April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How it works...
The HOG descriptors from the input image are computed and then fed into a pretrained SVM classifier (obtained using cv2's HOGDescriptor_getDefaultPeopleDetector()), which was used to predict the presence or absence of a person in or from an image block at multiple scales with the detectMultiScale() function from OpenCV-Python.
The object(s) were detected multiple times at different scales, and they were fused together using non-maximum suppression (additionally, we may see some false positives too).
The non_max_suppression() function was invoked to avoid the detection of the same object at multiple times and scales.
The IoU was used by non-maximum suppression to calculate the amount of overlap of two different bounding boxes, ...
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