re-implement equipment with masks

vision.py

@@ -72,12 +72,18 @@ class Vision:
 
         return keep_rects
 
-    def find(self, haystack_img, needle_img, threshold=0.5, max_results=10):
+
+    def find(self, haystack_img, needle_img, threshold=0.5, max_results=10, normalize=False, mask=None):
         # run the OpenCV algorithm
         needle_w = needle_img.shape[1]
         needle_h = needle_img.shape[0]
 
-        result = cv.matchTemplate(haystack_img, needle_img, self.method)
+        if normalize:
+            result = cv.matchTemplate(haystack_img, needle_img, cv.TM_CCORR_NORMED, None, mask)
+            _minVal, _maxVal, minLoc, maxLoc = cv.minMaxLoc(result, None)
+            cv.normalize(result, result, 0, 1, cv.NORM_MINMAX, -1)
+        else:
+            result = cv.matchTemplate(haystack_img, needle_img, self.method)
 
         # Get the all the positions from the match result that exceed our threshold
         locations = np.where(result >= threshold)
@@ -91,6 +97,15 @@ class Vision:
         # concatenate together results without causing an error
         if not locations:
             return np.array([], dtype=np.int32).reshape(0, 4)
+        #while len(locations) > 1000:
+        #    threshold = threshold + 0.01
+        #    locations = np.where(result >= threshold)
+        #    locations = list(zip(*locations[::-1]))
+        #    print("modified treshhold to:" + str(threshold))
+        #    print("actual locations:" + str(len(locations)))
+
+        if len(locations) > 5000:
+            return np.array([], dtype=np.int32).reshape(0, 4)
 
         # You'll notice a lot of overlapping rectangles get drawn. We can eliminate those redundant
         # locations by using groupRectangles().