work on segments.py

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

image = cv2.imread("test.png")
segments = slic(img_as_float(image), n_segments = 100, sigma = 5)
# show the output of SLIC
"""fig = plt.figure("Superpixels")
ax = fig.add_subplot(1, 1, 1)
ax.imshow(mark_boundaries(img_as_float(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), segments))
plt.axis("off")
plt.show()"""
print(segments)
print(len(segments))
print(len(segments[0]))
cv2.imshow("pixels",image)

for (i, segVal) in enumerate(np.unique(segments)):
	# construct a mask for the segment
	#print ("[x] inspecting segment %d" % (i))
	print(segVal,i)
	mask = np.zeros(image.shape[:2], dtype = "uint8")
	mask[segments == segVal] = 255
	# show the masked region
	cv2.imshow("Mask", mask)
	cv2.imshow("Applied", cv2.bitwise_and(image, image, mask = mask))
	cv2.waitKey(0)