Face-Detection-with-OpenCV | Face Detection in Python using OpenCV | Computer Vision library

3rd dimension helps you iterate over predictions and

in the 4th dimension, there are actual results

class_lable = int(inference_results[0, 0, i,1]) --> gives one hot encoded class label for ith box

conf = inference_results[0, 0, i, 2] --> gives confidence of ith box prediction

TopLeftX,TopLeftY, BottomRightX, BottomRightY = inference_results[0, 0, i, 3:7] -->gives co-ordinates bounding boxes for resized small image

and 2nd dimension is used when the predictions are made in more than one stages, for example in YOLO the predictions are done at 3 different layers. you can iterate over these predictions using 2nd dimension like [:,i,:,:]