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How many objects are detectable in Yolo? #3896
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https://github.com/AlexeyAB/darknet#how-to-improve-object-detection
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Ok, thank you very much! |
I assume you're asking about YOLOv3. Then this diagram might be helpful.
In short, predictions are made at 3 scales, 1/8, 1/16 and 1/32 of the original dimension. For input size of 416x416, it'll be 52x52, 26x26, 13x13. For every grid in each scale, 3 anchor boxes are predicted. There are 9 anchor boxes given, because there are 3 for every scale. So the total no. of prediction is (52x52 + 26x26 + 13x13)*3 = 10647. AlexeyAB's formula will give you the same number. |
thank you very much. that helped a lot |
@gnefihs have the chart about yolov4 like this? |
Hello,
I read a lot of comments about the process of detecting objects with Yolo, but I still have some questions concerning the detection process:
Yolov3 divides the input image in 13x13 parts and on each part, yolo checks for anchor-points, right?
So when you have 9 anchors in your .cfg-file, you can detext up to 13x13x9 objects?
Thanks for your help!
Knust
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