#%%     #this line is for VSCode editor only

import cv2

#from skimage.measure import compare_ssim

import argparse

#import imutils

import numpy as np

import matplotlib.pyplot as plt

%matplotlib inline

#change the path as per you configuration

img = cv2.imread(r'C:\\Users\\ANSHUL KIYAWAT\\Desktop\\image3.jpg',0)

#sobely = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=5)

#sobelx = cv2.Sobel(img, cv2.CV_64F, 1, 0, ksize=5)

#laplacian = cv2.Laplacian(img,cv2.CV_64F)

def build_filters():

    """ returns a list of kernels in several orientations

    """

    filters = []

    ksize = 31

    for theta in np.arange(0, np.pi, np.pi / 32):

        params = {'ksize': (ksize, ksize), 'sigma': 2.5, 'theta': theta, 'lambd': 15.0,

                  'gamma': 0.02, 'psi': 0, 'ktype': cv2.CV_32F}

        kern = cv2.getGaborKernel(**params)

        kern /= 1.5*kern.sum()

        filters.append((kern, params))

    return filters

def process(img, filters):

    """ returns the img filtered by the filter list

    """

    accum = np.zeros_like(img)

    for kern, params in filters:

        fimg = cv2.filter2D(img, cv2.CV_8UC3, kern)

        np.maximum(accum, fimg, accum)

    return accum

#main

filters = build_filters()

p = process(img, filters)

equ = cv2.equalizeHist(p)

plt.figure(1)

plt.subplot(121), plt.imshow(img, cmap='gray')

plt.title('Original'), plt.xticks([]), plt.yticks([])

plt.subplot(122), plt.imshow(equ, cmap='gray')

plt.title('Gabor Only'),plt.xticks([]),plt.yticks([])

#plt.subplot(123), plt.imshow(equ, cmap='gray')

#plt.title('Histogram + Gabor'), plt.xticks([]), plt.yticks([])