new_contents: # Ported From: http://docs.opencv.org/3.1.0/d7/d8b/tutorial_py_face_detection.html
  import os
  import cv2
  
  cascade = cv2.CascadeClassifier('/home/matt/Projects/opencv-junk/classifier/run_two/cascade_xmls/cascade.xml')
  img_dir = '/mnt/jam-gui/smb-share:server=jamstation,share=gopro/2017-02-17/HERO4 Session 1/testing_frames'
  img_files = [i for i in os.listdir(img_dir) if os.path.splitext(i)[1] == '.jpg']
  
  ## Single Detection
  # img_file = 'GOPR0195_64000.jpg'
  ## Double Detection
  # img_file = 'GP010195_200.jpg'
  
  ## Test that the rec will detect a large positive image used in training the cascade.
  # img_dir = '/home/matt/Projects/opencv-sharrow-images/positives'
  ## LARGE TRAINING POSITIVE, WILL DETECT IN CURRENT CASCADE
  # img_file = '10.jpg'
  ## SMALL TRAINING POSITIVE, WON'T DETECT IN CURRENT CASCADE
  # img_file = 'GP010194_71100.jpg'
  
  for img_file in img_files:
      img = cv2.imread(os.path.join(img_dir, img_file))
      gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
      faces = cascade.detectMultiScale(gray, 1.3, 5)
  
      if len(faces) > 0:
          for (x, y, w, h) in faces:
              cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
              roi_gray = gray[y:y + h, x:x + w]
              roi_color = img[y:y + h, x:x + w]
  
          cv2.imshow('img', img)
          cv2.waitKey(0)
          cv2.destroyAllWindows()
  
subject: Add simple script to display positive detections