human_pic.py

from imutils.object_detection import non_max_suppression
from imutils import paths
import numpy as np
import imutils
import cv2

hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())

for imagePath in paths.list_images('./human_detection'):
	image = cv2.imread(imagePath)
	image = imutils.resize(image, width=min(400, image.shape[1]))
	orig = image.copy()

	(rects, weights) = hog.detectMultiScale(image, winStride=(4, 4),
		padding=(8, 8), scale=1.05)
    
    #Before__
	for (x, y, w, h) in rects:
		cv2.rectangle(orig, (x, y), (x + w, y + h), (0, 0, 255), 2)

	rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])
	pick = non_max_suppression(rects, probs=None, overlapThresh=0.65)

    #After__
	for (xA, yA, xB, yB) in pick:
		cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)
		cv2.imwrite('result.jpg', image)

	filename = imagePath[imagePath.rfind("/") + 1:]
	print("[INFO] {}: {} original boxes, {} after suppression".format(
		filename, len(rects), len(pick)))

	cv2.imshow("Before NMS", orig)
	cv2.imshow("After NMS", image)
	cv2.waitKey(0)