Update app.py

app.py

@@ -41,10 +41,6 @@ class ReferenceBoxNotDetectedError(Exception):
     """Raised when the reference box cannot be detected in the image"""
     pass
 
-class BoundaryExceedsError(Exception):
-    """Raised when the optional boundary dimensions exceed allowed image dimensions."""
-    pass
-
 class BoundaryOverlapError(Exception):
     """Raised when the optional boundary dimensions are too small and overlap with the inner contours."""
     pass
@@ -390,11 +386,6 @@ def add_rectangular_boundary(doc, polygons_inch, boundary_length, boundary_width
     if boundary_width_in <= inner_width + 2 * clearance_side or boundary_length_in <= inner_length + 2 * clearance_tb:
         raise BoundaryOverlapError("Error: The specified boundary dimensions are too small and overlap with the inner contours. Please provide larger values.")
 
-    # Check if boundary exceeds image limits (1 inch less than image dimensions)
-    if image_height_in is not None and image_width_in is not None:
-        if boundary_length_in > (image_height_in - 2) or boundary_width_in > (image_width_in - 2):
-            raise BoundaryExceedsError("Error: The specified boundary dimensions exceed the allowed image dimensions. Please enter smaller values.")
-
     # Calculate center of inner contours
     center_x = (min_x + max_x) / 2
     center_y = (min_y + max_y) / 2
@@ -462,23 +453,32 @@ def predict(
         image = np.array(enhanced_image)
 
     # ---------------------
-    # 1) Detect the drawer with YOLOWorld
+    # 1) Detect the drawer with YOLOWorld (or use original image if not detected)
     # ---------------------
+    drawer_detected = True
     try:
         t = time.time()
         drawer_img = yolo_detect(image)
         print("Drawer detection completed in {:.2f} seconds".format(time.time() - t))
     except DrawerNotDetectedError as e:
-        return None, None, None, None, f"Error: {str(e)}"
-    # Ensure that shrunked_img is defined only after successful detection
+        print(f"Drawer not detected: {e}, using original image.")
+        drawer_detected = False
+        drawer_img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+    # Process the image (either cropped drawer or original)
     t = time.time()
-    shrunked_img = make_square(shrink_bbox(drawer_img, 0.90))
+    if drawer_detected:
+        # For detected drawers: shrink and square
+        shrunked_img = make_square(shrink_bbox(drawer_img, 0.90))
+    else:
+        # For non-drawer images: keep original dimensions
+        shrunked_img = drawer_img  # Already in BGR format from above
     del drawer_img
     gc.collect()
-    print("Image shrinking completed in {:.2f} seconds".format(time.time() - t))
+    print("Image processing completed in {:.2f} seconds".format(time.time() - t))
 
     # ---------------------
-    # 2) Detect the reference box with YOLO
+    # 2) Detect the reference box with YOLO (now works on either cropped or original image)
     # ---------------------
     try:
         t = time.time()
@@ -517,12 +517,9 @@ def predict(
     print("Scaling factor determined: {}".format(scaling_factor))
 
     # ---------------------
-    # 4) Optional boundary dimension checks
+    # 4) Optional boundary dimension checks (now without size limits)
     # ---------------------
     if add_boundary.lower() == "yes":
-        image_height_px, image_width_px = shrunked_img.shape[:2]
-        image_height_in = image_height_px * scaling_factor
-        image_width_in = image_width_px * scaling_factor
         if offset_unit.lower() == "mm":
             if boundary_length < 50:
                 boundary_length = boundary_length * 25.4
@@ -533,12 +530,7 @@ def predict(
         else:
             boundary_length_in = boundary_length
             boundary_width_in = boundary_width
-
-        if boundary_length_in > (image_height_in - 1) or boundary_width_in > (image_width_in - 1):
-            raise BoundaryExceedsError(
-                "Error: The specified boundary dimensions exceed the allowed image dimensions. Please enter smaller values."
-            )
-
+            
     # ---------------------
     # 5) Remove background from the shrunked drawer image (main objects)
     # ---------------------