From 7a14285cb684698ad5a4e0196444e76fdb7e4176 Mon Sep 17 00:00:00 2001
From: Jeffin Francis <francisjeffin07@gmail.com>
Date: Thu, 4 Jun 2020 19:32:51 +0530
Subject: [PATCH] Harris corner detection (#2064)
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* Added Lstm example for stock predection

* Changes after review

* changes after build failed

* Add Kiera’s to requirements.txt

* requirements.txt: Add keras and tensorflow

* psf/black

* haris corner detection

* fixup! Format Python code with psf/black push

* changes after review

* changes after review

* fixup! Format Python code with psf/black push

Co-authored-by: Christian Clauss <cclauss@me.com>
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
---
 computer_vision/harriscorner.py | 75 +++++++++++++++++++++++++++++++++
 maths/number_of_digits.py       |  2 +-
 2 files changed, 76 insertions(+), 1 deletion(-)
 create mode 100644 computer_vision/harriscorner.py

diff --git a/computer_vision/harriscorner.py b/computer_vision/harriscorner.py
new file mode 100644
index 000000000..35302f014
--- /dev/null
+++ b/computer_vision/harriscorner.py
@@ -0,0 +1,75 @@
+import numpy as np
+import cv2
+
+"""
+Harris Corner Detector
+https://en.wikipedia.org/wiki/Harris_Corner_Detector
+"""
+
+
+class Harris_Corner:
+    def __init__(self, k: float, window_size: int):
+
+        """
+        k : is an empirically determined constant in [0.04,0.06]
+        window_size : neighbourhoods considered
+        """
+
+        if k in (0.04, 0.06):
+            self.k = k
+            self.window_size = window_size
+        else:
+            raise ValueError("invalid k value")
+
+    def __str__(self):
+
+        return f"Harris Corner  detection with k : {self.k}"
+
+    def detect(self, img_path: str):
+
+        """
+        Returns the image with corners identified
+        img_path  : path of the image
+        output : list of the corner positions, image
+        """
+
+        img = cv2.imread(img_path, 0)
+        h, w = img.shape
+        corner_list = []
+        color_img = img.copy()
+        color_img = cv2.cvtColor(color_img, cv2.COLOR_GRAY2RGB)
+        dy, dx = np.gradient(img)
+        ixx = dx ** 2
+        iyy = dy ** 2
+        ixy = dx * dy
+        k = 0.04
+        offset = self.window_size // 2
+        for y in range(offset, h - offset):
+            for x in range(offset, w - offset):
+                wxx = ixx[
+                    y - offset : y + offset + 1, x - offset : x + offset + 1
+                ].sum()
+                wyy = iyy[
+                    y - offset : y + offset + 1, x - offset : x + offset + 1
+                ].sum()
+                wxy = ixy[
+                    y - offset : y + offset + 1, x - offset : x + offset + 1
+                ].sum()
+
+                det = (wxx * wyy) - (wxy ** 2)
+                trace = wxx + wyy
+                r = det - k * (trace ** 2)
+                # Can change the value
+                if r > 0.5:
+                    corner_list.append([x, y, r])
+                    color_img.itemset((y, x, 0), 0)
+                    color_img.itemset((y, x, 1), 0)
+                    color_img.itemset((y, x, 2), 255)
+        return color_img, corner_list
+
+
+if __name__ == "__main__":
+
+    edge_detect = Harris_Corner(0.04, 3)
+    color_img, _ = edge_detect.detect("path_to_image")
+    cv2.imwrite("detect.png", color_img)
diff --git a/maths/number_of_digits.py b/maths/number_of_digits.py
index 127170651..30e82f60f 100644
--- a/maths/number_of_digits.py
+++ b/maths/number_of_digits.py
@@ -15,4 +15,4 @@ def num_digits(n: int) -> int:
 
 
 if __name__ == "__main__":
-    print(num_digits(12345))   # ===> 5
+    print(num_digits(12345))  # ===> 5