Update app.py

app.py

@@ -477,13 +477,17 @@ def predict(
     del objects_mask
     gc.collect()
     print("Mask dilation completed in {:.2f} seconds".format(time.time() - t))
+    # Save the dilated mask for debugging if needed.
     Image.fromarray(dilated_mask).save("./outputs/scaled_mask_new.jpg")
+    # --- Extract outlines (only used for DXF generation) ---
     t = time.time()
     outlines, contours = extract_outlines(dilated_mask)
-    shrunked_img_contours = cv2.drawContours(shrunked_img.copy(), contours, -1, (0, 0, 255), thickness=2)
+    print("Outline extraction completed in {:.2f} seconds".format(time.time() - t))
+    # Instead of drawing the original contours, we now prepare a clean copy of the shrunk image for drawing new contours.
+    output_img = shrunked_img.copy()
     del shrunked_img
     gc.collect()
-    print("Outline extraction completed in {:.2f} seconds".format(time.time() - t))
+    # --- Generate DXF using the extracted contours and apply finger clearance ---
     t = time.time()
     use_finger_clearance = True if finger_clearance.lower() == "yes" else False
     doc, final_polygons_inch = save_dxf_spline(contours, scaling_factor, processed_size[0], finger_clearance=use_finger_clearance)
@@ -495,7 +499,7 @@ def predict(
         boundary_polygon = add_rectangular_boundary(doc, final_polygons_inch, boundary_length, boundary_width, boundary_unit)
         if boundary_polygon is not None:
             final_polygons_inch.append(boundary_polygon)
-    # --- Annotation Text Placement (Bottom-Right) ---
+    # --- Annotation Text Placement (Centered horizontally) ---
     min_x = float("inf")
     min_y = float("inf")
     max_x = -float("inf")
@@ -525,19 +529,20 @@ def predict(
         text_entity.dxf.insert = (text_x, text_y)
     dxf_filepath = os.path.join("./outputs", "out.dxf")
     doc.saveas(dxf_filepath)
-    # --- End Annotation Text Placement ---
-    draw_polygons_inch(final_polygons_inch, shrunked_img_contours, scaling_factor, processed_size[0], color=(0,0,255), thickness=2)
-    outlines_bgr = cv2.cvtColor(outlines, cv2.COLOR_GRAY2BGR)
-    draw_polygons_inch(final_polygons_inch, outlines_bgr, scaling_factor, processed_size[0], color=(0,0,255), thickness=2)
+    # --- Draw only the new contours (final_polygons_inch) on the clean output image ---
+    draw_polygons_inch(final_polygons_inch, output_img, scaling_factor, processed_size[0], color=(0,0,255), thickness=2)
+    # Also prepare an "Outlines" image based on a blank canvas for clarity.
+    new_outlines = np.zeros_like(output_img)
+    draw_polygons_inch(final_polygons_inch, new_outlines, scaling_factor, processed_size[0], color=(0,0,255), thickness=2)
     if annotation_text.strip():
         text_px = int(text_x / scaling_factor)
         text_py = int(processed_size[0] - (text_y / scaling_factor))
-        cv2.putText(shrunked_img_contours, annotation_text.strip(), (text_px, text_py), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2, cv2.LINE_AA)
-        cv2.putText(outlines_bgr, annotation_text.strip(), (text_px, text_py), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2, cv2.LINE_AA)
-    outlines_color = cv2.cvtColor(outlines_bgr, cv2.COLOR_BGR2RGB)
+        cv2.putText(output_img, annotation_text.strip(), (text_px, text_py), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2, cv2.LINE_AA)
+        cv2.putText(new_outlines, annotation_text.strip(), (text_px, text_py), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2, cv2.LINE_AA)
+    outlines_color = cv2.cvtColor(new_outlines, cv2.COLOR_BGR2RGB)
     print("Total prediction time: {:.2f} seconds".format(time.time() - overall_start))
     return (
-        cv2.cvtColor(shrunked_img_contours, cv2.COLOR_BGR2RGB),
+        cv2.cvtColor(output_img, cv2.COLOR_BGR2RGB),
         outlines_color,
         dxf_filepath,
         dilated_mask,