Such a great communication happening in this video. The awareness of your audience at 8:15 is amazing. While it's true that "communication is what the listener does", to be a communicator, you must have empathy. Be proud of yourself for this.
What an awesome video! You really know how a student thinks. You answered all my questions - even the ones that I didn't realize I had! This was some excellent video format and pacing. I have liked and subscribed.
Awesome work Sir, You explain such complicated things in a way, it feels like cakewalk to understand. Thanks alot . Please make full python yolo implementation for video inputs.
Hi man. Finally, someone that understands how to make a great video. I just see 15'' and got what I was looking for. I also want to watch the rest because it is well explained. thanks
thank you sir .. you have explained the content in very good manner. . with coding from scratch and i like it ... have a very nice moring..and many many best wishes from me to you !
Thank you so much for creating this video! You really explained everything clearly. I was looking for an explanation about YOLO on other platforms but no one could explain this as clearly as you have. May I ask if I can translate your video into Chinese and share it on a Chinese video platform for all the people who are interested in learning YOLO but failed to find an excellent video like this one? Really appreciate your effort in making this video.
Thank you for the practical tutorials.🙏🙏🙏 I have the following questions: Can we use the saved weights from YOLOv7 instance segmentation for a classification problem? We have a binary classification problem with 500 images, one class having only 30 images and the rest belonging to the other class. Can we extract features using instance segmentation on the images with fewer samples and then use all the features for classification?
I just love this video. It is the best explanation of the real 'concept' of YOLO algorithm. Thank you very much for your great effort and sharing the insight!
At 6:48 - Bh seems correct (1.3), but why is Bw=2? If Bw is the proportion of the grid cell's width, it looks like it should be ~1.5. At 7:28 - Here the dimensions seem like they should be Bw=2, and Bh=1.7, but they are shown in the vector as Bw=3 and By=2. Am I missing something, or are these meant to just be rough estimates for the demo?
Hi sir i have a doubt. You explained that the grid is considered to have an object only if the center of the bounding box is in that grid.But how do we find the boundung box and center, then?
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My Deep Learning teacher couldn't explain this in 3 weeks the same way you did in 16 minutes, thank you very much.
so true
I think you didn't concentrate to your teacher lecture like you did in this video
@@Abraham33286yes..
Inki mind class me present rhti nhi hai.
Yaha akele dekh rha hai n.
To islie samjh gya 😂😂
Among all the yolov explaining videos this one makes the most sense! Thanks
The best explanation for YOLO! It's really helpful. Thank you.
I watched a hour long video earlier and understood nothing, and now in just 16 min, I understood everything. Thanks a lot!
Glad you enjoyed it.
Such a great communication happening in this video. The awareness of your audience at 8:15 is amazing. While it's true that "communication is what the listener does", to be a communicator, you must have empathy. Be proud of yourself for this.
This is the best explanation that I have not seen any where
Only once I watched and got knowledge on yolo
Thank you so much for this knowledge sharing
I used YOLO before I understood what it was, thank you for helping me understand how YOLO works
I really like your style of explanation. It's very clear and informative.
Glad it was helpful!
My God which kind of perfect explanation is this wow I don’t what to say bro just God bless you
Yes.. there is no details about network!, its only about box encoding
Perfect and Clear Introduction to YOLO
Glad it was helpful!
What an awesome video! You really know how a student thinks. You answered all my questions - even the ones that I didn't realize I had! This was some excellent video format and pacing. I have liked and subscribed.
Awesome work Sir, You explain such complicated things in a way, it feels like cakewalk to understand. Thanks alot . Please make full python yolo implementation for video inputs.
Such a perfect introduction to YOLO. Thanks!
please make a full project on this from code to deploying
You clear the concept in 16 min thanks bro..
thanks mate, went through a couple of videos and your's the one that explain it the best
You have explained things so well Ma Sha Allah, stay blessed and keep up the good work.
the best explanation honestly you are a master
Excellent introduction to YOLO. Looking forward for code deployment video
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Gone thru many udemy courses, no one explains like you! Thanks for the efforts!
I like this video very much. You explained the working of YOLO very simple , crystal and clear way. Thank you very much. Expect more.
I am new to ML but still i understand what you have said bout YOLO great work
excelente tutorial
The amount of good information and dogs in this video make me happy :)
Brilliant explanation, thank you so much!
man, this was such a good explanation to YOLO!
Thank you very much sir !!! Egarly waiting for next part
it my first time around and i have already got a good level on YOLO...thanks for explanation///
The best Explanation of Yolo thank you very much
Hi man. Finally, someone that understands how to make a great video. I just see 15'' and got what I was looking for. I also want to watch the rest because it is well explained. thanks
Best explanation till date
Sir your explanation is amazing in the field of data science
You are really awesome, explained it clearly
thank you sir .. you have explained the content in very good manner. . with coding from scratch and i like it ... have a very nice moring..and many many best wishes from me to you !
Every software engineers should subscribe this best channel omg you are just fire 🔥 wow
This was amazing! love it
Yeah! Very clear explanation.
Glad it was helpful!
well worth watching. thanks for this. i had to pause where you said to as well. then I got it.
Glad it was helpful!
Very nice, excellent description. Thank you!
thank you for the presentation, it is easier for me to understand compared to the paper
Great explanation of YOLO. And I need to say thank you for all your tutorials. I learnt a lot from you. Keep it up!
Thanks for sharing your knowledge
At 7:28, that looks more like 2 x the width of the grid cell. Why is it 3?
you made our life easier
Thank you so much for creating this video! You really explained everything clearly. I was looking for an explanation about YOLO on other platforms but no one could explain this as clearly as you have. May I ask if I can translate your video into Chinese and share it on a Chinese video platform for all the people who are interested in learning YOLO but failed to find an excellent video like this one? Really appreciate your effort in making this video.
Exceptional.
Waiting for more videos on yolo👏👏
yup next one will cover coding part
Nice work. You deserve more than one upvote. Sadly I can only give one.
Brilliant!!!!!!!!!
Helpful. Nice work. Thank you so much.
Glad it was helpful!
Glad I watched ur video ❤❤❤
Tks a lot sir, perfect explanation....
I like it bro clear and simple explanations
very nice explanation , btw either it will help to detect either brand logo is fake or not?
This video was fantastic. Thank you
This is a great video, but the real magic of YOLO is in the loss function. Would you do a video on that?
Great explaination of NMS.
Glad it was helpful!
Excellent explanation
great video.. salute !
Cool explanation, thanks!!
Excellent 👍
The best video!!
best explanation... you are doing a great job.
Great Explanation. Thank you
Great Sir
Thank you 😇
Thankyou Sir that was a very good and simple explanation of a complex algorithm :) Thankyousomuch sir
Amazing as always! Thank you for providing this information and helping unravel important topics
Great explainaition
Thank you alot this explanation is all i ever needed
Great video!
Excellent explanation, you teach these topics in such a way that even a layman can understand
احسنت الشرح والتفصيل شكرا لك
Good Video. However, I still have no idea how CNN can handle multiple anchors. Is there any paper that illustrates this technique?
Best explanation
Thank you for the practical tutorials.🙏🙏🙏
I have the following questions:
Can we use the saved weights from YOLOv7 instance segmentation for a classification problem?
We have a binary classification problem with 500 images, one class having only 30 images and the rest belonging to the other class. Can we extract features using instance segmentation on the images with fewer samples and then use all the features for classification?
Sir
The explanation was very clear
And can I get the ppt that you used in the explanation
Thanks in advance
I really loved this video! Thank you!
thank you so much for this, very easy to understand !
better than andrew ng's explanation thanks!
Nicely explain
Splendid!
Is it possible to use it for regression and not clasification?
I just love this video. It is the best explanation of the real 'concept' of YOLO algorithm. Thank you very much for your great effort and sharing the insight!
Thanks for the explanation. It's help me alot to understand yolo 👍
Nicely explained everything Thank you sir
At 6:48 - Bh seems correct (1.3), but why is Bw=2? If Bw is the proportion of the grid cell's width, it looks like it should be ~1.5.
At 7:28 - Here the dimensions seem like they should be Bw=2, and Bh=1.7, but they are shown in the vector as Bw=3 and By=2.
Am I missing something, or are these meant to just be rough estimates for the demo?
I agree - that really putted me off, lol
amazing content and good explanation
Really good explanation. I just have one doubt. How are bounding box measures calculated in yolo algo?
yes, it is the million dollar question :)
Amazing explanation as always..
Hi, This is a very effective video. please provide a full project video with source code like face recognition project.
Nice explanation!
Glad it was helpful!
Today's best face detection algorithm?yoko also used in face detection?
Totally Awesome
wonderful video very informative
Hi sir i have a doubt. You explained that the grid is considered to have an object only if the center of the bounding box is in that grid.But how do we find the boundung box and center, then?
Great explanation
Greatly explained. Does code video uploaded yet ?