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YOLO (You only look once) is a state of the art object detection algorithm that has become main method of detecting objects in the field of computer vision. Previously people used techniques such as sliding window object detection, R CNN, Fast R CNN and Faster R CNN. But after its invention in 2015, YOLO has become an industry standard for object detection due to its speed and accuracy. In this video we will understand the theory behind how exactly YOLO algorithm works. In next video we will write code to detect objects using YOLO framework.
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Thanks, it's an excellent explanation, just what I needed.
nice explanation
What a crisp and beautiful explanation without unnecessary info. Loved this tutorial.
The amount of good information and dogs in this video make me happy π
Good Video. However, I still have no idea how CNN can handle multiple anchors. Is there any paper that illustrates this technique?
Such a perfect introduction to YOLO. Thanks!
amazing content and good explanation
I do not understand rectangles from (time around 13). How the picture has been devided by yolo to receive these rectanngles?
The best video!!
thank you so much for this, very easy to understand !
This video was fantastic. Thank you
Amazing explanation as always..<3<3.
Can I give same image multiple times when train the model ?
There is a significant mistake about the confidence, it is not setting a threshold of IOU and then select the max probability. It is combining those two together and then select the max.
This is the core of YOLO, and you are misleading people, do your research!!!
very nice explanation , btw either it will help to detect either brand logo is fake or not?
you the best g
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Sir I have one doubt if we have images of tomato and green chilli in a same train folder and we simply giving the path and class names of apple and chilli in yaml file how the model correctly pics the apple with apple class in the shuffled dataset.
Very good video
Best explanation
Hey man, good stuff. I am not a coder so pardon my question but do you know if YOLO7 or 8 can be used for body measurement and not just object detection?
Thank you for the practical tutorials.πππ
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?
Thank you for the practical tutorials.πππ
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?
ΩWhat can I do for my imbalanced data in the medical image Where accuracy is very important and there is no excuse for mistakes.
I need pdf
Thank you alot this explanation is all i ever needed
How we determine use the grid 3×3 or 4×4 or etc?
how to overcome with two anchor boxes??