def process_image(image):
# undistort
#Utils.display_image(image, "Undistorted road image")
undistorted_image = CalibrationUtils.undistort_img(image, mtx, dist)
#Utils.compare_before_after(image, undistorted_image, "Raw Image", "Undistorted Image")
# select region
#roi = Roi.select_roi(undistorted_image, roishape)
#Utils.compare_before_after(undistorted_image, roi, "Undistorted Image", "ROI")
# transform
transformed_roi = Roi.transform(undistorted_image, roishape.reshape(4, 2),
roi_dst_shape)
#Utils.compare_before_after(undistorted_image, transformed_roi, "Undistorted", "Wraped ROI")
# image threshold
threshold = Roi.threshold(transformed_roi)
#Utils.compare_before_after(transformed_roi, threshold, "Wraped ROI", "Threshold Image")
# detect lane
global left_fit_arr
global right_fit_arr
left_fit_arr, right_fit_arr = Lane.detect(threshold, left_fit_arr,
right_fit_arr)
left_fit, right_fit = np.mean(left_fit_arr, axis=0), np.mean(right_fit_arr,
axis=0)
#result = Lane.visualize_detection(threshold, left_fit, right_fit)
# calc curvature
left_curve, right_curve = Lane.curvature(left_fit, right_fit)
final_curve = (left_curve + right_curve) / 2
# draw lane
left_fit, right_fit = left_fit_arr[-1], right_fit_arr[-1]
with_lane = Utils.draw_lane(undistorted_image, threshold,
left_fit, right_fit, roi_dst_shape,
roishape.reshape(4, 2))
#Utils.compare_before_after(undistorted_image, with_lane)
with_lane = Utils.draw_curve(with_lane, final_curve)
#Utils.compare_before_after(undistorted_image, with_lane, "Undistorted Image", "Undist. Image with lane")
#Utils.display_image(with_lane, "Final Image")
return with_lane
