Detecting geometrical shapes using opencv

Image-Processing/Detecting Contours/detecting_geometrical_shapes.py

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+import numpy as np
+import cv2
+
+img = cv2.imread('shapes.PNG')
+imgGry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+
+ret , thrash = cv2.threshold(imgGry, 240 , 255, cv2.CHAIN_APPROX_NONE)
+contours , hierarchy = cv2.findContours(thrash, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+
+
+for contour in contours:
+    approx = cv2.approxPolyDP(contour, 0.01* cv2.arcLength(contour, True), True)
+    cv2.drawContours(img, [approx], 0, (0, 0, 0), 5)
+    x = approx.ravel()[0]
+    y = approx.ravel()[1] - 5
+
+    if len(approx) == 3:
+        cv2.putText( img, "Triangle", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0) )
+    elif len(approx) == 4 :
+        x, y , w, h = cv2.boundingRect(approx)
+        aspectRatio = float(w)/h
+        print(aspectRatio)
+        if aspectRatio >= 0.95 and aspectRatio < 1.05:
+            cv2.putText(img, "square", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0))
+
+        else:
+            cv2.putText(img, "rectangle", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0))
+
+    elif len(approx) == 5 :
+        cv2.putText(img, "pentagon", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0))
+
+    elif len(approx) == 10 :
+        cv2.putText(img, "star", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0))
+
+    else:
+        cv2.putText(img, "circle", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0))
+
+cv2.imshow('shapes', img)
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+
+