def process_frame(self, img_org, flag=False):
img_undist = undistort(img_org, mtx, dist)
img_undist_gray = cv2.cvtColor(img_undist, cv2.COLOR_RGB2GRAY)
img_ylane_th = lab_select(img_undist, thresh=(150, 200))
img_wlane_th = luv_select(img_undist, thresh=(225, 255))
img_grad_abx = abs_sobel_th(img_undist, orient='x', ksize=ks, thresh=th)
img_grad_mag = mag_sobel_th(img_undist, ks, th)
img_grad_dir = dir_sobel_th(img_undist, ksize=7, thresh=(1.0, 1.2))
img_combined = np.zeros_like(img_undist_gray)
# img_combined[ (img_wlane_th == 1) | (img_ylane_th == 1) ] = 1
img_combined[(img_wlane_th == 1) | (img_ylane_th == 1) |
(img_grad_abx == 1) | (img_grad_mag == 1)] = 1
# (img_grad_abx == 1) | (img_grad_mag == 1) | (img_grad_dir == 1) ] = 1
img_pers, persM = corners_unwarp(img_combined, nx, ny, mtx, dist, src, dst)
img_combined_pers = np.copy(img_pers)
roi_combined = mask_roi(img_combined_pers)
win_c, lc_pts, rc_pts = find_window_centroids(roi_combined, w_win, h_win,
margin)
left_fitx, right_fitx, ploty_win = polyfit_window(h_img, lc_pts, rc_pts,
h_win)
avg_curve_r = measure_curve_r(ploty_img, lc_pts, rc_pts, ploty_win, h_img)
offset_m = get_offset(lc_pts, rc_pts, w_img)
dist_bw_lines = np.average(left_fitx) - np.average(right_fitx)
self.dist_bw_lines.append(dist_bw_lines)
avg_dist_bw_lines = np.average(self.dist_bw_lines[-60:])
dist_diff_squa = (avg_dist_bw_lines - dist_bw_lines)**2
dist_diff_squa_stack.append(dist_diff_squa)
dist_mse = np.average(dist_diff_squa_stack) # Mean Square Error
print("dist_bw_lines", dist_bw_lines)
print("dist_mse", dist_mse)
if dist_mse <= 750:
self.l_curr_fitx.append([left_fitx])
self.r_curr_fitx.append([right_fitx])
l_avg_fitx = np.average(self.l_curr_fitx[-5:], axis=0)
r_avg_fitx = np.average(self.r_curr_fitx[-5:], axis=0)
img_fin = draw_lane(roi_combined, l_avg_fitx, r_avg_fitx, ploty_img,
img_undist, Minv)
cv2.putText(img_fin, ("Curve Radius: " + str(avg_curve_r) + "m"),
(256, 50), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(img_fin, ("Center Offset: " + str(offset_m) + "m"), (896, 50),
font, 1, (255, 255, 255), 2, cv2.LINE_AA)
"""
cv2.imwrite("../output_images/output_img_undist.jpg", img_undist)
cv2.imwrite("../output_images/output_img_wlane_th.jpg", img_wlane_th*255)
cv2.imwrite("../output_images/output_img_ylane_th.jpg", img_ylane_th*255)
cv2.imwrite("../output_images/output_img_grad_abx.jpg", img_grad_abx*255)
cv2.imwrite("../output_images/output_img_grad_mag.jpg", img_grad_mag*255)
cv2.imwrite("../output_images/output_img_grad_dir.jpg", img_grad_dir*255)
cv2.imwrite("../output_images/output_img_combined.jpg", img_combined*255)
cv2.imwrite("../output_images/output_img_combined_pers.jpg", img_combined_pers*255)
cv2.imwrite("../output_images/output_img_fin.jpg", img_fin)
"""
if flag is False:
return img_fin
else:
show_window_centroids(img_combined, w_win, h_win, win_c)
return img_fin, roi_grad_abx, roi_grad_mag, roi_grad_dir, roi_hls_ch_s, img_combined, show_window_centroids, roi_wline_th, roi_yline_th
img_grad_mag = mag_sobel_th(img_undist, ks, th)
img_grad_dir = dir_sobel_th(img_undist, ksize=7, thresh=(1.0, 1.2))
img_combined = np.zeros_like(img_undist_gray)
# img_combined[ (img_wlane_th == 1) | (img_ylane_th == 1) ] = 1
img_combined[ (img_wlane_th == 1) | (img_ylane_th == 1) |
(img_grad_abx == 1) | (img_grad_mag == 1) ] = 1
# (img_grad_abx == 1) | (img_grad_mag == 1) | (img_grad_dir == 1) ] = 1
# img_pers, persM = corners_unwarp(img_combined, nx, ny, mtx, dist, src, dst)
img_combined_pers = np.copy(img_pers)
roi_combined = mask_roi(img_combined_pers)
"""
win_c, lc_pts, rc_pts = find_window_centroids(roi_combined, w_win, h_win, margin)
left_fitx, right_fitx, ploty_win = polyfit_window(h_img, lc_pts, rc_pts, h_win)
avg_curve_r = measure_curve_r(ploty_img, lc_pts, rc_pts, ploty_win, h_img)
offset_m = get_offset(lc_pts, rc_pts, w_img)
dist_bw_lines = np.average(left_fitx) - np.average(right_fitx)
self.dist_bw_lines.append(dist_bw_lines)
avg_dist_bw_lines = np.average(self.dist_bw_lines[-60:])
dist_diff_squa = (avg_dist_bw_lines-dist_bw_lines)**2
dist_diff_squa_stack.append(dist_diff_squa)
dist_mse = np.average(dist_diff_squa_stack) # Mean Square Error
print("dist_bw_lines", dist_bw_lines)
print("dist_mse", dist_mse)
if dist_mse <= 750:
def process_frame(self, img_org, flag=False):
img_undist = undistort(img_org, mtx, dist)
img_pers, Mpers = corners_unwarp(img_undist, src, dst)
img_hls_ch_s = hls_select(img_pers, ch='s', thresh=(125, 190))
img_grad_abx = abs_sobel_th(img_pers,
orient='x',
ksize=ks,
thresh=(35, 115))
img_grad_mag = mag_sobel_th(img_pers, ksize=ks, thresh=(35, 115))
img_grad_dir = dir_sobel_th(img_pers, ksize=7, thresh=(0.8, 1.4))
img_wlane_th = threshold(cv2.cvtColor(img_pers, cv2.COLOR_RGB2GRAY),
thresh=(225, 255))
img_roi_wlane = mask_roi(img_wlane_th)
img_ylane_th = threshold(img_pers[:, :, 0], thresh=(235, 255))
img_roi_ylane = mask_roi(img_ylane_th)
img_roi_abx = mask_roi(img_grad_abx)
img_roi_mag = mask_roi(img_grad_mag)
img_roi_hls = mask_roi(img_hls_ch_s)
img_combined = np.zeros_like(img_grad_dir)
img_combined[(img_roi_abx == 1) | (img_roi_hls == 1) | (img_roi_ylane == 1)
| ((img_roi_mag == 1) &
(img_grad_dir == 0)) | (img_roi_wlane == 1)] = 1
win_c, lc_pts, rc_pts = find_window_centroids(img_combined, w_win, h_win,
margin)
left_fitx, right_fitx, ploty_win = polyfit_window(h_img, lc_pts, rc_pts,
h_win)
avg_curve_r = measure_curve_r(ploty_img, lc_pts, rc_pts, ploty_win, h_img)
offset_m = get_offset(lc_pts, rc_pts, w_img)
dist_bw_lines = abs(np.average(left_fitx) - np.average(right_fitx))
self.dist_bw_lines.append(dist_bw_lines)
avg_dist_bw_lines = np.average(self.dist_bw_lines[-60:])
dist_diff_squa = (abs(avg_dist_bw_lines - dist_bw_lines))**2
dist_diff_squa_stack.append(dist_diff_squa)
dist_mse = np.average(dist_diff_squa_stack) # Mean Square Error
if dist_diff_squa <= 750:
self.l_curr_fitx.append([left_fitx])
self.r_curr_fitx.append([right_fitx])
l_avg_fitx = np.average(self.l_curr_fitx[-5:], axis=0)
r_avg_fitx = np.average(self.r_curr_fitx[-5:], axis=0)
img_fin = draw_lane(img_combined, l_avg_fitx, r_avg_fitx, ploty_img,
img_undist, Minvs)
cv2.putText(img_fin, ("Curve Radius: " + str(avg_curve_r) + "m"),
(256, 50), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(img_fin, ("Center Offset: " + str(offset_m) + "m"), (256, 100),
font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(img_fin, ("Distance b/w Lines: " + str(dist_bw_lines)),
(256, 150), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(img_fin, ("Distance Square Err: " + str(dist_diff_squa)),
(256, 200), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(img_fin, ("Distance MSE: " + str(dist_mse)), (256, 250), font,
1, (255, 255, 255), 2, cv2.LINE_AA)
if flag is False:
return img_fin
else:
show_window_centroids(img_combined, w_win, h_win, win_c)
return img_fin, img_grad_abx, img_grad_mag, img_grad_dir, img_combined, show_window_centroids, img_wline_th, img_yline_th