--- a
+++ b/Gabor_HistEq.py
@@ -0,0 +1,57 @@
+#%%     #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([])