formatting

locate.py

@@ -1,6 +1,7 @@
 import cv2
 import numpy as np
 
+
 def non_max_suppression(boxes, overlapThresh):
     if len(boxes) == 0:
         return []
@@ -12,10 +13,10 @@ def non_max_suppression(boxes, overlapThresh):
     pick = []
 
     # Grab the coordinates of the bounding boxes
-    x1 = boxes[:,0]
-    y1 = boxes[:,1]
-    x2 = boxes[:,2]
-    y2 = boxes[:,3]
+    x1 = boxes[:, 0]
+    y1 = boxes[:, 1]
+    x2 = boxes[:, 2]
+    y2 = boxes[:, 3]
 
     # Compute the area of the bounding boxes and sort by bottom-right y-coordinate
     area = (x2 - x1 + 1) * (y2 - y1 + 1)
@@ -43,15 +44,18 @@ def non_max_suppression(boxes, overlapThresh):
         overlap = (w * h) / area[idxs[:last]]
 
         # Delete all indexes from the index list that have overlap greater than the threshold
-        idxs = np.delete(idxs, np.concatenate(([last], np.where(overlap > overlapThresh)[0])))
+        idxs = np.delete(
+            idxs, np.concatenate(([last], np.where(overlap > overlapThresh)[0]))
+        )
 
     # Return only the bounding boxes that were picked
     return boxes[pick].astype("int")
 
+
 # Load images
-target_image = cv2.imread('test/20240108_021855.png')
-template_image = cv2.imread('templates/end_of_log.jpg')
-w, h = template_image.shape[:-1]
+target_image = cv2.imread("test/20240108_224218.jpg")
+template_image = cv2.imread("templates/dungeon/attack.png")
+h, w = template_image.shape[:-1]
 
 # Template matching
 result = cv2.matchTemplate(target_image, template_image, cv2.TM_CCOEFF_NORMED)
@@ -70,15 +74,15 @@ rectangles = [(*loc, loc[0] + w, loc[1] + h) for loc in locations]
 rectangles = non_max_suppression(rectangles, 0.3)
 
 # Draw rectangles around matches
-for (startX, startY, endX, endY) in rectangles:
+for startX, startY, endX, endY in rectangles:
     cv2.rectangle(target_image, (startX, startY), (endX, endY), (0, 255, 0), 2)
 
     # Print the coordinates of the rectangle
-    centerX = round(startX + (endX-startX)/2)
-    centerY = round(startY + (endY-startY)/2)
+    centerX = round(startX + (endX - startX) / 2)
+    centerY = round(startY + (endY - startY) / 2)
     print(f"center coordinates: {centerX}/{centerY}")
 
 # Display the result
-cv2.imshow('Matched Results', target_image)
+cv2.imshow("Matched Results", target_image)
 cv2.waitKey(0)
 cv2.destroyAllWindows()