Fixing annotations in database

src/gui/tabs/training_tab.py

@@ -905,9 +905,14 @@ class TrainingTab(QWidget):
             if stats["registered_images"]:
                 message += f" {stats['registered_images']} image(s) had database-backed annotations."
             if stats["missing_records"]:
-                message += (
-                    f" {stats['missing_records']} image(s) had no database entry; empty label files were written."
-                )
+                preserved = stats.get("preserved_existing_labels", 0)
+                if preserved:
+                    message += (
+                        f" {stats['missing_records']} image(s) had no database annotations; "
+                        f"preserved {preserved} existing label file(s) (no overwrite)."
+                    )
+                else:
+                    message += f" {stats['missing_records']} image(s) had no database annotations; empty label files were written."
             split_messages.append(message)
 
         for msg in split_messages:
@@ -929,6 +934,7 @@ class TrainingTab(QWidget):
         processed_images = 0
         registered_images = 0
         missing_records = 0
+        preserved_existing_labels = 0
         total_annotations = 0
 
         for image_file in images_dir.rglob("*"):
@@ -950,6 +956,12 @@ class TrainingTab(QWidget):
             else:
                 missing_records += 1
 
+            # If the database has no entry for this image, do not overwrite an existing label file
+            # with an empty one (preserve any manually created labels on disk).
+            if not found and label_path.exists():
+                preserved_existing_labels += 1
+                continue
+
             annotations_written = 0
             with open(label_path, "w", encoding="utf-8") as handle:
                 for entry in annotation_entries:
@@ -979,6 +991,7 @@ class TrainingTab(QWidget):
             "processed_images": processed_images,
             "registered_images": registered_images,
             "missing_records": missing_records,
+            "preserved_existing_labels": preserved_existing_labels,
             "total_annotations": total_annotations,
         }
 
@@ -1008,6 +1021,10 @@ class TrainingTab(QWidget):
         resolved_image = image_path.resolve()
         candidates: List[str] = []
 
+        # Some DBs store absolute paths in `images.relative_path`.
+        # Include the absolute resolved path as a lookup candidate.
+        candidates.append(resolved_image.as_posix())
+
         for base in (dataset_root, images_dir):
             try:
                 relative = resolved_image.relative_to(base.resolve()).as_posix()
@@ -1032,6 +1049,13 @@ class TrainingTab(QWidget):
             return False, []
 
         annotations = self.db_manager.get_annotations_for_image(image_row["id"]) or []
+
+        # Treat "found" as "has database-backed annotations".
+        # If the image exists in DB but has no annotations yet, we don't want to overwrite
+        # an existing label file on disk with an empty one.
+        if not annotations:
+            return False, []
+
         yolo_entries: List[Dict[str, Any]] = []
 
         for ann in annotations: