yamciayamcia's profile - activity

have following code and I have some questions about it: 1. What is detection window size for HOG detector and how does it change within program run? 2. What classificators are being used in OpenCV HOG detector? 3. Confusion matrix for HOG in OpenCV?

# detect people in the image and start counting time
start = datetime.datetime.now()
(rects, weights) = hog.detectMultiScale(image, winStride=winStride,
    padding=padding, scale=scale, useMeanshiftGrouping=meanShift)
#end time counting
print("[INFO] detection took: {}s".format(
    (datetime.datetime.now() - start).total_seconds()))

# draw the original bounding boxes
for (x, y, w, h) in rects:
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

# show the output image
cv2.imshow("Detections", image)
cv2.waitKey(0)
print ("dws: ", dws)

Thanks. It's almost clear now, but how counting occurrences of gradients leads to telling program that it's a person?

I got you, but to use detector, we also need classificator, right? So I'm asking, when I run hog.detectmultiscale, which

Thanks. I managed to find out for the first question, but two still remaining and I couldn't find any info about it...

Three questions about HOG detector have following code and I have some questions about it: 1. What is detection window s