Image Segmentation with UNET (Intro to Computer Vision Part 2)

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Video Description: The second part of a six-part PyTorch tutorial series. Learn how to segment images with UNET! We will build UNET from scratch and then learn how to train on a custom dataset using PyTorch Lightning. All details for the project and links to the public colab notebooks can be found at the link below.

Series Summary: By the end of the series, a PyTorch computer vision novice should have the tools to train any of the models we cover (object counting with CNNs, image segmentation with UNET, Faster RCNN, Mask RCNN) on a custom dataset (Part 1 - Part 4) and also quickly apply a trained Mask RCNN model to their own images and videos (Part 5).

Python Packages Used: pytorch, torchvision, pytorch-lightning, open cv (cv2), torchmetrics

Pro Tip: Put the video in 1.5 speed if it's feeling too long! :)

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Debugging with Pytorch Lightning link is not working in the collab

haiyang

Great Lectures. Can you make a line by line code walkthrough for 1st lecture because many logics are skipped / helpful for pytorch beginners like me.

raj-nqke

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