Minor Results.to_sql cleanup (#19081)

Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/engine/results.py

@@ -967,7 +967,7 @@ class Results(SimpleClass):
 
         # Convert results to a list of dictionaries
         data = self.summary(normalize=normalize, decimals=decimals)
-        if not data:
+        if len(data) == 0:
             LOGGER.warning("⚠️ No results to save to SQL. Results dict is empty")
             return
 
@@ -977,31 +977,20 @@ class Results(SimpleClass):
 
         # Create table if it doesn't exist
         columns = (
-            "id INTEGER PRIMARY KEY AUTOINCREMENT, class_name TEXT, confidence REAL, "
-            "box TEXT, masks TEXT, kpts TEXT, obb TEXT"
+            "id INTEGER PRIMARY KEY AUTOINCREMENT, class_name TEXT, confidence REAL, box TEXT, masks TEXT, kpts TEXT"
         )
         cursor.execute(f"CREATE TABLE IF NOT EXISTS {table_name} ({columns})")
 
         # Insert data into the table
-        for i, item in enumerate(data):
-            detect, obb = None, None  # necessary to reinit these variables inside for loop to avoid duplication
-            class_name = item.get("name")
-            box = item.get("box", {})
-            # Serialize the box as JSON for 'detect' and 'obb' based on key presence
-            if all(key in box for key in ["x1", "y1", "x2", "y2"]) and not any(key in box for key in ["x3", "x4"]):
-                detect = json.dumps(box)
-            if all(key in box for key in ["x1", "y1", "x2", "y2", "x3", "x4"]):
-                obb = json.dumps(box)
-
+        for item in data:
             cursor.execute(
-                f"INSERT INTO {table_name} (class_name, confidence, box, masks, kpts, obb) VALUES (?, ?, ?, ?, ?, ?)",
+                f"INSERT INTO {table_name} (class_name, confidence, box, masks, kpts) VALUES (?, ?, ?, ?, ?)",
                 (
-                    class_name,
+                    item.get("name"),
                     item.get("confidence"),
-                    detect,
-                    json.dumps(item.get("segments", {}).get("x", [])),
-                    json.dumps(item.get("keypoints", {}).get("x", [])),
-                    obb,
+                    json.dumps(item.get("box", {})),
+                    json.dumps(item.get("segments", {})),
+                    json.dumps(item.get("keypoints", {})),
                 ),
             )
 

ultralytics/utils/checks.py

@@ -131,7 +131,7 @@ def check_imgsz(imgsz, stride=32, min_dim=1, max_dim=2, floor=0):
         floor (int): Minimum allowed value for image size.
 
     Returns:
-        (List[int]): Updated image size.
+        (List[int] | int): Updated image size.
     """
     # Convert stride to integer if it is a tensor
     stride = int(stride.max() if isinstance(stride, torch.Tensor) else stride)