Add main agent, cli and opencv image template comparison test

tests/templateMatching.py

@@ -0,0 +1,48 @@
+import os
+import cv2 as cv
+from matplotlib import pyplot as plt
+ 
+# interpolate here_path to get the path to the fishing target image      
+herePath = os.path.dirname(os.path.realpath(__file__))
+
+img = cv.imread(os.path.join(herePath, "assets", "Bobber2.png"), cv.IMREAD_GRAYSCALE)
+assert img is not None, "file could not be read, check with os.path.exists()"
+img2 = img.copy()
+template = cv.imread(os.path.join(herePath, "assets", "FishTest3.png"), cv.IMREAD_GRAYSCALE)
+assert template is not None, "file could not be read, check with os.path.exists()"
+w, h = template.shape[::-1]
+ 
+# All the 6 methods for comparison in a list
+methods = ['TM_CCOEFF', 'TM_CCOEFF_NORMED', 'TM_CCORR',
+            'TM_CCORR_NORMED', 'TM_SQDIFF', 'TM_SQDIFF_NORMED']
+ 
+for meth in methods:
+    img = img2.copy()
+    method = getattr(cv, meth)
+ 
+    # Apply template Matching
+    res = cv.matchTemplate(img,template,method)
+    min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res)
+ 
+    # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
+    if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
+        top_left = min_loc
+    else:
+        top_left = max_loc
+    bottom_right = (top_left[0] + w, top_left[1] + h)
+ 
+    cv.rectangle(img,top_left, bottom_right, 255, 2)
+ 
+    plt.subplot(121)
+    plt.imshow(res,cmap = 'gray')
+    plt.title('Matching Result')
+    plt.xticks([])
+    plt.yticks([])
+    plt.subplot(122)
+    plt.imshow(img,cmap = 'gray')
+    plt.title('Detected Point')
+    plt.xticks([])
+    plt.yticks([])
+    plt.suptitle(meth)
+ 
+    plt.show()