def updateImage():
global grayscaled_image
# GET SLIDER BAR VALUES
canny_thresh_low = cv2.getTrackbarPos(NAME_CANNY_LOWER, WINDOW_CANNY)
canny_thresh_high = cv2.getTrackbarPos(NAME_CANNY_UPPER, WINDOW_CANNY)
hough_thresh = cv2.getTrackbarPos(NAME_HOUGH_THRESHOLD, WINDOW_HOUGH)
horizontal_thresh = cv2.getTrackbarPos(NAME_HORIZON_SLIDER, WINDOW_CANNY)
# CANNY FILTER
canny_img = Filtering.CannyFilter(grayscaled_image, canny_thresh_low, canny_thresh_high)
# REMOVE ABOVE HORIZON
removed_horizon_img, horizontal_line = Operations.RemoveAboveHorizon(canny_img,
horizontal_thresh - horizon_offset_origin)
removed_horizon_img_w_lines = np.copy(cv2.cvtColor(removed_horizon_img, cv2.COLOR_GRAY2BGR))
cv2.line(removed_horizon_img_w_lines, (horizontal_line[0], horizontal_line[1]),
(horizontal_line[2], horizontal_line[3]), (0, 0, 255), 2)
cv2.imshow(WINDOW_CANNY, removed_horizon_img_w_lines)
# HOUGH FILTER
lines = Filtering.HoughFilter(removed_horizon_img, hough_thresh)
# all_lines_image = Draw.DrawHoughLinesOnImage(lines, rgb_image, (0, 0, 255))
# SEPARATE STREETS, GET THE LINES ASSOCIATED WITH YOUR LANE ONLY, BY ANGLE
street_lines = Operations.SeparateStreets(lines)
# lane_separated_image = Draw.DrawHoughLinesOnImage(street_lines, rgb_image, (0, 0, 255))
# CLUSTER INTO LEFT AND RIGHT LANE (HOPEFULLY)
cluster1, cluster2 = Operations.ClusterHoughPoints(street_lines)
cluster11, cluster12 = Operations.ClusterHoughPoints(cluster1)
# lane11 = Operations.GetLaneFromStdDeviation(cluster11)
# lane12 = Operations.GetLaneFromStdDeviation(cluster12)
cluster21, cluster22 = Operations.ClusterHoughPoints(cluster2)
# lane21 = Operations.GetLaneFromStdDeviation(cluster21)
# lane22 = Operations.GetLaneFromStdDeviation(cluster22)
# FIND AND DRAW LINES ASSOCIATED WITH STREETS
rgb_image = np.copy(cv2.cvtColor(grayscaled_image, cv2.COLOR_GRAY2BGR))
street_lines_image = Draw.DrawHoughLinesOnImage(cluster11, rgb_image, (255, 255, 0))
street_lines_image = Draw.DrawHoughLinesOnImage(cluster12, street_lines_image, (255, 0, 255))
street_lines_image = Draw.DrawHoughLinesOnImage(cluster21, street_lines_image, (255, 0, 0))
street_lines_image = Draw.DrawHoughLinesOnImage(cluster22, street_lines_image, (0, 0, 255))
# FIND AND DRAW LANES
global left_outer, left_inner, right_inner, right_outer
left_outer, left_inner, right_inner, right_outer = Operations. \
DetermineLanes(cluster1, cluster2, left_outer, left_inner, right_inner, right_outer)
lanes_image = np.copy(rgb_image)
# lanes_image = Draw.DrawLaneOnImage(left_lane, lanes_image, (255, 0, 0))
# lanes_image = Draw.DrawLaneOnImage(right_lane, lanes_image, (255, 0, 255))
lanes_image = Draw.DrawLaneOnImage(left_outer, lanes_image, (255, 0, 0))
lanes_image = Draw.DrawLaneOnImage(left_inner, lanes_image, (255, 255, 0))
lanes_image = Draw.DrawLaneOnImage(right_outer, lanes_image, (0, 255, 0))
lanes_image = Draw.DrawLaneOnImage(right_inner, lanes_image, (0, 0, 255))
# DRAW CENTER LINE IMAGE FOR FRAME
lanes_w_center_line = Draw.DrawCenterLine(lanes_image, np.shape(lanes_image)[1] / 2, (0, 255, 0))
# GET AND DRAW CENTER LINE FOR LANE X INTERCEPTS
center_point_x, x_left, x_right = Operations.GetCenterPointBetweenLanes(left_inner, right_inner,
lanes_w_center_line)
lanes_w_center_line = Draw.DrawCenterLine(lanes_w_center_line, center_point_x, (255, 255, 0))
# DISPLAY PERCENT FROM LEFT AND RIGHT LANE ON IMAGE
image_width = np.shape(lanes_w_center_line)[1]
image_height = np.shape(lanes_w_center_line)[0]
percent_from_left = (image_width / 2 - x_left) / (x_right - x_left)
percent_from_right = (image_width / 2 - x_right) / (x_right - x_left)
left_text = 'Left Lane = ' + str(int(percent_from_left * 100))
right_text = 'Right Lane = ' + str(int(percent_from_right * 100))
cv2.putText(lanes_w_center_line, left_text, (0, image_height - 3), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255),
thickness=2)
cv2.putText(lanes_w_center_line, right_text, (300, image_height - 3), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255),
thickness=2)
# SHOW HOUGH LINE IMAGES
images = np.array([street_lines_image, lanes_w_center_line])
smaller_images = Draw.ScaleAndStackImages(images, 0.5)
cv2.imshow(WINDOW_HOUGH, smaller_images)