I am trying to implement HOG Descriptor with OpenCV to detect Pedestrians in a video. I am currently using the pre-made dataset by OpenCV hogcascade_pedestrians.xml. Unfortuntley the documentation on this part is very poor on the internet although the HOG Descriptor is very effective for human detection. I have been writing a code for pedestrians detection with Python, and I have stopped at the following code:
import cv2 import numpy as np import imutils VidCap = cv2.VideoCapture('pedestrians.mp4') HOGCascade = cv2.HOGDescriptor('hogcascade_pedestrians.xml') HOGCascade.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector()) while True: _ , image = VidCap.read() image = imutils.resize(image, width=700) gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) clahe = cv2.createCLAHE(clipLimit=15.0,tileGridSize=(8,8)) gray = clahe.apply(gray) winStride = (8,8) padding = (16,16) scale = 1.05 meanshift = -1 (rects, weights) = HOGCascade.detectMultiScale(gray, winStride=winStride, padding=padding, scale=scale, useMeanshiftGrouping=meanshift) for (x, y, w, h) in rects: cv2.rectangle(image, (x, y), (x+w, y+h), (0,200,255), 2) cv2.imshow('Image', image) if cv2.waitKey(5) == 27: break VidCap.release() cv2.destroyAllWindows() I presume that the code scripting would be something like codes written for Haar Cascades. But I have tried that and I got errors. Do anyone have any idea of how to implement the HOG Descriptor on OpenCV with Python.
I have read the following question, but I get nothing from the second answer.
My problem is that I can't find the way to write the code, as the documentation about this part is very poor.
Note: I am using OpenCV 3.1.0-dev with Python 2.7.11