"""

Image Data Analysis Using Numpy & OpenCV

author: Mohammed Innat

email: innat1994@gmail.com

website: https://iphton.github.io/iphton.github.io/

Please feel free to use and modify this, but keep the above information. Thanks!

"""

# importing necessary packages

from skimage import color

from skimage import exposure

import numpy as np

import imageio

import matplotlib.pyplot as plt

from scipy.signal import convolve2d

# load the image

pic = imageio.imread('<image location>')

plt.figure(figsize = (6,6))

plt.imshow(pic);

# Convert the image to grayscale

img = color.rgb2gray(pic)

# outline kernel - used for edge detection

kernel = np.array([[-1,-1,-1],

[-1,8,-1],

[-1,-1,-1]])

# we use 'valid' which means we do not add zero padding to our image

edges = convolve2d(img, kernel, mode = 'valid')

# Adjust the contrast of the filtered image by applying Histogram Equalization

edges_equalized = exposure.equalize_adapthist(edges/np.max(np.abs(edges)),

clip_limit = 0.03)

# plot the edges_clipped

plt.imshow(edges_equalized, cmap='gray')

plt.axis('off')

plt.show()