In YOLO grid size is 17x17, the number of anchor boxes are 5 and able to detect 80 classes .What will be the size of the output layer.*1 point2427632946476852250
Question
In YOLO grid size is 17x17, the number of anchor boxes are 5 and able to detect 80 classes .What will be the size of the output layer.*1 point2427632946476852250
Solution
The output of YOLO (You Only Look Once) is a convolutional feature map that contains bounding box attributes. These attributes are then used to predict classes and bounding box coordinates.
The size of the output layer can be calculated as follows:
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Each grid cell predicts a certain number of bounding boxes. In this case, it's 5 (the number of anchor boxes).
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Each bounding box is described by 5 attributes (x, y, w, h, and confidence score).
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Each grid cell also predicts the class probabilities for each class. In this case, it's 80 classes.
So, for each grid cell, the number of attributes predicted is (5 bounding boxes x 5 attributes) + 80 class probabilities = 25 + 80 = 105.
Since the grid size is 17x17, the total number of predictions is 17 x 17 x 105 = 30345.
So, the size of the output layer will be 30345.
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