# Read image in grayscale.
img = cv2.imread('road_lanes.png', cv2.IMREAD_GRAYSCALE)

# Perform binary thresholding.
retval, img_thresh = cv2.threshold(img, 165, 255, cv2.THRESH_BINARY_INV)

# Display the images.
plt.figure(figsize = [20, 8])
plt.subplot(121); plt.imshow(img); plt.title('Original')
plt.subplot(122); plt.imshow(img_thresh); plt.title('Thresholded');
print(img_thresh[0][0])

# Read the original image.
img = cv2.imread('Piano_Sheet_Music.png', cv2.IMREAD_GRAYSCALE)

# Perform adaptive thresholding.
img_thresh_adp = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 13, 7)

# Display the images.
plt.figure(figsize = [18, 15])
plt.subplot(221); plt.imshow(img);              plt.title('Original')
plt.subplot(224); plt.imshow(img_thresh_adp);   plt.title('Thresholded (adaptive)');
print(img_thresh_gbl_1[0][0])