Hi Umar, thanks for this amazing code explanation. Just one question, how is the prediction_iou computed in the Automatic Mask generation of SAM? I am asking because we only have the model's prediction and to compute iou you need ground truth labels. Thanks!
One question regarding the Vision Transfomrer, even if this is not the main topic: Why do they use the FIRST Token? Wouldn't usually the LAST token caputre all the information of the before seen ones?
Nice video! I think your understanding of the source code is really good. Could you please share your annotated code? It will be very helpful for my undergraduate graduation project.
As always the slides are freely available: github.com/hkproj/segment-anything-slides
I am a undergraduate student learning AI, your videos help me a lot. Thanks for the selfless work you are doing.
I am a undergraduate student learning ML, your videos help me a lot. Thanks for the selfless work you are doing.
Please keep making this kind of videos Umar! You're really a gifted teacher.
Thank you for your kind words, @pierret00
Please stay tuned, more videos coming soon
It's amazing how you can make this difficult subject much easier and more fun to learn! Thank you!
very helpful! Keep making such great content
23:39 -> loved that intuitive explanation!
Hey Umar, Great work on this video! Keep it up!
I was actually expecting me to watch this, but it was very informative
Thank you for the clear explanation. I would love to watch a video on SAM 2 as well.
Very helpful, thanks! Please keep uploading 🙂
Really great explanation !! Thanks !
Amazing Content. Clearly Explained !!!
Great explanation man!
Thank you! This is really helpful
Amazing explanation!
Hi Umar, thanks for this amazing code explanation. Just one question, how is the prediction_iou computed in the Automatic Mask generation of SAM? I am asking because we only have the model's prediction and to compute iou you need ground truth labels. Thanks!
The video is awesome.
awesome video man!
How does SAM calculate the predicted IoU for our output masks, if it doesn't have a ground truth for the given image?
Please do an explanation for SAM2!
incredible explanation! would you be interested in reviewing the SEEM (Segment Everything Everywhere All at Once) model?
Great job
thanks a lot. how can we access to codes that explained in video?
One question regarding the Vision Transfomrer, even if this is not the main topic:
Why do they use the FIRST Token? Wouldn't usually the LAST token caputre all the information of the before seen ones?
Valeu!
Is there any way we can mask same object with same colors ?
based on python roadmap, what topic should i focused to sir?
A video for coding SAM from scratch would be entertaining!
Nice video!
I think your understanding of the source code is really good.
Could you please share your annotated code? It will be very helpful for my undergraduate graduation project.
very nice!
Thank you!!!
This is very helpful