--- a
+++ b/gaussian.py
@@ -0,0 +1,35 @@
+import sys
+import cv2 as cv
+import numpy as np
+from matplotlib import pyplot as plt
+
+ddepth = cv.CV_16S
+kernel_size = 3
+# [variables]
+# [load]
+src = cv.imread(r'C://Users/Shubhi/Desktop/Projects/Kidney-Stone-Detection-IP/images/image2.jpg', cv.IMREAD_COLOR) # Load an image
+# Check if image is loaded fine
+# [load]
+# [reduce_noise]
+# Remove noise by blurring with a Gaussian filter
+src = cv.GaussianBlur(src, (3, 3), 0)
+# [reduce_noise]
+# [convert_to_gray]
+# Convert the image to grayscale
+src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+# [convert_to_gray]
+# Create Window
+# [laplacian]
+# Apply Laplace function
+dst = cv.Laplacian(src_gray, ddepth, kernel_size)
+# [laplacian]
+# [convert]
+# converting back to uint8
+abs_dst = cv.convertScaleAbs(dst)
+# [convert]
+# [display]
+plt.subplot(121),plt.imshow(src, cmap = 'gray')
+plt.title('Input Image'), plt.xticks([]), plt.yticks([])
+plt.subplot(122),plt.imshow(abs_dst, cmap = 'gray')
+plt.title('Magnitude Spectrum'), plt.xticks([]), plt.yticks([])
+plt.show()