diff --git a/combine_main.py b/combine_main.py
index 2289294..0ed859a 100644
--- a/combine_main.py
+++ b/combine_main.py
@@ -83,7 +83,7 @@ def run():
         #cv.waitKey(150)
         #continue
 
-        spawn_1 = vision_stun.find(screenshot, cv.imread("magic/spawn_1.jpg", cv.IMREAD_UNCHANGED), 0.5, 1)
+        spawn_1 = vision_stun.find(screenshot, cv.imread("magic/spawn_1.jpg", cv.IMREAD_UNCHANGED),  0.5, 1, True, cv.imread("magic/spawn_1-mask.png", cv.IMREAD_UNCHANGED))
         if len(spawn_1) == 1:
             spawn_button_active = True
             points = vision_stun.get_click_points(spawn_1)
@@ -121,7 +121,7 @@ def run():
                 cv.imshow("output_needle", processed_needle)
                 cv.waitKey(150)
 
-                rectangles = vision_stun.find(processed_screenshot, processed_needle, 0.70, 2)
+                rectangles = vision_stun.find(processed_screenshot, processed_needle, 0.90, 2, True, None)
                 # draw the detection results onto the original image
                 #output_image = vision_stun.draw_rectangles(screenshot, rectangles)
                 #cv.imshow("output_image", output_image)
diff --git a/magic/spawn_0.jpg b/magic/spawn_0.jpg
index 31fc3ae..eaed723 100644
Binary files a/magic/spawn_0.jpg and b/magic/spawn_0.jpg differ
diff --git a/magic/spawn_1.jpg b/magic/spawn_1.jpg
index dd7bdc2..f046bdf 100644
Binary files a/magic/spawn_1.jpg and b/magic/spawn_1.jpg differ
diff --git a/readme.txt b/readme.txt
new file mode 100644
index 0000000..ea0cc90
--- /dev/null
+++ b/readme.txt
@@ -0,0 +1,4 @@
+Strength 100      = x2 Mining Bonus
+Endurance 100  = x2 Farming Bonus
+Charisma 100     = x2 Equipment Bonus
+Ethic 100       = x2 Crops Bonus
\ No newline at end of file
diff --git a/vision.py b/vision.py
index 8d91a1a..cdaca19 100644
--- a/vision.py
+++ b/vision.py
@@ -92,13 +92,14 @@ class Vision:
         needle_w = needle_img.shape[1]
         needle_h = needle_img.shape[0]
 
-        if normalize:
+        if mask is not None:
             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)
+            #_minVal, _maxVal, minLoc, maxLoc = cv.minMaxLoc(result, None)
         else:
             result = cv.matchTemplate(haystack_img, needle_img, self.method)
 
+        if normalize:
+            cv.normalize(result, result, 0, 1, cv.NORM_MINMAX, -1)
         # Get the all the positions from the match result that exceed our threshold
         locations = np.where(result >= threshold)
         locations = list(zip(*locations[::-1]))