Update app.py

app.py

@@ -43,7 +43,7 @@ class DrawerNotDetectedError(Exception):
     pass
 
 class ReferenceBoxNotDetectedError(Exception):
-    """Raised when the Reference coin cannot be detected in the image"""
+    """Raised when the reference box cannot be detected in the image"""
     pass
 
 class BoundaryOverlapError(Exception):
@@ -69,10 +69,10 @@ print("YOLOWorld model loaded in {:.2f} seconds".format(time.time() - start_time
 
 print("Loading YOLO reference model...")
 start_time = time.time()
-reference_model_path = os.path.join(CACHE_DIR, "coin_det.pt")
+reference_model_path = os.path.join(CACHE_DIR, "best.pt")
 if not os.path.exists(reference_model_path):
     print("Caching YOLO reference model to", reference_model_path)
-    shutil.copy("coin_det.pt", reference_model_path)
+    shutil.copy("best.pt", reference_model_path)
 reference_detector_global = YOLO(reference_model_path)
 print("YOLO reference model loaded in {:.2f} seconds".format(time.time() - start_time))
 
@@ -120,7 +120,7 @@ def unload_and_reload_models():
     gc.collect()
     new_drawer_detector = YOLOWorld(os.path.join(CACHE_DIR, "yolov8x-worldv2.pt"))
     new_drawer_detector.set_classes(["box"])
-    new_reference_detector = YOLO(os.path.join(CACHE_DIR, "coin_det.pt"))
+    new_reference_detector = YOLO(os.path.join(CACHE_DIR, "best.pt"))
     new_birefnet = AutoModelForImageSegmentation.from_pretrained(
         "zhengpeng7/BiRefNet", trust_remote_code=True, cache_dir=CACHE_DIR
     )
@@ -155,9 +155,9 @@ def yolo_detect(image: Union[str, Path, int, Image.Image, list, tuple, np.ndarra
 
 def detect_reference_square(img: np.ndarray):
     t = time.time()
-    res = reference_detector_global.predict(img, conf=0.3)
+    res = reference_detector_global.predict(img, conf=0.15)
     if not res or len(res) == 0 or len(res[0].boxes) == 0:
-        raise ReferenceBoxNotDetectedError("Reference Coin not detected in the image.")
+        raise ReferenceBoxNotDetectedError("Reference box not detected in the image.")
     print("Reference detection completed in {:.2f} seconds".format(time.time() - t))
     return (
         save_one_box(res[0].cpu().boxes.xyxy, res[0].orig_img, save=False),
@@ -286,51 +286,42 @@ def polygon_to_exterior_coords(poly: Polygon):
         return []
     return list(poly.exterior.coords)
 
-
-def place_finger_cut_adjusted(tool_polygon, points_inch, existing_centers, all_polygons, circle_diameter=1.0, min_gap=0.25, max_attempts=30): #1st best
+def place_finger_cut_adjusted(tool_polygon, points_inch, existing_centers, all_polygons, circle_diameter=1.0, min_gap=0.25, max_attempts=30):
+    import random
     needed_center_distance = circle_diameter + min_gap
     radius = circle_diameter / 2.0
-    import random
-    for _ in range(max_attempts):
-        idx = random.randint(0, len(points_inch) - 1)
-        cx, cy = points_inch[idx]
-
-        # Check if this point is too close to an existing center
-        too_close = any(np.hypot(cx - ex_x, cy - ex_y) < needed_center_distance for ex_x, ex_y in existing_centers)
-        if too_close:
-            continue
-
-        # Create the finger cut circle and try adding it to the tool
-        circle_poly = Point((cx, cy)).buffer(radius, resolution=64)
-        union_poly = tool_polygon.union(circle_poly)
-
-        # Check for overlap and spacing with other tools
-        overlap_with_others = False
-        too_close_to_others = False
-
-        for poly in all_polygons:
-            if poly.equals(tool_polygon):
-                continue  # Skip comparing the tool to itself
-
-            if union_poly.intersects(poly):
-                overlap_with_others = True
-                break
-
-            if circle_poly.buffer(min_gap).intersects(poly):
-                too_close_to_others = True
-                break
-
-        if overlap_with_others or too_close_to_others:
-            continue
-
-        existing_centers.append((cx, cy))
-        return union_poly, (cx, cy)
-
+    attempts = 0
+    indices = list(range(len(points_inch)))
+    random.shuffle(indices)  # Shuffle indices for randomness
+
+    for i in indices:
+        if attempts >= max_attempts:
+            break
+        cx, cy = points_inch[i]
+        # Try small adjustments around the chosen candidate
+        for dx in np.linspace(-0.1, 0.1, 5):
+            for dy in np.linspace(-0.1, 0.1, 5):
+                candidate_center = (cx + dx, cy + dy)
+                # Check distance from already placed centers
+                if any(np.hypot(candidate_center[0] - ex, candidate_center[1] - ey) < needed_center_distance for ex, ey in existing_centers):
+                    continue
+                circle_poly = Point(candidate_center).buffer(radius, resolution=64)
+                union_poly = tool_polygon.union(circle_poly)
+                overlap = False
+                # Check against other tool polygons for overlap or proximity issues
+                for poly in all_polygons:
+                    if union_poly.intersects(poly) or circle_poly.buffer(min_gap).intersects(poly):
+                        overlap = True
+                        break
+                if overlap:
+                    continue
+                # If candidate passes, accept it
+                existing_centers.append(candidate_center)
+                return union_poly, candidate_center
+        attempts += 1
     print("Warning: Could not place a finger cut circle meeting all spacing requirements.")
     return None, None
 
-
-
 # ---------------------
 # DXF Spline and Boundary Functions
 # ---------------------
@@ -353,7 +344,7 @@ def save_dxf_spline(inflated_contours, scaling_factor, height, finger_clearance=
                 points_inch.append(points_inch[0])
             tool_polygon = build_tool_polygon(points_inch)
             if finger_clearance:
-                union_poly, center = place_finger_cut_adjusted(tool_polygon, points_inch, finger_cut_centers, final_polygons_inch, circle_diameter=1.0, min_gap=0.25, max_attempts=100)
+                union_poly, center = place_finger_cut_adjusted(tool_polygon, points_inch, finger_cut_centers, final_polygons_inch, circle_diameter=1.0, min_gap=0.25, max_attempts=30)
                 if union_poly is not None:
                     tool_polygon = union_poly
             exterior_coords = polygon_to_exterior_coords(tool_polygon)
@@ -420,11 +411,13 @@ def add_rectangular_boundary(doc, polygons_inch, boundary_length, boundary_width
     msp.add_lwpolyline(rect_coords, close=True, dxfattribs={"layer": "BOUNDARY"})
     
     text_top = boundary_polygon.bounds[1] + 1
-    too_small = boundary_width_in < inner_width + 2 * clearance_side or boundary_length_in < inner_length + 2 * clearance_tb
-    if too_small:
-        raise BoundaryOverlapError("Error: The specified boundary dimensions are too small and overlap with the inner contours. Please provide larger values.")
-    if annotation_text.strip() and text_top > min_y - 0.75:
-        raise TextOverlapError("Error: The text is too close to the inner contours. Please increase boundary length.")
+    if (annotation_text.strip()==0):
+        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.")
+    else:
+        if text_top > (min_y - 0.75):
+            raise TextOverlapError("Error: The Text is overlapping the inner contours of the object.")
+        
     return boundary_polygon
 
 def draw_polygons_inch(polygons_inch, image_rgb, scaling_factor, image_height, color=(0,0,255), thickness=2):
@@ -508,7 +501,7 @@ def predict(
     try:
         t = time.time()
         reference_obj_img, scaling_box_coords = detect_reference_square(shrunked_img)
-        print("Reference coin detection completed in {:.2f} seconds".format(time.time() - t))
+        print("Reference square detection completed in {:.2f} seconds".format(time.time() - t))
     except ReferenceBoxNotDetectedError as e:
         return None, None, None, None, f"Error: {str(e)}"
 
@@ -518,15 +511,14 @@ def predict(
     t = time.time()
     reference_obj_img = make_square(reference_obj_img)
     reference_square_mask = remove_bg_u2netp(reference_obj_img)
-    reference_square_mask= resize_img(reference_square_mask,(reference_obj_img.shape[1],reference_obj_img.shape[0]))
     print("Reference image processing completed in {:.2f} seconds".format(time.time() - t))
 
     t = time.time()
     try:
         cv2.imwrite("mask.jpg", cv2.cvtColor(reference_obj_img, cv2.COLOR_RGB2GRAY))
         scaling_factor = calculate_scaling_factor(
+            reference_image_path="./Reference_ScalingBox.jpg",
             target_image=reference_square_mask,
-            reference_obj_size_mm=0.955,
             feature_detector="ORB",
         )
     except ZeroDivisionError:
@@ -537,8 +529,8 @@ def predict(
         print(f"Error calculating scaling factor: {e}")
 
     if scaling_factor is None or scaling_factor == 0:
-        scaling_factor = 0.7
-        print("Using default scaling factor of 0.7 due to calculation error")
+        scaling_factor = 1.0
+        print("Using default scaling factor of 1.0 due to calculation error")
     gc.collect()
     print("Scaling factor determined: {}".format(scaling_factor))
 
@@ -572,7 +564,7 @@ def predict(
     objects_mask = remove_bg(shrunked_img)
     processed_size = objects_mask.shape[:2]
 
-    objects_mask = exclude_scaling_box(objects_mask, scaling_box_coords, orig_size, processed_size, expansion_factor=1.2)
+    objects_mask = exclude_scaling_box(objects_mask, scaling_box_coords, orig_size, processed_size, expansion_factor=2)
     objects_mask = resize_img(objects_mask, (shrunked_img.shape[1], shrunked_img.shape[0]))
     del scaling_box_coords
     gc.collect()
@@ -781,8 +773,8 @@ if __name__ == "__main__":
             gr.Textbox(label="Scaling Factor (inches/pixel)")
         ],
         examples=[
-            ["./Test20.jpg", 0.075, "inches", "No", "No", 30.0, 20.0, "MyTool"],
-            ["./Test21.jpg", 0.075, "inches", "Yes", "Yes", 30.0, 20.0, "Tool2"]
+            ["./Test20.jpg", 0.075, "inches", "No", "No", 300.0, 200.0, "MyTool"],
+            ["./Test21.jpg", 0.075, "inches", "Yes", "Yes", 300.0, 200.0, "Tool2"]
         ]
     )
     iface.launch(share=True)