new_contents: # import the necessary packages
  from __future__ import print_function
  from imutils.object_detection import non_max_suppression
  from imutils import paths
  import numpy as np
  import argparse
  import imutils
  import cv2
  import time 
  
  # construct the argument parse and parse the arguments
  ap = argparse.ArgumentParser()
  ap.add_argument("-i", "--images", required=True, help="path to images directory")
  args = vars(ap.parse_args())
   
  # initialize the HOG descriptor/person detector
  hog = cv2.HOGDescriptor()
  hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
  
  # loop over the image paths
  for imagePath in paths.list_images(args["images"]):
  	startTime = time.time()
  	# load the image and resize it to (1) reduce detection time
  	# and (2) improve detection accuracy
  	image = cv2.imread(imagePath)
  	image = imutils.resize(image, width=min(500, image.shape[1]))
  	orig = image.copy()
   
  	# detect people in the image
  	(rects, weights) = hog.detectMultiScale(image, winStride=(3, 4), padding=(8, 8), scale=1.07)
   
  	# draw the original bounding boxes
  	for (x, y, w, h) in rects:
  		cv2.rectangle(orig, (x, y), (x + w, y + h), (0, 0, 255), 2)
   
  	# apply non-maxima suppression to the bounding boxes using a
  	# fairly large overlap threshold to try to maintain overlapping
  	# boxes that are still people
  	rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])
  	pick = non_max_suppression(rects, probs=None, overlapThresh=0.75)
   
  	# draw the final bounding boxes
  	for (xA, yA, xB, yB) in pick:
  		cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)
   
  	# show some information on the number of bounding boxes
  	filename = imagePath[imagePath.rfind("/") + 1:]
  	print("[INFO] {}: {} original boxes, {} after suppression".format(filename, len(rects), len(pick)))
  	text = "{} People".format(len(pick))
  	print ('The script took {0} second !'.format(time.time() - startTime))
  	
  	# Write some Text
  	font = cv2.FONT_HERSHEY_SIMPLEX
  	cv2.putText(image,text,(10,50), font, .5,(255,255,255),2)
   
  	# show the output images
  	#cv2.imshow("Before NMS", orig)
  	cv2.imshow("After NMS", image)
  	cv2.waitKey(0)
  
subject: Create detect.py