I have been working on a Covid CT dataset from Kaggle containing 20 CT scans of patients diagnosed with COVID-19 as well as segmentation of lungs and infections made by experts. My goal was to build a segmentation model using UNet. Due to fewer images (only 20 ;P), I had to perform data augmentation after which, I had 3200 images and masks in the training dataset. On passing these to the Dataloader and training the model, it took 1.5 hrs to run a single epoch and the GPU was barely being used.

After digging a bit, I found on Kaggle

Shambhavi Malik

Junior Undergraduate studying Biomed at IIT BHU.

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