added laplacian_filter file

digital_image_processing/filters/laplacian_filter.py

@@ -0,0 +1,79 @@
+# @Author  : ojas-wani
+# @File    : laplacian_filter.py
+# @Date    : 10/04/2023
+
+import numpy as np
+from cv2 import (
+    BORDER_DEFAULT,
+    COLOR_BGR2GRAY,
+    CV_64F,
+    cvtColor,
+    filter2D,
+    imread,
+    imshow,
+    waitKey,
+)
+from digital_image_processing.filters.gaussian_filter import gaussian_filter
+
+
+def my_laplacian(ksize: int, src: np.ndarray) -> np.ndarray:
+    """
+    :param src: the source image, which should be a grayscale or color image.
+    :param ksize: the size of the kernel used to compute the Laplacian filter,
+                  which can be 1, 3, 5 or 7.
+
+    """
+
+    # Create a Laplacian kernel matrix according to the ksize
+    if ksize == 1:
+        kernel = np.array([[0, -1, 0], [-1, 4, -1], [0, -1, 0]])
+    elif ksize == 3:
+        kernel = np.array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
+    elif ksize == 5:
+        kernel = np.array(
+            [
+                [0, 0, -1, 0, 0],
+                [0, -1, -2, -1, 0],
+                [-1, -2, 16, -2, -1],
+                [0, -1, -2, -1, 0],
+                [0, 0, -1, 0, 0],
+            ]
+        )
+    elif ksize == 7:
+        kernel = np.array(
+            [
+                [0, 0, 0, -1, 0, 0, 0],
+                [0, 0, -2, -3, -2, 0, 0],
+                [0, -2, -7, -10, -7, -2, 0],
+                [-1, -3, -10, 68, -10, -3, -1],
+                [0, -2, -7, -10, -7, -2, 0],
+                [0, 0, -2, -3, -2, 0, 0],
+                [0, 0, 0, -1, 0, 0, 0],
+            ]
+        )
+
+    # Apply the Laplacian kernel using convolution
+    laplacian_result = filter2D(
+        src, CV_64F, kernel, 0, borderType=BORDER_DEFAULT, anchor=(0, 0)
+    )
+
+    return laplacian_result
+
+
+if __name__ == "__main__":
+    # read original image
+    img = imread(r"../image_data/lena.jpg")
+
+    # turn image in gray scale value
+    gray = cvtColor(img, COLOR_BGR2GRAY)
+
+    # Applying gaussian filter
+    blur_image = gaussian_filter(gray, 3, sigma=1)
+
+    # Apply multiple Kernel to detect edges
+    laplacian_image = my_laplacian(ksize=3, src=blur_image)
+
+    imshow("Original image", img)
+    imshow("Deteced edges using laplacian filter", laplacian_image)
+
+    waitKey(0)