Update app.py

app.py

@@ -310,7 +310,8 @@ def calculate_paper_scaling_factor(paper_contour: np.ndarray, paper_size: str) -
     scale_y = expected_height_mm / detected_height_px
     
     # Use average of both scales
-    scaling_factor = (scale_x + scale_y) / 2
+    # scaling_factor = (scale_x + scale_y) / 2
+    scaling_factor = min(scale_x, scale_y)
     
     logger.info(f"Paper detection: {detected_width_px}x{detected_height_px} px -> {expected_width_mm}x{expected_height_mm} mm")
     logger.info(f"Calculated scaling factor: {scaling_factor:.4f} mm/px")
@@ -408,11 +409,25 @@ def exclude_paper_area(mask: np.ndarray, paper_contour: np.ndarray, expansion_fa
     # Create paper mask with slight expansion to ensure complete removal
     paper_mask = np.zeros(mask.shape[:2], dtype=np.uint8)
     
-    # Expand paper contour slightly
-    epsilon = expansion_factor * cv2.arcLength(paper_contour, True)
-    expanded_contour = cv2.approxPolyDP(paper_contour, epsilon, True)
+    # # Expand paper contour slightly
+    # epsilon = expansion_factor * cv2.arcLength(paper_contour, True)
+    # expanded_contour = cv2.approxPolyDP(paper_contour, epsilon, True)
     
-    cv2.fillPoly(paper_mask, [expanded_contour], 255)
+    # cv2.fillPoly(paper_mask, [expanded_contour], 255)
+    # Create a more aggressive inward shrinking of paper bounds
+    rect = cv2.boundingRect(paper_contour)
+    shrink_pixels = int(min(rect[2], rect[3]) * 0.05)  # Shrink by 5% of smaller dimension
+    
+    # Create shrunken rectangle
+    x, y, w, h = rect
+    shrunken_contour = np.array([
+        [[x + shrink_pixels, y + shrink_pixels]],
+        [[x + w - shrink_pixels, y + shrink_pixels]],
+        [[x + w - shrink_pixels, y + h - shrink_pixels]],
+        [[x + shrink_pixels, y + h - shrink_pixels]]
+    ])
+    
+    cv2.fillPoly(paper_mask, [shrunken_contour], 255)
     
     # Invert paper mask and apply to object mask
     paper_mask_inv = cv2.bitwise_not(paper_mask)
@@ -469,7 +484,7 @@ def save_dxf_spline(inflated_contours, scaling_factor, height, finger_clearance=
     original_polygons = []
 
     # Scale correction factor
-    scale_correction = 1.079
+    scale_correction = 1.0
 
     for contour in inflated_contours:
         try:
@@ -840,11 +855,13 @@ def predict_with_paper(image, paper_size, offset,offset_unit, finger_clearance=F
     # Apply edge rounding if specified
     rounded_mask = objects_mask.copy()
     
-    # Apply dilation for offset
+    # Apply dilation for offset - more precise calculation
     if offset_mm > 0:
-        offset_pixels = (float(offset_mm) / scaling_factor)  # Remove the *2 +1 which was causing excessive dilation
-        kernel = np.ones((int(offset_pixels), int(offset_pixels)), np.uint8)
-        dilated_mask = cv2.dilate(rounded_mask, kernel)
+        offset_pixels = int(round(float(offset_mm) / scaling_factor))
+        if offset_pixels > 0:
+            kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (offset_pixels*2+1, offset_pixels*2+1))
+            dilated_mask = cv2.dilate(rounded_mask, kernel, iterations=1)
+        
     else:
         dilated_mask = rounded_mask.copy()