def process_image(image, debug=False):
undistorted = undistort_image(image)
threshold = combined_threshold(undistorted)
bird_eye = original2bird_eye(threshold)
lane_line_params = calc_lane_lines(bird_eye)
result = draw_lane_lines(undistorted, lane_line_params)
if debug:
f, axarr = plt.subplots(3, 2, figsize=(15, 15))
axarr[0, 0].imshow(undistorted)
axarr[0, 0].set_title('Undistorted Image')
axarr[0, 1].imshow(threshold, cmap='gray')
axarr[0, 1].set_title('Threshold Image')
axarr[1, 0].imshow(original2bird_eye(undistorted))
axarr[1, 0].set_title('Bird Eye Image')
axarr[1, 1].imshow(bird_eye, cmap='gray')
axarr[1, 1].set_title('Bird Eye threshold Image')
axarr[2, 0].imshow(lane_line_params['out_img'])
axarr[2, 0].plot(lane_line_params['left_fit_x'],
lane_line_params['plot_y'],
color='yellow')
axarr[2, 0].plot(lane_line_params['right_fit_x'],
lane_line_params['plot_y'],
color='yellow')
axarr[2, 0].set_title('Curvature Image')
axarr[2, 1].imshow(result)
axarr[2, 1].set_title('Result Image')
plt.show()
return result
def process_video_frame(image):
global prev_fit
undistorted = undistort_image(image)
threshold = combined_threshold(undistorted)
bird_eye = original2bird_eye(threshold)
lane_line_params = calc_lane_lines(bird_eye)
result = draw_lane_lines(undistorted, lane_line_params)
return result
def process_image(image):
undistorted = undistort_image(image)
threshold = combined_threshold(undistorted)
bird_eye = original2bird_eye(threshold)
lane_line_params = calc_lane_lines(bird_eye)
result = draw_lane_lines(undistorted, lane_line_params)
f, axarr = plt.subplots(2, 2, figsize=(30, 15))
axarr[0, 0].imshow(undistorted)
axarr[0, 0].set_title('Undistorted')
axarr[0, 1].imshow(threshold, cmap='gray')
axarr[0, 1].set_title('Threshold')
axarr[1, 0].imshow(lane_line_params['out_img'])
axarr[1, 0].plot(lane_line_params['left_fit_x'], lane_line_params['plot_y'], color='yellow')
axarr[1, 0].plot(lane_line_params['right_fit_x'], lane_line_params['plot_y'], color='yellow')
axarr[1, 0].set_title('Calculated')
axarr[1, 1].imshow(result)
axarr[1, 1].set_title('Result')
plt.show()
return result
def process_video_frame(image):
"""process the frame and return the processed result"""
global prev_fit
undistorted = undistort_image(image)
threshold = combined_threshold(undistorted)
bird_eye = original2bird_eye(threshold)
lane_line_params = calc_lane_lines(bird_eye, prev_fit=prev_fit)
# Compute confidence by recent two curvature and decide how to search in next frame
curve = lane_line_params['curvature']
last_curve = curve_queue[0] if len(curve_queue) else curve
confident = abs(curve - last_curve) / curve < 0.2
if not confident:
prev_fit = False
else:
prev_fit = lane_line_params['left_fit'], lane_line_params['right_fit']
# maintain the latest curves and output an average to draw
curve_queue.appendleft(curve)
lane_line_params['curvature'] = sum(curve_queue) / len(curve_queue)
result = draw_lane_lines(undistorted, lane_line_params, prev_fit=prev_fit)
return result
# Calculate the new radii of curvature
left_curvature = cal_curvature(left_fit[0], left_fit[1], y_to_eval)
return left_curvature
if __name__ == '__main__':
images = glob.glob('./test_images/*.jpg')
# show result on test images
for idx, filename in enumerate(images):
image = cv2.imread(filename)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
undistorted = undistort_image(image)
threshold = combined_threshold(undistorted)
bird_eye = original2bird_eye(threshold)
lane_line_params = calc_lane_lines(bird_eye)
f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 10))
ax1.imshow(image)
ax1.set_title(os.path.basename(filename) + ' Original', fontsize=12)
ax2.imshow(lane_line_params['out_img'])
ax2.set_title(os.path.basename(filename) + ' Calculated', fontsize=12)
ax2.plot(lane_line_params['left_fit_x'],
lane_line_params['plot_y'],
color='yellow')
ax2.plot(lane_line_params['right_fit_x'],
lane_line_params['plot_y'],
color='yellow')
plt.show()