ld_lane_detect.py

cnt = 0

for img in tqdm_notebook(col_images):
  
  # apply frame mask
  masked = cv2.bitwise_and(img[:,:,0], img[:,:,0], mask=stencil)
  
  # apply image thresholding
  ret, thresh = cv2.threshold(masked, 130, 145, cv2.THRESH_BINARY)

  # apply Hough Line Transformation
  lines = cv2.HoughLinesP(thresh, 1, np.pi/180, 30, maxLineGap=200)
  dmy = img.copy()
  
  # Plot detected lines
  try:
    for line in lines:
      x1, y1, x2, y2 = line[0]
      cv2.line(dmy, (x1, y1), (x2, y2), (255, 0, 0), 3)
  
    cv2.imwrite('detected/'+str(cnt)+'.png',dmy)
  
  except TypeError: 
    cv2.imwrite('detected/'+str(cnt)+'.png',img)

  cnt+= 1