M = cv2.getPerspectiveTransform(src, dst)
trans = cv2.warpPerspective(img, M, img.shape[1::-1], flags=cv2.INTER_LINEAR)
trans_on_test.append(trans)
thresh = []
binary_wrapeds = []
histogram = []
for img in undistorted:
x_thresh = utils.abs_sobel_thresh(img, orient='x', thresh_min=55, thresh_max=100)
mag_thresh = utils.mag_thresh(img, sobel_kernel=3, mag_thresh=(70, 255))
dir_thresh = utils.dir_threshold(img, sobel_kernel=3, thresh=(0.7, 1.3))
s_thresh = utils.hls_select(img,channel='s',thresh=(160, 255))
s_thresh_2 = utils.hls_select(img,channel='s',thresh=(200, 240))
white_mask = utils.select_white(img)
yellow_mask = utils.select_yellow(img)
combined = np.zeros_like(mag_thresh)
# combined[(x_thresh==1) | ((mag_thresh == 1) & (dir_thresh == 1)) | (s_thresh==1)] = 1
# combined[((mag_thresh == 1) & (dir_thresh == 1))] = 1
combined[((x_thresh == 1) | (s_thresh == 1)) | ((mag_thresh == 1) & (dir_thresh == 1))| (white_mask>0)|(s_thresh_2 == 1) ]=1
src = np.float32([[(203, 720), (585, 460), (695, 460), (1127, 720)]])
dst = np.float32([[(320, 720), (320, 0), (960, 0), (960, 720)]])
M = cv2.getPerspectiveTransform(src, dst)
binary_warped = cv2.warpPerspective(combined, M, img.shape[1::-1], flags=cv2.INTER_LINEAR)
hist = np.sum(binary_warped[binary_warped.shape[0]//2:,:], axis=0)
histogram.append(hist)
binary_wrapeds.append(binary_warped)
thresh = []
binary_wrapeds = []
histogram = []
for img in undistorted:
x_thresh = utils.abs_sobel_thresh(img,
orient='x',
thresh_min=55,
thresh_max=100)
mag_thresh = utils.mag_thresh(img, sobel_kernel=3, mag_thresh=(70, 255))
dir_thresh = utils.dir_threshold(img, sobel_kernel=3, thresh=(0.7, 1.3))
s_thresh = utils.hls_select(img, channel='s', thresh=(160, 255))
s_thresh_2 = utils.hls_select(img, channel='s', thresh=(200, 240))
white_mask = utils.select_white(img)
yellow_mask = utils.select_yellow(img)
combined = np.zeros_like(mag_thresh)
# combined[(x_thresh==1) | ((mag_thresh == 1) & (dir_thresh == 1)) | (s_thresh==1)] = 1
# combined[((mag_thresh == 1) & (dir_thresh == 1))] = 1
combined[((x_thresh == 1) | (s_thresh == 1)) | ((mag_thresh == 1) &
(dir_thresh == 1)) |
(white_mask > 0) | (s_thresh_2 == 1)] = 1
src = np.float32([[(203, 720), (585, 460), (695, 460), (1127, 720)]])
dst = np.float32([[(320, 720), (320, 0), (960, 0), (960, 720)]])
M = cv2.getPerspectiveTransform(src, dst)
binary_warped = cv2.warpPerspective(combined,
M,
img.shape[1::-1],
flags=cv2.INTER_LINEAR)