import cv2
from skimage import segmentation
from skimage.util import img_as_float
from matplotlib import pyplot as plt
import numpy as np

image = cv2.imread("test_img.jpg")

segments = segmentation.slic(img_as_float(image), n_segments=300, compactness=20, sigma=10)
segments += 1
segment_ids = np.unique(segments)
fig = plt.figure("Superpiksele")
ax = fig.add_subplot(1, 1, 1)
ax.imshow(segmentation.mark_boundaries(img_as_float(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), segments))
plt.axis("off")
plt.show()
def get_color_histogram(image, superpixels, index):
    indices = np.where(superpixels.ravel() == index)[0]
    r_hist = np.bincount(image[:, :, 0].ravel()[indices], minlength=256)
    g_hist = np.bincount(image[:, :, 1].ravel()[indices], minlength=256)
    b_hist = np.bincount(image[:, :, 2].ravel()[indices], minlength=256)
    histogram = (r_hist + g_hist + b_hist) / 3
    cv2.imshow(" ", histogram)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    return histogram
get_color_histogram(image, segments, segment_ids)