lane_temp

lanes = predict(lane_model,frame)
   
    lanes[lanes > 0.5] = 1.0
    lanes[lanes < 0.5] = 0
    
    lanes = cv2.resize(lanes, (1280,720))
    
    lanes *= 255
    lanes = cv2.normalize(lanes.astype('uint8'), None, 0, 255, cv2.NORM_MINMAX)
    lanes = cv2.cvtColor(lanes, cv2.COLOR_RGB2GRAY)
  
    (_, contours, _) = cv2.findContours(lanes, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    # biggest area
   
    for target in contours:
        if cv2.contourArea(target) < 2500:
            target = []
            #cv2.drawContours(frame, [target], -1, [0, 200, 0], -1) # debug
        else:
            x = target[:, :, 0].flatten()
            y = target[:, :, 1].flatten()
            poly = np.poly1d(np.polyfit(x, y, 5))
            for _x in range(min(x), max(x), 5): # too lazy for line/curve :)
                cv2.circle(dst, (_x, int(poly(_x))), 4, [255, 0, 0])

    # Display the resulting frame
    lanes = cv2.cvtColor(lanes, cv2.COLOR_GRAY2RGB)