PyTorch Image Segmentation Tutorial with U-NET: everything from scratch baby

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Semantic segmentation with U-NET implementation from scratch.

You'll learn about:
✔️How to implement U-Net
✔️Setting up training and everything else :)

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⌚️ Timestampo:
0:00 - Introduction
1:03 - Model from scratch
22:20 - Dataset from scratch
29:50 - Training from scratch
39:48 - Utils (almost) from scratch
50:10 - Evaluation and Ending

[AladdinPersson]

These from scratch videos & paper implementations take a lot of time for me to do, if you want to see me make more of these types of videos: please crush that *like* button and *subscribe* and I'll do it :)

Support the channel ❤️:


⌚️ Timestamps:
0:00​ - Introduction
1:03​ - Model from scratch
22:20​ - Dataset from scratch
29:50​ - Training from scratch
39:48​ - Utils (almost) from scratch
50:10​ - Evaluation and Ending

[foobar]

I'm writing this comment, because I want more of these types of videos.

[mohamedshatarah]

You are amazing! I have been struggling with this for 2 weeks and your video is so helpful. I can only imagine the amount of work you put into this. Thank you so much.

[josephmargaryan]

Hey bro, I know this video is from a long time ago. But thank you for teaching me and, most importantly, being an inspiration. I have now learned how to do the dataset, training loop, and Unet model, all from scratch in my head, just like you. I have also written a thesis on the subject as part of my bachelor's project at my university. Again, thank you, and I hope to learn more from you in the future.

[mathelecs]

You are the only one who does from scratch this good. Please keep up the good work man!

[aylinmousavian]

Many thanks of writing this specifically with PyTorch from scratch, I love your videos doing from scratch, you are awesome

[JosephCatrambone]

I was listening and following along like a Bob Ross show. Admittedly, I've already implemented a UNet, but the implementation here was much cleaner and nicer. Thanks for making this.

[thegt]

Thanks! Great work. Useful practical information

[mathematicalninja]

I literally read UNIX from scratch and I was like oh boy who is this legend 🤣🤣

[domingo]

Hi There, This content is gold. I am a huge supporter of writing things from scratch so many thanks for doing it. I do have one suggestion thou. Would you consider implementing also the loss function they used in the UNET paper?

They are using cross-entropy modified with the weighted map so they force the network to segment very thin borders between cells. I think this would also be very useful.

[nikolayandcards]

Great topic! Can't wait to watch it in my spare time.

[MuhammadHamza-or]

Man that was amazing! It was pure quality content. Keep it up!

[kwingwingchan]

I am new to machine learning, I would like to ask:
1) How could I train the model with COCO format dataset
2) How could I train the model with more than 1 label class
3) How to apply the trained model

[ayushjangid-yeariddmathem]

Thanks a Learnt a hell lot of new things from this video other than image segmentation.
Your lectures are pure gem!!!!

[RossMelbourne]

Thank you for the in-depth explanation of how to implement UNET. I would love to see you update GitHub to save the model and a separate display.py showing how to load the model and display the image segmentation predictions.

[arunavamaulik]

Thank you for these detailed tutorials, they are very informative
Keep them coming!

[stefanlazov]

Thank you for the nice video! I think this will help a lot of people that are trying to learn how to develop models and also people like me that have experience but need to expand their knowledge in PyTorch.

[thaimeuu]

not a single confusion in this video, thanks

[Annachrome]

learnt soo much from this thank you! love the proper structure instead of line by line commands in colab or sth

[ArpitAnand-ydtr]

I'm very thankful for the video and great implementation too but I wish you could go into details of why you do certain things and perhaps explain stuff a bit more.
Would be super helpful !