C4W3L09 YOLO Algorithm

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Same concept is used in YOLO v3, but instead of softmax activation for all classes, logistic regression is applied to each class (meaning there can be an object belonging to two classes)

andresfernandoaranda

i have read multiple blog posts on yolo, along with the original paper, but this video provides the intuition at a different level. amazing !

ujjalkrdutta

YOLO algorithm *CORRECTION*

At time 5:00, for the slide titled "Outputting the non-max suppressed output" the text should read "For each grid cell" instead of "For each grid call".

manuel

I am not clear how will it's work at Inference time? How can I get model output BB into original image format? Kindly give me the mathematics how to compute it?

sahil-

So, at 1:49 we give the pc value to the 2nd anchor box because it had more IoU and not to the 1st. So to generalize, check if there's something worth in the grid; if there is, assign the associated pc value to anchor box with the highest IoU.

vaibhavsingh

This algorithm simplified the bounding box regression by having a 3x3 (or some other) grid output, right? What I didn't understand is how anchor boxes are used in this algorithm...

rpcruz

Is this YOLO or YOLO 9000? According to the YOLO paper, I think the y should be 3x3x((2x5)+3), so y is 3x3x13. Is this right?

Denmark_

Thank you very much for all your YOLO videos. They are just great :)

PoRouS

@0:56 I think something is wrong. According to YOLO paper we have [S, S, (B * 5 + C)] which means each cell has C classes but here you said that each anchor box has C classes or [S, S, B*(5+C)].

mehranmehralian

@5:28 How come bounding boxes size are different ? How is the bounding box size changing ?

maheshmedam

Is yolo is a deep learning algorithm???

waqasmalik

Johnson Deborah Miller Jason Garcia Dorothy

LinoMathiasen-mw

Is this a graduate or undergraduate level course?

GaganDaroach

Is Non-Max suppression used during training?

manikantabandla

at 6:01 how this lady's bounding box is there is separate CNN for each grid cell....can somebody explain ?

adityarajora

Just wanted to let you know that this video has been ripped and re-uploaded:

munzutai

OK, so how many objects can one cell of YOLOv1 predict? The article says 'we only predict one set of class probabilities per grid cell regardless of the number of boxes'? It seems that the article skirts around the fact that the model can only predict at most 1 object/cell, but the wording above does not exclude, for example, the case when all B objects belong to the same class. So how many?

alexter-sarkisov

If we divide the image into 3*3=9 small boxes, why do we still need bx, by, bh, bw these box coordinate variables?

lorryzou

I read some documents and I know yolo use HSV, can you explain for me why?

ngantrieuninh

Let's say I have an object in 3 of the grid cells. Then, the outputs of all the 3 of the grid cells should be identical, with the same values of bx, by, bh, bw. Am I correct?

lakshmanvengadesan

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