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lines_slope_intercept.argmax(axis=0)
lines_slope_intercept.argmin(axis=0)
max (immediate left)
slopes (i.e. slope and intercept within x%)
abs(line[0] - max_slope_line[0])
abs(line[1] - max_slope_line[1])
left_slopes.append(line[0])
left_intercepts.append(line[1])
abs(line[0] - min_slope_line[0])
abs(line[1] - min_slope_line[1])
right_slopes.append(line[0])
right_intercepts.append(line[1])
np.zeros(shape=(1,2,4)
len(left_slopes)
sum(left_slopes)
len(left_slopes)
sum(left_intercepts)
len(left_intercepts)
if (left_bottom_x >= 0)
len(right_slopes)
sum(right_slopes)
len(right_slopes)
sum(right_intercepts)
len(right_intercepts)
if (right_bottom_x <= x_size)
cv2.line(img, (x1, y1)
hough_lines(img, rho, theta, threshold, min_line_len, max_line_gap)
cv2.HoughLinesP(img, rho, theta, threshold, np.array([])
np.zeros((img.shape[0], img.shape[1], 3)
draw_lines(line_img, lines)
weighted_img(img, initial_img, α=0.8, β=1., λ=0.)
hough_lines()
image (all black)
cv2.addWeighted(initial_img, α, img, β, λ)
os.listdir("test_images/")
enumerate(os.listdir("test_images/")
mpimg.imread('test_images/' + img)
grayscale(image)
hsv(image)
np.array([20,100,100])
np.array([30,255,255])
np.array([0,0,235])
np.array([255,255,255])
cv2.inRange(hsv_img, lower_yel, upper_yel)
cv2.inRange(hsv_img, lower_wht, upper_wht)
cv2.bitwise_or(yellow_mask, white_mask)
astype('uint8')
cv2.bitwise_or(subdued_gray, full_mask)
gaussian_blur(boosted_lanes,kernel_size)
canny(blurred_img,canny_low_threshold,canny_high_threshold)
np.array([[(x*0.,y)
region_of_interest(edges_img, vertices)
hough_lines(masked_img,hough_rho,hough_theta,hough_threshold,hough_min_line_length,hough_max_line_gap)
weighted_img(hough_img,image)
plt.figure(figsize=(6,10)
plt.imshow(result, cmap="gray")
plt.imshow(gray, cmap='gray')
enumerate(os.listdir("test_images2/")
mpimg.imread('test_images2/' + img)
grayscale(image)
hsv(image)
np.array([20,100,100])
np.array([30,255,255])
np.array([0,0,235])
np.array([255,255,255])
cv2.inRange(hsv_img, lower_yel, upper_yel)
cv2.inRange(hsv_img, lower_wht, upper_wht)
cv2.bitwise_or(yellow_mask, white_mask)
astype('uint8')
cv2.bitwise_or(subdued_gray, full_mask)
gaussian_blur(boosted_lanes,kernel_size)
canny(blurred_img,canny_low_threshold,canny_high_threshold)
np.array([[(x*0.,y)
region_of_interest(edges_img, vertices)
hough_lines(masked_img,hough_rho,hough_theta,hough_threshold,hough_min_line_length,hough_max_line_gap)
weighted_img(hough_img,image)
plt.figure(figsize=(8,10)
plt.imshow(result, cmap="gray")
plt.imshow(gray, cmap='gray')
process_image(image)
image (3 channel)
output (image with lines are drawn on lanes)
grayscale(image)
hsv(image)
np.array([20,100,100])
np.array([30,255,255])
np.array([0,0,235])
np.array([255,255,255])
cv2.inRange(hsv_img, lower_yel, upper_yel)
cv2.inRange(hsv_img, lower_wht, upper_wht)
cv2.bitwise_or(yellow_mask, white_mask)
astype('uint8')
cv2.bitwise_or(subdued_gray, full_mask)
gaussian_blur(boosted_lanes,kernel_size)
canny(blurred_img,canny_low_threshold,canny_high_threshold)
np.array([[(x*0.,y)
region_of_interest(edges_img, vertices)
hough_lines(masked_img,hough_rho,hough_theta,hough_threshold,hough_min_line_length,hough_max_line_gap)
weighted_img(hough_img,image)
cv2.cvtColor(masked_img, cv2.COLOR_GRAY2RGB)