django app and setup a free smtp server from send in blue. The django app is capable of authenticating users by sending them email. I have committed all the changes to the forked repo. Since the plan is to use Reactjs frontend so I have used Django-rest-framework. For authentication I have used rest-auth. "awesome library" The steps to setup your own rest authentication service using Django: Install django rest auth and allauth: pip install django
Read more