def addCurvatureStamp(leftFit, rightFit, image, origin, color=(255, 255, 255), fontScale=1.0):
"""
Evaluating lane curvature and adding it to a given image
:param leftFit: left curve polynomial parameters
:param rightFit: right curve polynomial parameters
:param image: image where data being added
:param origin: upper-left corner of the offset stamp
:param color: stamp color
:param fontScale: font scale
:return: void (adds text to passed image)
"""
imgH = image.shape[0]
yBottom = imgH-1
scaleY = 27 / imgH # meters per pixel
leftCurvature = aux.curvature(fitParams=leftFit, variable=yBottom, scale=scaleY)
rightCurvature = aux.curvature(fitParams=rightFit, variable=yBottom, scale=scaleY)
curvature = (leftCurvature + rightCurvature) / 2
aux.putText(img=image, text='Estimated Lane Curvature: {:.1f} m'.format(round(curvature / 100, 1) * 100),
origin=origin, color=color, scale=fontScale)
def lanefinding_pipeline(image, left_lane_line, right_lane_line):
#def find_lane_lines(image):
undist = camera_cal(image, mtx, dist)
thresholded = threshold(undist)
warped, M, M_inv = perspective_transform(thresholded, mtx, dist, src, dest)
#if not (left_lane_line.detected or right_lane_line.detected):
left_lane_line, right_lane_line, car_center, lane_center, y, out_img = sliding_window(
warped, left_lane_line, right_lane_line)
# print(left_fit)
# print(right_fit)
# update Line objects
# left_lane_line.detected = True
# right_lane_line.detected = True
# if abs(offset(car_center, lane_center)) > 0.3:
# left_lane_line, right_lane_line, car_center, lane_center = prior_frame_search(warped, 100, left_lane_line.current_fit, right_lane_line.current_fit)
# left_fit, right_fit, left_fitx, right_fitx, y, out_img = fit_poly(warped.shape, leftx, lefty, rightx, righty, out_img)
# sanity checks
# left_curve, right_curve = curvature(left_lane_line.fit_x, right_lane_line.fit_x, y)
# curverad = curvature(left_lane_line.fit_x, left_lane_line.fit_y)
#left_curve, right_curve = curvature(left_lane_line.fit_x, right_lane_line.fit_x, y)
left_curve = curvature(left_lane_line.fit_x, left_lane_line.fit_y)
right_curve = curvature(right_lane_line.fit_x, right_lane_line.fit_y)
# print(left_curve, right_curve)
# if left_curve < 1000 or right_curve < 1000:
# #leftx, lefty, rightx, righty, car_center, lane_center = prior_frame_search(warped, 100, left_lane_line.current_fit, right_lane_line.current_fit)
# left_fit, right_fit, left_fitx, right_fitx, y, out_img = fit_poly(warped.shape, leftx, lefty, rightx, righty, out_img)
# left_curve, right_curve = curvature(left_fit, right_fit, y)
# result = draw_lane_lines(image, undist, warped, left_lane_line.recent_xfitted, right_lane_line.recent_xfitted, y, M_inv, prev_car_center, prev_lane_center,
# left_lane_line.radius_of_curvature, right_lane_line.radius_of_curvature)
# else:
# # update Line objects
# left_lane_line.current_fit = left_fit
# right_lane_line.current_fit = right_fit
# left_lane_line.recent_xfitted = left_fitx
# right_lane_line.recent_xfitted = right_fitx
# left_lane_line.radius_of_curvature = left_curve
# right_lane_line.radius_of_curvature = right_curve
# prev_car_center = car_center
# prev_lane_center = lane_center
# leftx, lefty, rightx, righty, car_center, lane_center = base_lane_lines(warped)
# left_fit, right_fit, left_fitx, right_fitx, y = fit_poly(warped.shape, leftx, lefty, rightx, righty)
# left_curve, right_curve = curvature(left_fit, right_fit, y)
result = draw_lane_lines(image, undist, warped, left_lane_line.fit_x,
right_lane_line.fit_x, y, M_inv, car_center,
lane_center, left_curve, right_curve)
# draw_copy = np.copy(result)
# plt.imshow(draw_copy)
# plt.show()
#plt.imshow(warped, cmap = "gray")
# plt.imshow(result)
# plt.show()
return result