Harris

app.py

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+import cv2
+import matplotlib.pyplot as plt
+from scipy import signal as sig
+import numpy as np
+from scipy.ndimage.filters import convolve
+import gradio as gr
+
+def gradient_x(imggray):
+    ##Sobel operator kernels.
+    kernel_x = np.array([[-1, 0, 1],[-2, 0, 2],[-1, 0, 1]])
+    return sig.convolve2d(imggray, kernel_x, mode='same')
+
+def gradient_y(imggray):
+    kernel_y = np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]])
+    return sig.convolve2d(imggray, kernel_y, mode='same')
+
+def gaussian_kernel(size, sigma=1):
+    size = int(size) // 2
+    x, y = np.mgrid[-size:size+1, -size:size+1]
+    normal = 1 / (2.0 * np.pi * sigma**2)
+    g =  np.exp(-((x**2 + y**2) / (2.0*sigma**2))) * normal
+    return g
+
+
+def harris(img):
+    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    I_x = gradient_x(img_gray)
+    I_y = gradient_y(img_gray)
+    Ixx = convolve(I_x**2, gaussian_kernel(3, 1))
+    Ixy = convolve(I_y*I_x, gaussian_kernel(3, 1))
+    Iyy = convolve(I_y**2, gaussian_kernel(3, 1))
+
+
+    k = 0.05
+
+    # determinant
+    detA = Ixx * Iyy - Ixy ** 2
+    # trace
+    traceA = Ixx + Iyy
+        
+    harris_response = detA - k * traceA ** 2
+
+    window_size = 3
+    offset = window_size//2
+    width, height = img_gray.shape
+
+    for y in range(offset, height-offset):
+        for x in range(offset, width-offset):
+            Sxx = np.sum(Ixx[y-offset:y+1+offset, x-offset:x+1+offset])
+            Syy = np.sum(Iyy[y-offset:y+1+offset, x-offset:x+1+offset])
+            Sxy = np.sum(Ixy[y-offset:y+1+offset, x-offset:x+1+offset])
+
+    det = (Sxx * Syy) - (Sxy**2)
+    trace = Sxx + Syy
+    r = det - k*(trace**2)
+
+
+    img_copy_for_corners = np.copy(img)
+    img_copy_for_edges = np.copy(img)
+
+    for rowindex, response in enumerate(harris_response):
+        for colindex, r in enumerate(response):
+            if r > 0:
+                # this is a corner
+                img_copy_for_corners[rowindex, colindex] = [255,0,0]
+            elif r < 0:
+                # this is an edge
+                img_copy_for_edges[rowindex, colindex] = [0,255,0]
+
+    return img_copy_for_corners
+
+
+interface = gr.Interface(
+title = "Harris Corner Detector 🤖",
+description = "<h3>The idea is to locate interest points where the surrounding neighbourhood shows edges in more than one direction.</h3> <br> <b>Select an image 🖼</b>",
+article='Step-by-step on GitHub <a href="https://github.com/Ivanrs297/machine-learning-projects/blob/main/computer-vision/edge_detection/main.ipynb"> notebook </a> <br> ~ Ivanrs',
+allow_flagging = "never",
+fn = harris, 
+inputs = [
+    gr.Image(),
+],
+outputs = "image"
+)
+
+interface.launch(share = False)