Update scalingtestupdated.py

scalingtestupdated.py

@@ -30,7 +30,7 @@ class ScalingSquareDetector:
             raise ValueError("Invalid feature detector. Choose 'ORB' or 'SIFT'.")
 
     def find_scaling_square(
-        self, reference_image_path, target_image, known_size_mm, roi_margin=30
+        self, target_image, known_size_mm, roi_margin=30
     ):
         """
         Detect the scaling square in the target image based on the reference image.
@@ -50,22 +50,23 @@ class ScalingSquareDetector:
 
         # # Select the largest square-like contour
         largest_square = None
-        largest_square_area = 0
-        for contour in contours:
-            x_c, y_c, w_c, h_c = cv2.boundingRect(contour)
-            aspect_ratio = w_c / float(h_c)
-            if 0.9 <= aspect_ratio <= 1.1:
-                peri = cv2.arcLength(contour, True)
-                approx = cv2.approxPolyDP(contour, 0.02 * peri, True)
-                if len(approx) == 4:
-                    area = cv2.contourArea(contour)
-                    if area > largest_square_area:
-                        largest_square = contour
-                        largest_square_area = area
+        # largest_square_area = 0
+        # for contour in contours:
+        #     x_c, y_c, w_c, h_c = cv2.boundingRect(contour)
+        #     aspect_ratio = w_c / float(h_c)
+        #     if 0.9 <= aspect_ratio <= 1.1:
+        #         peri = cv2.arcLength(contour, True)
+        #         approx = cv2.approxPolyDP(contour, 0.02 * peri, True)
+        #         if len(approx) == 4:
+        #             area = cv2.contourArea(contour)
+        #             if area > largest_square_area:
+        #                 largest_square = contour
+        #                 largest_square_area = area
 
         # if largest_square is None:
         #     raise ValueError("No square-like contour found in the ROI.")
-
+        for contour in contours:
+            largest_square=contour
         # Draw the largest contour on the original image
         target_image_color = cv2.cvtColor(target_image, cv2.COLOR_GRAY2BGR)
         cv2.drawContours(
@@ -82,7 +83,7 @@ class ScalingSquareDetector:
 
         # Calculate the scaling factor
         avg_square_size_px = (square_width_px + square_height_px) / 2
-        scaling_factor = 0.5 / avg_square_size_px  # mm per pixel
+        scaling_factor = known_size_mm / avg_square_size_px  # mm per pixel
 
         return scaling_factor #, square_height_px, square_width_px, roi_binary
 
@@ -101,9 +102,8 @@ class ScalingSquareDetector:
 
 
 def calculate_scaling_factor(
-    reference_image_path,
     target_image,
-    known_square_size_mm=12.7,
+    reference_obj_size_mm=0.955,
     feature_detector="ORB",
     debug=False,
     roi_margin=30,
@@ -113,9 +113,8 @@ def calculate_scaling_factor(
 
     # Find scaling square and calculate scaling factor
     scaling_factor = detector.find_scaling_square(
-        reference_image_path=reference_image_path,
         target_image=target_image,
-        known_size_mm=known_square_size_mm,
+        known_size_mm=reference_obj_size_mm,
         roi_margin=roi_margin,
     )
 
@@ -137,7 +136,7 @@ if __name__ == "__main__":
     for idx, file in enumerate(os.listdir("./sample_images")):
         img = np.array(Image.open(os.path.join("./sample_images", file)))
         img = yolo_detect(img, ['box'])
-        model = YOLO("./last.pt")
+        model = YOLO("./coin_det.pt")
         res = model.predict(img, conf=0.6)
         
         box_img = save_one_box(res[0].cpu().boxes.xyxy, im=res[0].orig_img, save=False)
@@ -148,9 +147,8 @@ if __name__ == "__main__":
         try:
 
             scaling_factor = calculate_scaling_factor(
-                reference_image_path="./Reference_ScalingBox.jpg",
                 target_image=box_img,
-                known_square_size_mm=12.7,
+                known_square_size_mm=0.955,
                 feature_detector="ORB",
                 debug=False,
                 roi_margin=90,
@@ -158,7 +156,7 @@ if __name__ == "__main__":
             # cv2.imwrite(f"./outputs/{idx}_binary_{file}", roi_binary)
             
             # Square size in mm
-            # square_size_mm = 12.7
+            # square_size_mm = 0.955
 
             # # Compute the calculated scaling factors and compare
             # calculated_scaling_factor = square_size_mm / height_px
@@ -177,4 +175,4 @@ if __name__ == "__main__":
         except Exception as e:
             from traceback import print_exc
             print(print_exc())
-            print(f"Error: {e}")
+            print(f"Error: {e}")