feat: gauss (i dont effing know tbhh) lab4

labo4.py

@@ -108,11 +108,21 @@ def sharpen(img: Img, isotropy: Isotropy) -> Img:
     return new_image
 
 
+def gauss_kernel(length: int = 3, sigma: float = 1.0) -> Img:
+    half = (length - 1) / 2
+    x_axis = np.linspace(-half, half, length)
+
+    gauss = np.exp(-0.5 * np.square(x_axis) / np.square(sigma))
+    kernel = np.outer(gauss, gauss)
+
+    return kernel / np.sum(kernel)
+
+
 if __name__ == "__main__":
-    img = load_img("resources/hotel.png")
+    img = load_img("resources/noisy_hotel.png")
     gray = rgb_to_gray(img)
 
-    laplacian = laplace(gray, Isotropy.ISO_45)
+    laplacian = laplace(xcorr(gray, gauss_kernel()), Isotropy.ISO_45)
     thresholded = thresholding(laplacian, 50)
 
     sharp_iso_90 = sharpen(gray, Isotropy.ISO_90)