def flood_image(original_image_path, flooded_output_path):
"""
Floods background of the image, starting at seeds that
are obtained at the edges in unknown areas. After
filling, unknown areas should only be inside particles.
:param original_image_path: Path to input image
:param flooded_output_path: Path to flooded image
:return: Image where background is BG_COLOR and rest is
either UNKNOWN_COLOR or FG_COLOR.
"""
img = cv2.imread(original_image_path, 0)
sure_fg = Filters.threshold(img, 130, False)
#equalize histogram
# equalized_img = ImageUtilities.histeq(img)
# plt.subplot(121), plt.imshow(img, cmap='gray')
# plt.title('img'), plt.xticks([]), plt.yticks([])
# plt.subplot(122), plt.imshow(equalized_img, cmap='gray')
# plt.title('equalized_img'), plt.xticks([]), plt.yticks([])
# plt.show()
# Scharr filter
grad = Filters.scharr(img)
grad_8 = np.uint8(grad)
grad_bg = Filters.threshold(grad_8, 4, True)
grad_bg[np.all([grad_bg == 0, img < 55], axis=0)] = 255
sure_bg = grad_bg - sure_fg
sure_bg_filtered = Filters.median_filter(sure_bg, 3)
cv2.imwrite('Gradient.tif', grad_bg)
cv2.imwrite('Gradient_Background.tif', grad_bg)
cv2.imwrite('Sure_Background_Filtered.tif', sure_bg_filtered)
sure_bg_inv = Filters.threshold(sure_bg_filtered, 2, True)
sure_bg_inv = (sure_bg_inv // 255) + 1
sure_bg_flood = np.copy(sure_bg_inv)
seeds = find_seeds(sure_bg_flood)
flood_fill(seeds, sure_bg_flood, UNKNOWN_COLOR, BG_COLOR)
cv2.imwrite(flooded_output_path, sure_bg_flood)
return sure_bg_flood
