Implement template matching position retrieval in VideoEditor

This commit introduces a new method to get the template matching position and confidence for a specific frame. It optimizes the tracking process by utilizing cropped regions for faster template matching while maintaining functionality for full frame matching when no crop is set. Additionally, it updates the rendering logic to visualize the template matching point on the canvas, enhancing user feedback with confidence levels displayed. This update improves the overall accuracy and efficiency of the template matching feature.

croppa/main.py

@@ -1760,6 +1760,38 @@ class VideoEditor:
                 return (x1 + t * (x2 - x1), y1 + t * (y2 - y1))
         return None
 
+    def _get_template_matching_position(self, frame_number):
+        """Get template matching position and confidence for a frame"""
+        if not self.template_matching_enabled or self.tracking_template is None:
+            return None
+        
+        if self.current_display_frame is not None:
+            # Use only the cropped region for much faster template matching
+            if self.crop_rect:
+                crop_x, crop_y, crop_w, crop_h = self.crop_rect
+                # Extract only the cropped region from raw frame
+                cropped_frame = self.current_display_frame[crop_y:crop_y+crop_h, crop_x:crop_x+crop_w]
+                if cropped_frame is not None and cropped_frame.size > 0:
+                    # Track template in cropped frame (much faster!)
+                    result = self.track_template(cropped_frame)
+                    if result:
+                        center_x, center_y, confidence = result
+                        # Map from cropped frame coordinates to raw frame coordinates
+                        # Add crop offset back
+                        raw_x = center_x + crop_x
+                        raw_y = center_y + crop_y
+                        return (raw_x, raw_y, confidence)
+            else:
+                # No crop - use full frame
+                raw_frame = self.current_display_frame.copy()
+                if raw_frame is not None:
+                    result = self.track_template(raw_frame)
+                    if result:
+                        center_x, center_y, confidence = result
+                        return (center_x, center_y, confidence)
+        
+        return None
+
     def _get_display_params(self):
         """Unified display transform parameters for current frame in rotated space."""
         eff_x, eff_y, eff_w, eff_h = self._get_effective_crop_rect_for_frame(getattr(self, 'current_frame', 0))
@@ -2957,6 +2989,23 @@ class VideoEditor:
                 cv2.circle(canvas, (sx, sy), 4, (0, 255, 0), -1)  # Green circles for features
                 cv2.circle(canvas, (sx, sy), 4, (255, 255, 255), 1)
         
+        # Draw template matching point (blue circle with confidence)
+        if (not self.is_image_mode and 
+            self.template_matching_enabled and 
+            self.tracking_template is not None):
+            # Get template matching position for current frame
+            template_pos = self._get_template_matching_position(self.current_frame)
+            if template_pos:
+                tx, ty, confidence = template_pos
+                # Map to screen coordinates
+                sx, sy = self._map_rotated_to_screen(tx, ty)
+                # Draw blue circle for template matching
+                cv2.circle(canvas, (sx, sy), 8, (255, 0, 255), -1)  # Magenta circle for template
+                cv2.circle(canvas, (sx, sy), 8, (255, 255, 255), 2)
+                # Draw confidence text
+                conf_text = f"{confidence:.2f}"
+                cv2.putText(canvas, conf_text, (sx + 10, sy - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
+        
         # Draw selection rectangles for feature extraction/deletion
         if self.selective_feature_extraction_rect:
             x, y, w, h = self.selective_feature_extraction_rect