Major changes in annotation and results showing/storing

src/database/db_manager.py

@@ -40,8 +40,15 @@ class DatabaseManager:
 
         conn = self.get_connection()
         try:
-            # Check if annotations table needs migration
+            # Pre-schema migrations.
+            # These must run BEFORE executing schema.sql because schema.sql may
+            # contain CREATE INDEX statements referencing newly added columns.
+            #
+            # 1) Check if annotations table needs migration (may drop an old table)
             self._migrate_annotations_table(conn)
+            # 2) Ensure images table has the required columns (e.g. 'source')
+            self._migrate_images_table(conn)
+            conn.commit()
 
             # Read schema file and execute
             schema_path = Path(__file__).parent / "schema.sql"
@@ -53,6 +60,19 @@ class DatabaseManager:
         finally:
             conn.close()
 
+    def _migrate_images_table(self, conn: sqlite3.Connection) -> None:
+        """Migrate images table to include the 'source' column if missing."""
+
+        cursor = conn.cursor()
+        cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='images'")
+        if not cursor.fetchone():
+            return
+
+        cursor.execute("PRAGMA table_info(images)")
+        columns = {row[1] for row in cursor.fetchall()}
+        if "source" not in columns:
+            cursor.execute("ALTER TABLE images ADD COLUMN source TEXT")
+
     def _migrate_annotations_table(self, conn: sqlite3.Connection) -> None:
         """
         Migrate annotations table from old schema (class_name) to new schema (class_id).
@@ -85,6 +105,103 @@ class DatabaseManager:
         conn.execute("PRAGMA foreign_keys = ON")  # Enable foreign keys
         return conn
 
+    # ==================== Detection Run Operations ====================
+
+    def upsert_detection_run(
+        self,
+        image_id: int,
+        model_id: int,
+        count: int,
+        metadata: Optional[Dict] = None,
+    ) -> bool:
+        """Insert/update a per-image per-model detection run summary.
+
+        This enables the UI to show runs even when zero detections were produced.
+        """
+
+        conn = self.get_connection()
+        try:
+            cursor = conn.cursor()
+            cursor.execute(
+                """
+                INSERT INTO detection_runs (image_id, model_id, detected_at, count, metadata)
+                VALUES (?, ?, CURRENT_TIMESTAMP, ?, ?)
+                ON CONFLICT(image_id, model_id) DO UPDATE SET
+                    detected_at = CURRENT_TIMESTAMP,
+                    count = excluded.count,
+                    metadata = excluded.metadata
+                """,
+                (
+                    int(image_id),
+                    int(model_id),
+                    int(count),
+                    json.dumps(metadata) if metadata else None,
+                ),
+            )
+            conn.commit()
+            return True
+        finally:
+            conn.close()
+
+    def get_detection_run_summaries(self, limit: int = 500, offset: int = 0) -> List[Dict]:
+        """Return latest detection run summaries grouped by image+model.
+
+        Includes runs with 0 detections.
+        """
+
+        conn = self.get_connection()
+        try:
+            cursor = conn.cursor()
+            cursor.execute(
+                """
+                SELECT
+                    dr.image_id,
+                    dr.model_id,
+                    dr.detected_at,
+                    dr.count,
+                    dr.metadata,
+                    i.relative_path AS image_path,
+                    i.filename AS image_filename,
+                    m.model_name,
+                    m.model_version,
+                    GROUP_CONCAT(DISTINCT d.class_name) AS classes
+                FROM detection_runs dr
+                JOIN images i ON dr.image_id = i.id
+                JOIN models m ON dr.model_id = m.id
+                LEFT JOIN detections d
+                    ON d.image_id = dr.image_id AND d.model_id = dr.model_id
+                GROUP BY dr.image_id, dr.model_id
+                ORDER BY dr.detected_at DESC
+                LIMIT ? OFFSET ?
+                """,
+                (int(limit), int(offset)),
+            )
+
+            rows: List[Dict] = []
+            for row in cursor.fetchall():
+                item = dict(row)
+                if item.get("metadata"):
+                    try:
+                        item["metadata"] = json.loads(item["metadata"])
+                    except Exception:
+                        item["metadata"] = None
+                rows.append(item)
+            return rows
+        finally:
+            conn.close()
+
+    def get_detection_run_total(self) -> int:
+        """Return total number of detection_runs rows."""
+
+        conn = self.get_connection()
+        try:
+            cursor = conn.cursor()
+            cursor.execute("SELECT COUNT(*) AS cnt FROM detection_runs")
+            row = cursor.fetchone()
+            return int(row["cnt"] if row and row["cnt"] is not None else 0)
+        finally:
+            conn.close()
+
     # ==================== Model Operations ====================
 
     def add_model(
@@ -233,6 +350,7 @@ class DatabaseManager:
         height: int,
         captured_at: Optional[datetime] = None,
         checksum: Optional[str] = None,
+        source: Optional[str] = None,
     ) -> int:
         """
         Add a new image to the database.
@@ -253,10 +371,10 @@ class DatabaseManager:
             cursor = conn.cursor()
             cursor.execute(
                 """
-                INSERT INTO images (relative_path, filename, width, height, captured_at, checksum)
-                VALUES (?, ?, ?, ?, ?, ?)
+                INSERT INTO images (relative_path, filename, width, height, captured_at, checksum, source)
+                VALUES (?, ?, ?, ?, ?, ?, ?)
                 """,
-                (relative_path, filename, width, height, captured_at, checksum),
+                (relative_path, filename, width, height, captured_at, checksum, source),
             )
             conn.commit()
             return cursor.lastrowid
@@ -286,6 +404,18 @@ class DatabaseManager:
             return existing["id"]
         return self.add_image(relative_path, filename, width, height)
 
+    def set_image_source(self, image_id: int, source: Optional[str]) -> bool:
+        """Set/update the source marker for an image row."""
+
+        conn = self.get_connection()
+        try:
+            cursor = conn.cursor()
+            cursor.execute("UPDATE images SET source = ? WHERE id = ?", (source, int(image_id)))
+            conn.commit()
+            return cursor.rowcount > 0
+        finally:
+            conn.close()
+
     # ==================== Detection Operations ====================
 
     def add_detection(
@@ -494,6 +624,14 @@ class DatabaseManager:
         conn = self.get_connection()
         try:
             cursor = conn.cursor()
+            # Also clear detection run summaries so the Results tab does not continue
+            # to show historical runs after detections have been wiped.
+            try:
+                cursor.execute("DELETE FROM detection_runs")
+            except sqlite3.OperationalError:
+                # Backwards-compatible: table may not exist on older DB files.
+                pass
+
             cursor.execute("DELETE FROM detections")
             conn.commit()
             return cursor.rowcount
@@ -658,6 +796,153 @@ class DatabaseManager:
 
     # ==================== Annotation Operations ====================
 
+    def get_images_summary(
+        self,
+        name_filter: Optional[str] = None,
+        source_filter: Optional[str] = None,
+        order_by: str = "filename",
+        order_dir: str = "ASC",
+        limit: Optional[int] = None,
+        offset: int = 0,
+    ) -> List[Dict]:
+        """Return all images with annotation counts (including zero).
+
+        This is used by the Annotation tab to populate the image list even when
+        no annotations exist yet.
+
+        Args:
+            name_filter: Optional substring filter applied to filename/relative_path.
+            order_by: One of: 'filename', 'relative_path', 'annotation_count', 'added_at'.
+            order_dir: 'ASC' or 'DESC'.
+            limit: Optional max number of rows.
+            offset: Pagination offset.
+
+        Returns:
+            List of dicts: {id, relative_path, filename, added_at, annotation_count}
+        """
+
+        allowed_order_by = {
+            "filename": "i.filename",
+            "relative_path": "i.relative_path",
+            "annotation_count": "annotation_count",
+            "added_at": "i.added_at",
+        }
+        order_expr = allowed_order_by.get(order_by, "i.filename")
+        dir_norm = str(order_dir).upper().strip()
+        if dir_norm not in {"ASC", "DESC"}:
+            dir_norm = "ASC"
+
+        conn = self.get_connection()
+        try:
+            params: List[Any] = []
+            where_clauses: List[str] = []
+            if name_filter:
+                token = f"%{name_filter}%"
+                where_clauses.append("(i.filename LIKE ? OR i.relative_path LIKE ?)")
+                params.extend([token, token])
+            if source_filter:
+                where_clauses.append("i.source = ?")
+                params.append(source_filter)
+
+            where_sql = ""
+            if where_clauses:
+                where_sql = "WHERE " + " AND ".join(where_clauses)
+
+            limit_sql = ""
+            if limit is not None:
+                limit_sql = " LIMIT ? OFFSET ?"
+                params.extend([int(limit), int(offset)])
+
+            query = f"""
+                SELECT
+                    i.id,
+                    i.relative_path,
+                    i.filename,
+                    i.added_at,
+                    COUNT(a.id) AS annotation_count
+                FROM images i
+                LEFT JOIN annotations a ON a.image_id = i.id
+                {where_sql}
+                GROUP BY i.id
+                ORDER BY {order_expr} {dir_norm}
+                {limit_sql}
+            """
+
+            cursor = conn.cursor()
+            cursor.execute(query, params)
+            return [dict(row) for row in cursor.fetchall()]
+        finally:
+            conn.close()
+
+    def get_annotated_images_summary(
+        self,
+        name_filter: Optional[str] = None,
+        order_by: str = "filename",
+        order_dir: str = "ASC",
+        limit: Optional[int] = None,
+        offset: int = 0,
+    ) -> List[Dict]:
+        """Return images that have at least one manual annotation.
+
+        Args:
+            name_filter: Optional substring filter applied to filename/relative_path.
+            order_by: One of: 'filename', 'relative_path', 'annotation_count', 'added_at'.
+            order_dir: 'ASC' or 'DESC'.
+            limit: Optional max number of rows.
+            offset: Pagination offset.
+
+        Returns:
+            List of dicts: {id, relative_path, filename, added_at, annotation_count}
+        """
+
+        allowed_order_by = {
+            "filename": "i.filename",
+            "relative_path": "i.relative_path",
+            "annotation_count": "annotation_count",
+            "added_at": "i.added_at",
+        }
+        order_expr = allowed_order_by.get(order_by, "i.filename")
+        dir_norm = str(order_dir).upper().strip()
+        if dir_norm not in {"ASC", "DESC"}:
+            dir_norm = "ASC"
+
+        conn = self.get_connection()
+        try:
+            params: List[Any] = []
+            where_sql = ""
+            if name_filter:
+                # Case-insensitive substring search.
+                token = f"%{name_filter}%"
+                where_sql = "WHERE (i.filename LIKE ? OR i.relative_path LIKE ?)"
+                params.extend([token, token])
+
+            limit_sql = ""
+            if limit is not None:
+                limit_sql = " LIMIT ? OFFSET ?"
+                params.extend([int(limit), int(offset)])
+
+            query = f"""
+                SELECT
+                    i.id,
+                    i.relative_path,
+                    i.filename,
+                    i.added_at,
+                    COUNT(a.id) AS annotation_count
+                FROM images i
+                JOIN annotations a ON a.image_id = i.id
+                {where_sql}
+                GROUP BY i.id
+                HAVING annotation_count > 0
+                ORDER BY {order_expr} {dir_norm}
+                {limit_sql}
+            """
+
+            cursor = conn.cursor()
+            cursor.execute(query, params)
+            return [dict(row) for row in cursor.fetchall()]
+        finally:
+            conn.close()
+
     def add_annotation(
         self,
         image_id: int,
@@ -763,6 +1048,27 @@ class DatabaseManager:
         finally:
             conn.close()
 
+    def delete_annotations_for_image(self, image_id: int) -> int:
+        """Delete ALL annotations for a specific image.
+
+        This is primarily used for import/overwrite workflows.
+
+        Args:
+            image_id: ID of the image whose annotations should be deleted.
+
+        Returns:
+            Number of rows deleted.
+        """
+
+        conn = self.get_connection()
+        try:
+            cursor = conn.cursor()
+            cursor.execute("DELETE FROM annotations WHERE image_id = ?", (int(image_id),))
+            conn.commit()
+            return int(cursor.rowcount or 0)
+        finally:
+            conn.close()
+
     # ==================== Object Class Operations ====================
 
     def get_object_classes(self) -> List[Dict]:

src/database/schema.sql

@@ -7,7 +7,7 @@ CREATE TABLE IF NOT EXISTS models (
     model_name TEXT NOT NULL,
     model_version TEXT NOT NULL,
     model_path TEXT NOT NULL,
-    base_model TEXT NOT NULL DEFAULT 'yolov8s.pt',
+    base_model TEXT NOT NULL DEFAULT 'yolo11s.pt',
     created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
     training_params TEXT,  -- JSON string of training parameters
     metrics TEXT,          -- JSON string of validation metrics
@@ -23,7 +23,8 @@ CREATE TABLE IF NOT EXISTS images (
     height INTEGER,
     captured_at TIMESTAMP,
     added_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-    checksum TEXT
+    checksum TEXT,
+    source TEXT
 );
 
 -- Detections table: stores detection results
@@ -44,6 +45,19 @@ CREATE TABLE IF NOT EXISTS detections (
     FOREIGN KEY (model_id) REFERENCES models (id) ON DELETE CASCADE
 );
 
+-- Detection runs table: stores per-image per-model run summaries (including 0 detections)
+CREATE TABLE IF NOT EXISTS detection_runs (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    image_id INTEGER NOT NULL,
+    model_id INTEGER NOT NULL,
+    detected_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+    count INTEGER NOT NULL DEFAULT 0,
+    metadata TEXT,
+    UNIQUE(image_id, model_id),
+    FOREIGN KEY (image_id) REFERENCES images (id) ON DELETE CASCADE,
+    FOREIGN KEY (model_id) REFERENCES models (id) ON DELETE CASCADE
+);
+
 -- Object classes table: stores annotation class definitions with colors
 CREATE TABLE IF NOT EXISTS object_classes (
     id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -80,9 +94,13 @@ CREATE INDEX IF NOT EXISTS idx_detections_model_id ON detections(model_id);
 CREATE INDEX IF NOT EXISTS idx_detections_class_name ON detections(class_name);
 CREATE INDEX IF NOT EXISTS idx_detections_detected_at ON detections(detected_at);
 CREATE INDEX IF NOT EXISTS idx_detections_confidence ON detections(confidence);
+CREATE INDEX IF NOT EXISTS idx_detection_runs_image_id ON detection_runs(image_id);
+CREATE INDEX IF NOT EXISTS idx_detection_runs_model_id ON detection_runs(model_id);
+CREATE INDEX IF NOT EXISTS idx_detection_runs_detected_at ON detection_runs(detected_at);
 CREATE INDEX IF NOT EXISTS idx_images_relative_path ON images(relative_path);
 CREATE INDEX IF NOT EXISTS idx_images_added_at ON images(added_at);
+CREATE INDEX IF NOT EXISTS idx_images_source ON images(source);
 CREATE INDEX IF NOT EXISTS idx_annotations_image_id ON annotations(image_id);
 CREATE INDEX IF NOT EXISTS idx_annotations_class_id ON annotations(class_id);
 CREATE INDEX IF NOT EXISTS idx_models_created_at ON models(created_at);
-CREATE INDEX IF NOT EXISTS idx_object_classes_class_name ON object_classes(class_name);
+CREATE INDEX IF NOT EXISTS idx_object_classes_class_name ON object_classes(class_name);

src/gui/main_window.py

@@ -199,6 +199,10 @@ class MainWindow(QMainWindow):
                 self.training_tab.refresh()
             if hasattr(self, "results_tab"):
                 self.results_tab.refresh()
+            if hasattr(self, "annotation_tab"):
+                self.annotation_tab.refresh()
+            if hasattr(self, "validation_tab"):
+                self.validation_tab.refresh()
         except Exception as e:
             logger.error(f"Error applying settings: {e}")
 
@@ -215,6 +219,14 @@ class MainWindow(QMainWindow):
         logger.debug(f"Switched to tab: {tab_name}")
         self._update_status(f"Viewing: {tab_name}")
 
+        # Ensure the Annotation tab always shows up-to-date DB-backed lists.
+        try:
+            current_widget = self.tab_widget.widget(index)
+            if hasattr(self, "annotation_tab") and current_widget is self.annotation_tab:
+                self.annotation_tab.refresh()
+        except Exception as exc:
+            logger.debug(f"Failed to refresh annotation tab on selection: {exc}")
+
     def _show_database_stats(self):
         """Show database statistics dialog."""
         try:
@@ -527,6 +539,11 @@ class MainWindow(QMainWindow):
             if hasattr(self, "training_tab"):
                 self.training_tab.shutdown()
             if hasattr(self, "annotation_tab"):
+                # Best-effort refresh so DB-backed UI state is consistent at shutdown.
+                try:
+                    self.annotation_tab.refresh()
+                except Exception:
+                    pass
                 self.annotation_tab.save_state()
 
             logger.info("Application closing")

src/gui/tabs/annotation_tab.py

@@ -13,6 +13,11 @@ from PySide6.QtWidgets import (
     QFileDialog,
     QMessageBox,
     QSplitter,
+    QLineEdit,
+    QTableWidget,
+    QTableWidgetItem,
+    QHeaderView,
+    QAbstractItemView,
 )
 from PySide6.QtCore import Qt, QSettings
 from pathlib import Path
@@ -50,6 +55,32 @@ class AnnotationTab(QWidget):
         self.main_splitter = QSplitter(Qt.Horizontal)
         self.main_splitter.setHandleWidth(10)
 
+        # { Left-most pane: annotated images list
+        annotated_group = QGroupBox("Annotated Images")
+        annotated_layout = QVBoxLayout()
+
+        filter_row = QHBoxLayout()
+        filter_row.addWidget(QLabel("Filter:"))
+        self.annotated_filter_edit = QLineEdit()
+        self.annotated_filter_edit.setPlaceholderText("Type to filter by image name…")
+        self.annotated_filter_edit.textChanged.connect(self._refresh_annotated_images_list)
+        filter_row.addWidget(self.annotated_filter_edit, 1)
+        annotated_layout.addLayout(filter_row)
+
+        self.annotated_images_table = QTableWidget(0, 2)
+        self.annotated_images_table.setHorizontalHeaderLabels(["Image", "Annotations"])
+        self.annotated_images_table.horizontalHeader().setSectionResizeMode(0, QHeaderView.Stretch)
+        self.annotated_images_table.horizontalHeader().setSectionResizeMode(1, QHeaderView.ResizeToContents)
+        self.annotated_images_table.setSelectionBehavior(QAbstractItemView.SelectRows)
+        self.annotated_images_table.setSelectionMode(QAbstractItemView.SingleSelection)
+        self.annotated_images_table.setEditTriggers(QAbstractItemView.NoEditTriggers)
+        self.annotated_images_table.setSortingEnabled(True)
+        self.annotated_images_table.itemSelectionChanged.connect(self._on_annotated_image_selected)
+        annotated_layout.addWidget(self.annotated_images_table, 1)
+
+        annotated_group.setLayout(annotated_layout)
+        # }
+
         # { Left splitter for image display and zoom info
         self.left_splitter = QSplitter(Qt.Vertical)
         self.left_splitter.setHandleWidth(10)
@@ -104,11 +135,27 @@ class AnnotationTab(QWidget):
         load_group = QGroupBox("Image Loading")
         load_layout = QVBoxLayout()
 
-        # Load image button
+        # Buttons row
         button_layout = QHBoxLayout()
         self.load_image_btn = QPushButton("Load Image")
         self.load_image_btn.clicked.connect(self._load_image)
         button_layout.addWidget(self.load_image_btn)
+
+        self.import_images_btn = QPushButton("Import Images")
+        self.import_images_btn.setToolTip(
+            "Import one or more images into the database.\n" "Images already present in the DB are skipped."
+        )
+        self.import_images_btn.clicked.connect(self._import_images)
+        button_layout.addWidget(self.import_images_btn)
+
+        self.import_annotations_btn = QPushButton("Import Annotations")
+        self.import_annotations_btn.setToolTip(
+            "Import YOLO .txt annotation files and register them with their corresponding images.\n"
+            "Existing annotations for those images will be overwritten."
+        )
+        self.import_annotations_btn.clicked.connect(self._import_annotations)
+        button_layout.addWidget(self.import_annotations_btn)
+
         button_layout.addStretch()
         load_layout.addLayout(button_layout)
 
@@ -120,12 +167,13 @@ class AnnotationTab(QWidget):
         self.right_splitter.addWidget(load_group)
         # }
 
-        # Add both splitters to the main horizontal splitter
+        # Add list + both splitters to the main horizontal splitter
+        self.main_splitter.addWidget(annotated_group)
         self.main_splitter.addWidget(self.left_splitter)
         self.main_splitter.addWidget(self.right_splitter)
 
-        # Set initial sizes: 75% for left (image), 25% for right (controls)
-        self.main_splitter.setSizes([750, 250])
+        # Set initial sizes: list (left), canvas (middle), controls (right)
+        self.main_splitter.setSizes([320, 650, 280])
 
         layout.addWidget(self.main_splitter)
         self.setLayout(layout)
@@ -133,6 +181,375 @@ class AnnotationTab(QWidget):
         # Restore splitter positions from settings
         self._restore_state()
 
+        # Populate list on startup.
+        self._refresh_annotated_images_list()
+
+    def _import_images(self) -> None:
+        """Import one or more images into the database and refresh the list."""
+
+        settings = QSettings("microscopy_app", "object_detection")
+        last_dir = settings.value("annotation_tab/last_image_import_directory", None)
+
+        repo_root = (self.config_manager.get_image_repository_path() or "").strip()
+        if last_dir and Path(str(last_dir)).exists():
+            start_dir = str(last_dir)
+        elif repo_root and Path(repo_root).exists():
+            start_dir = repo_root
+        else:
+            start_dir = str(Path.home())
+
+        # Build filter string for supported extensions
+        patterns = " ".join(f"*{ext}" for ext in Image.SUPPORTED_EXTENSIONS)
+        file_paths, _ = QFileDialog.getOpenFileNames(
+            self,
+            "Select Image File(s)",
+            start_dir,
+            f"Images ({patterns})",
+        )
+
+        if not file_paths:
+            return
+
+        try:
+            settings.setValue("annotation_tab/last_image_import_directory", str(Path(file_paths[0]).parent))
+            # Keep compatibility with the existing image resolver fallback (it checks last_directory).
+            settings.setValue("annotation_tab/last_directory", str(Path(file_paths[0]).parent))
+        except Exception:
+            pass
+
+        imported = 0
+        tagged_existing = 0
+        skipped = 0
+        errors: list[str] = []
+
+        for fp in file_paths:
+            try:
+                img_path = Path(fp)
+                img = Image(str(img_path))
+                relative_path = self._compute_relative_path_for_repo(img_path)
+
+                # Skip if already present
+                existing = self.db_manager.get_image_by_path(relative_path)
+                if existing:
+                    # If the image already exists (e.g. created earlier by other workflows),
+                    # tag it as being managed by the Annotation tab so it becomes visible
+                    # in the left list.
+                    try:
+                        self.db_manager.set_image_source(int(existing["id"]), "annotation_tab")
+                        tagged_existing += 1
+                    except Exception:
+                        # If tagging fails, fall back to treating as skipped.
+                        skipped += 1
+                    continue
+
+                image_id = self.db_manager.add_image(
+                    relative_path,
+                    img_path.name,
+                    img.width,
+                    img.height,
+                    source="annotation_tab",
+                )
+                try:
+                    # In case the DB row was created by an older schema/migration path.
+                    self.db_manager.set_image_source(image_id, "annotation_tab")
+                except Exception:
+                    pass
+                imported += 1
+            except ImageLoadError as exc:
+                skipped += 1
+                errors.append(f"Failed to load image {fp}: {exc}")
+            except Exception as exc:
+                skipped += 1
+                errors.append(f"Failed to import image {fp}: {exc}")
+
+        self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
+        msg = (
+            f"Imported: {imported}\n"
+            f"Already in DB (tagged for Annotation tab): {tagged_existing}\n"
+            f"Skipped (errors): {skipped}"
+        )
+        if errors:
+            details = "\n".join(errors[:25])
+            if len(errors) > 25:
+                details += f"\n... and {len(errors) - 25} more"
+            msg += "\n\nDetails:\n" + details
+        QMessageBox.information(self, "Import Images", msg)
+
+    # ==================== Import annotations (YOLO .txt) ====================
+
+    def _import_annotations(self) -> None:
+        """Import YOLO segmentation/bbox annotations from one or more .txt files."""
+
+        settings = QSettings("microscopy_app", "object_detection")
+        last_dir = settings.value("annotation_tab/last_annotation_directory", None)
+
+        # Default start dir: repo root if set, otherwise last used, otherwise home.
+        repo_root = (self.config_manager.get_image_repository_path() or "").strip()
+        if last_dir and Path(str(last_dir)).exists():
+            start_dir = str(last_dir)
+        elif repo_root and Path(repo_root).exists():
+            start_dir = repo_root
+        else:
+            start_dir = str(Path.home())
+
+        file_paths, _ = QFileDialog.getOpenFileNames(
+            self,
+            "Select YOLO Annotation File(s)",
+            start_dir,
+            "YOLO annotations (*.txt)",
+        )
+
+        if not file_paths:
+            return
+
+        # Persist last annotation directory for the next import.
+        try:
+            settings.setValue("annotation_tab/last_annotation_directory", str(Path(file_paths[0]).parent))
+        except Exception:
+            pass
+
+        imported_images = 0
+        imported_annotations = 0
+        overwritten_images = 0
+        skipped = 0
+        errors: list[str] = []
+
+        for label_file in file_paths:
+            label_path = Path(label_file)
+            try:
+                image_path = self._infer_corresponding_image_path(label_path)
+                if not image_path:
+                    skipped += 1
+                    errors.append(f"Image not found for label file: {label_path}")
+                    continue
+
+                # Load image to obtain width/height for DB entry.
+                img = Image(str(image_path))
+
+                # Store in DB using a repo-relative path if possible.
+                relative_path = self._compute_relative_path_for_repo(image_path)
+                image_id = self.db_manager.get_or_create_image(relative_path, image_path.name, img.width, img.height)
+                try:
+                    self.db_manager.set_image_source(image_id, "annotation_tab")
+                except Exception:
+                    pass
+
+                # Overwrite existing annotations for this image.
+                try:
+                    deleted = self.db_manager.delete_annotations_for_image(image_id)
+                except AttributeError:
+                    # Safety fallback if older DBManager is used.
+                    deleted = 0
+                if deleted > 0:
+                    overwritten_images += 1
+
+                # Parse YOLO lines and insert as annotations.
+                parsed = self._parse_yolo_annotation_file(label_path)
+                if not parsed:
+                    # Empty/invalid label file: treat as "clear" operation (already deleted above)
+                    imported_images += 1
+                    continue
+
+                db_classes = self.db_manager.get_object_classes() or []
+                classes_by_index = {idx: row for idx, row in enumerate(db_classes)}
+
+                for class_index, bbox, poly in parsed:
+                    class_row = classes_by_index.get(int(class_index))
+                    if not class_row:
+                        skipped += 1
+                        errors.append(
+                            f"Unknown class index {class_index} in {label_path.name}. "
+                            "Create object classes in the UI first (class index is based on DB ordering)."
+                        )
+                        continue
+
+                    ann_id = self.db_manager.add_annotation(
+                        image_id=image_id,
+                        class_id=int(class_row["id"]),
+                        bbox=bbox,
+                        annotator="import",
+                        segmentation_mask=poly,
+                        verified=False,
+                    )
+                    if ann_id:
+                        imported_annotations += 1
+
+                imported_images += 1
+
+                # If we imported for the currently open image, reload.
+                if self.current_image_id and int(self.current_image_id) == int(image_id):
+                    self._load_annotations_for_current_image()
+
+            except ImageLoadError as exc:
+                skipped += 1
+                errors.append(f"Failed to load image for {label_path.name}: {exc}")
+            except Exception as exc:
+                skipped += 1
+                errors.append(f"Import failed for {label_path.name}: {exc}")
+
+        # Refresh annotated images list.
+        self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
+        summary = (
+            f"Imported files: {len(file_paths)}\n"
+            f"Images processed: {imported_images}\n"
+            f"Annotations inserted: {imported_annotations}\n"
+            f"Images overwritten (had existing annotations): {overwritten_images}\n"
+            f"Skipped: {skipped}"
+        )
+        if errors:
+            # Cap error details to avoid huge dialogs.
+            details = "\n".join(errors[:25])
+            if len(errors) > 25:
+                details += f"\n... and {len(errors) - 25} more"
+            summary += "\n\nDetails:\n" + details
+
+        QMessageBox.information(self, "Import Annotations", summary)
+
+    def _infer_corresponding_image_path(self, label_path: Path) -> Path | None:
+        """Infer image path from YOLO label file path.
+
+        Requirement: image(s) live in an `images/` folder located in the label file's parent directory.
+        Example:
+            /dataset/train/labels/img123.txt -> /dataset/train/images/img123.(any supported ext)
+        """
+
+        parent = label_path.parent
+        images_dir = parent.parent / "images"
+        stem = label_path.stem
+
+        # 1) Direct stem match in images dir (any supported extension)
+        for ext in Image.SUPPORTED_EXTENSIONS:
+            candidate = images_dir / f"{stem}{ext}"
+            if candidate.exists() and candidate.is_file():
+                return candidate
+
+        # 2) Fallback: repository-root search by filename
+        repo_root = (self.config_manager.get_image_repository_path() or "").strip()
+        if repo_root:
+            root = Path(repo_root).expanduser()
+            try:
+                if root.exists():
+                    for ext in Image.SUPPORTED_EXTENSIONS:
+                        filename = f"{stem}{ext}"
+                        for match in root.rglob(filename):
+                            if match.is_file():
+                                return match.resolve()
+            except Exception:
+                pass
+
+        return None
+
+    def _compute_relative_path_for_repo(self, image_path: Path) -> str:
+        """Compute a stable `relative_path` suitable for DB storage.
+
+        Policy:
+        - If an image repository root is configured and the image is under it, store a repo-relative path.
+        - Otherwise, store an absolute resolved path so the image can be reopened later.
+        """
+
+        repo_root = (self.config_manager.get_image_repository_path() or "").strip()
+        try:
+            if repo_root:
+                repo_root_path = Path(repo_root).expanduser().resolve()
+                img_resolved = image_path.expanduser().resolve()
+                if img_resolved.is_relative_to(repo_root_path):
+                    return img_resolved.relative_to(repo_root_path).as_posix()
+        except Exception:
+            pass
+        try:
+            return str(image_path.expanduser().resolve())
+        except Exception:
+            return str(image_path)
+
+    def _parse_yolo_annotation_file(
+        self, label_path: Path
+    ) -> list[tuple[int, tuple[float, float, float, float], list[list[float]] | None]]:
+        """Parse a YOLO .txt label file.
+
+        Supports:
+          - YOLO segmentation polygon format: "class x1 y1 x2 y2 ..." (normalized)
+          - YOLO bbox format: "class x_center y_center width height" (normalized)
+
+        Returns:
+            List of (class_index, bbox_xyxy_norm, segmentation_mask_db)
+            Where segmentation_mask_db is [[y_norm, x_norm], ...] or None.
+        """
+
+        out: list[tuple[int, tuple[float, float, float, float], list[list[float]] | None]] = []
+        try:
+            raw = label_path.read_text(encoding="utf-8").splitlines()
+        except OSError as exc:
+            logger.error(f"Failed to read label file {label_path}: {exc}")
+            return out
+
+        for line in raw:
+            stripped = line.strip()
+            if not stripped:
+                continue
+            parts = stripped.split()
+            if len(parts) < 5:
+                # not enough for bbox
+                continue
+
+            try:
+                class_idx = int(float(parts[0]))
+                coords = [float(x) for x in parts[1:]]
+            except Exception:
+                continue
+
+            # Segmentation polygon format (>= 6 values)
+            if len(coords) >= 6:
+                # bbox is not explicitly present in this format in our importer; compute from polygon.
+                xs = coords[0::2]
+                ys = coords[1::2]
+                if not xs or not ys:
+                    continue
+                x_min, x_max = min(xs), max(xs)
+                y_min, y_max = min(ys), max(ys)
+                bbox = (
+                    self._clamp01(x_min),
+                    self._clamp01(y_min),
+                    self._clamp01(x_max),
+                    self._clamp01(y_max),
+                )
+
+                # Convert to DB polyline convention: [[y_norm, x_norm], ...]
+                poly: list[list[float]] = []
+                for x, y in zip(xs, ys):
+                    poly.append([self._clamp01(float(y)), self._clamp01(float(x))])
+                # Ensure closure for consistency (optional)
+                if poly and poly[0] != poly[-1]:
+                    poly.append(list(poly[0]))
+                out.append((class_idx, bbox, poly))
+                continue
+
+            # bbox format: xc yc w h
+            if len(coords) >= 4:
+                xc, yc, w, h = coords[:4]
+                x_min = xc - w / 2.0
+                y_min = yc - h / 2.0
+                x_max = xc + w / 2.0
+                y_max = yc + h / 2.0
+                bbox = (
+                    self._clamp01(float(x_min)),
+                    self._clamp01(float(y_min)),
+                    self._clamp01(float(x_max)),
+                    self._clamp01(float(y_max)),
+                )
+                out.append((class_idx, bbox, None))
+
+        return out
+
+    @staticmethod
+    def _clamp01(value: float) -> float:
+        if value < 0.0:
+            return 0.0
+        if value > 1.0:
+            return 1.0
+        return float(value)
+
     def _load_image(self):
         """Load and display an image file."""
         # Get last opened directory from QSettings
@@ -166,13 +583,32 @@ class AnnotationTab(QWidget):
             settings.setValue("annotation_tab/last_directory", str(Path(file_path).parent))
 
             # Get or create image in database
-            relative_path = str(Path(file_path).name)  # Simplified for now
+            repo_root = self.config_manager.get_image_repository_path()
+            relative_path: str
+            try:
+                if repo_root:
+                    repo_root_path = Path(repo_root).expanduser().resolve()
+                    file_resolved = Path(file_path).expanduser().resolve()
+                    if file_resolved.is_relative_to(repo_root_path):
+                        relative_path = file_resolved.relative_to(repo_root_path).as_posix()
+                    else:
+                        # Fallback: store filename only to avoid leaking absolute paths.
+                        relative_path = file_resolved.name
+                else:
+                    relative_path = str(Path(file_path).name)
+            except Exception:
+                relative_path = str(Path(file_path).name)
             self.current_image_id = self.db_manager.get_or_create_image(
                 relative_path,
                 Path(file_path).name,
                 self.current_image.width,
                 self.current_image.height,
             )
+            # Mark as managed by Annotation tab so it appears in the left list.
+            try:
+                self.db_manager.set_image_source(int(self.current_image_id), "annotation_tab")
+            except Exception:
+                pass
 
             # Display image using the AnnotationCanvasWidget
             self.annotation_canvas.load_image(self.current_image)
@@ -180,6 +616,9 @@ class AnnotationTab(QWidget):
             # Load and display any existing annotations for this image
             self._load_annotations_for_current_image()
 
+            # Update annotated images list (newly annotated image added/selected).
+            self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
             # Update info label
             self._update_image_info()
 
@@ -275,6 +714,9 @@ class AnnotationTab(QWidget):
             # Reload annotations from DB and redraw (respecting current class filter)
             self._load_annotations_for_current_image()
 
+            # Update list counts.
+            self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
         except Exception as e:
             logger.error(f"Failed to save annotation: {e}")
             QMessageBox.critical(self, "Error", f"Failed to save annotation:\n{str(e)}")
@@ -405,6 +847,9 @@ class AnnotationTab(QWidget):
             self.annotation_tools.set_has_selected_annotation(False)
             self._load_annotations_for_current_image()
 
+            # Update list counts.
+            self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
         except Exception as e:
             logger.error(f"Failed to delete annotations: {e}")
             QMessageBox.critical(
@@ -521,4 +966,173 @@ class AnnotationTab(QWidget):
 
     def refresh(self):
         """Refresh the tab."""
-        pass
+        self._refresh_annotated_images_list(select_image_id=self.current_image_id)
+
+    # ==================== Annotated images list ====================
+
+    def _refresh_annotated_images_list(self, select_image_id: int | None = None) -> None:
+        """Reload annotated-images list from the database."""
+        if not hasattr(self, "annotated_images_table"):
+            return
+
+        # Preserve selection if possible
+        desired_id = select_image_id if select_image_id is not None else self.current_image_id
+
+        name_filter = ""
+        if hasattr(self, "annotated_filter_edit"):
+            name_filter = self.annotated_filter_edit.text().strip()
+
+        try:
+            rows = self.db_manager.get_images_summary(name_filter=name_filter, source_filter="annotation_tab")
+        except Exception as exc:
+            logger.error(f"Failed to load images summary: {exc}")
+            rows = []
+
+        sorting_enabled = self.annotated_images_table.isSortingEnabled()
+        self.annotated_images_table.setSortingEnabled(False)
+        self.annotated_images_table.blockSignals(True)
+        try:
+            self.annotated_images_table.setRowCount(len(rows))
+            for r, entry in enumerate(rows):
+                image_name = str(entry.get("filename") or "")
+                count = int(entry.get("annotation_count") or 0)
+                rel_path = str(entry.get("relative_path") or "")
+
+                name_item = QTableWidgetItem(image_name)
+                # Tooltip shows full path of the image (best-effort: repository_root + relative_path)
+                full_path = rel_path
+                repo_root = self.config_manager.get_image_repository_path()
+                if repo_root and rel_path and not Path(rel_path).is_absolute():
+                    try:
+                        full_path = str((Path(repo_root) / rel_path).resolve())
+                    except Exception:
+                        full_path = str(Path(repo_root) / rel_path)
+                name_item.setToolTip(full_path)
+                name_item.setData(Qt.UserRole, int(entry.get("id")))
+                name_item.setData(Qt.UserRole + 1, rel_path)
+
+                count_item = QTableWidgetItem()
+                # Use EditRole to ensure numeric sorting.
+                count_item.setData(Qt.EditRole, count)
+                count_item.setData(Qt.UserRole, int(entry.get("id")))
+                count_item.setData(Qt.UserRole + 1, rel_path)
+
+                self.annotated_images_table.setItem(r, 0, name_item)
+                self.annotated_images_table.setItem(r, 1, count_item)
+
+            # Re-select desired row
+            if desired_id is not None:
+                for r in range(self.annotated_images_table.rowCount()):
+                    item = self.annotated_images_table.item(r, 0)
+                    if item and item.data(Qt.UserRole) == desired_id:
+                        self.annotated_images_table.selectRow(r)
+                        break
+        finally:
+            self.annotated_images_table.blockSignals(False)
+            self.annotated_images_table.setSortingEnabled(sorting_enabled)
+
+    def _on_annotated_image_selected(self) -> None:
+        """When user clicks an item in the list, load that image in the annotation canvas."""
+        selected = self.annotated_images_table.selectedItems()
+        if not selected:
+            return
+
+        # Row selection -> take the first column item
+        row = self.annotated_images_table.currentRow()
+        item = self.annotated_images_table.item(row, 0)
+        if not item:
+            return
+
+        image_id = item.data(Qt.UserRole)
+        rel_path = item.data(Qt.UserRole + 1) or ""
+        if not image_id:
+            return
+
+        image_path = self._resolve_image_path_for_relative_path(rel_path)
+        if not image_path:
+            QMessageBox.warning(
+                self,
+                "Image Not Found",
+                "Unable to locate image on disk for:\n"
+                f"{rel_path}\n\n"
+                "Tip: set Settings → Image repository path to the folder containing your images.",
+            )
+            return
+
+        try:
+            self.current_image = Image(image_path)
+            self.current_image_path = image_path
+            self.current_image_id = int(image_id)
+            self.annotation_canvas.load_image(self.current_image)
+            self._load_annotations_for_current_image()
+            self._update_image_info()
+        except ImageLoadError as exc:
+            logger.error(f"Failed to load image '{image_path}': {exc}")
+            QMessageBox.critical(self, "Error Loading Image", f"Failed to load image:\n{exc}")
+        except Exception as exc:
+            logger.error(f"Unexpected error loading image '{image_path}': {exc}")
+            QMessageBox.critical(self, "Error", f"Unexpected error:\n{exc}")
+
+    def _resolve_image_path_for_relative_path(self, relative_path: str) -> str | None:
+        """Best-effort conversion from a DB relative_path to an on-disk file path."""
+
+        rel = (relative_path or "").strip()
+        if not rel:
+            return None
+
+        candidates: list[Path] = []
+
+        # 1) Repository root + relative
+        repo_root = (self.config_manager.get_image_repository_path() or "").strip()
+        if repo_root:
+            candidates.append(Path(repo_root) / rel)
+
+        # 2) If the DB path is absolute, try it directly.
+        candidates.append(Path(rel))
+
+        # 3) Try the directory of the currently loaded image (helps when DB stores only filenames)
+        if self.current_image_path:
+            try:
+                candidates.append(Path(self.current_image_path).expanduser().resolve().parent / Path(rel).name)
+            except Exception:
+                pass
+
+        # 4) Try the last directory used by the annotation file picker
+        try:
+            settings = QSettings("microscopy_app", "object_detection")
+            last_dir = settings.value("annotation_tab/last_directory", None)
+            if last_dir:
+                candidates.append(Path(str(last_dir)) / Path(rel).name)
+        except Exception:
+            pass
+
+        # 4b) Try the last directory used by the image import picker
+        try:
+            settings = QSettings("microscopy_app", "object_detection")
+            last_import_dir = settings.value("annotation_tab/last_image_import_directory", None)
+            if last_import_dir:
+                candidates.append(Path(str(last_import_dir)) / Path(rel).name)
+        except Exception:
+            pass
+
+        for p in candidates:
+            try:
+                expanded = p.expanduser()
+                if expanded.exists() and expanded.is_file():
+                    return str(expanded.resolve())
+            except Exception:
+                continue
+
+        # 5) Fallback: search by filename within repository root.
+        filename = Path(rel).name
+        if repo_root and filename:
+            root = Path(repo_root).expanduser()
+            try:
+                if root.exists():
+                    for match in root.rglob(filename):
+                        if match.is_file():
+                            return str(match.resolve())
+            except Exception as exc:
+                logger.debug(f"Search for {filename} under {root} failed: {exc}")
+
+        return None

src/gui/tabs/results_tab.py

@@ -40,6 +40,12 @@ class ResultsTab(QWidget):
         self.db_manager = db_manager
         self.config_manager = config_manager
 
+        # Pagination
+        self.page_size = 200
+        self.current_page = 0  # 0-based
+        self.total_runs = 0
+        self.total_pages = 0
+
         self.detection_summary: List[Dict] = []
         self.current_selection: Optional[Dict] = None
         self.current_image: Optional[Image] = None
@@ -66,6 +72,20 @@ class ResultsTab(QWidget):
         self.refresh_btn.clicked.connect(self.refresh)
         controls_layout.addWidget(self.refresh_btn)
 
+        self.prev_page_btn = QPushButton("◀ Prev")
+        self.prev_page_btn.setToolTip("Previous page")
+        self.prev_page_btn.clicked.connect(self._prev_page)
+        controls_layout.addWidget(self.prev_page_btn)
+
+        self.next_page_btn = QPushButton("Next ▶")
+        self.next_page_btn.setToolTip("Next page")
+        self.next_page_btn.clicked.connect(self._next_page)
+        controls_layout.addWidget(self.next_page_btn)
+
+        self.page_label = QLabel("Page 1/1")
+        self.page_label.setMinimumWidth(100)
+        controls_layout.addWidget(self.page_label)
+
         self.delete_all_btn = QPushButton("Delete All Detections")
         self.delete_all_btn.setToolTip(
             "Permanently delete ALL detections from the database.\n" "This cannot be undone."
@@ -183,6 +203,8 @@ class ResultsTab(QWidget):
 
     def refresh(self):
         """Refresh the detection list and preview."""
+        # Reset to first page on refresh.
+        self.current_page = 0
         self._load_detection_summary()
         self._populate_results_table()
         self.current_selection = None
@@ -193,57 +215,135 @@ class ResultsTab(QWidget):
         if hasattr(self, "export_labels_btn"):
             self.export_labels_btn.setEnabled(False)
 
+        self._update_pagination_controls()
+
+    def _prev_page(self):
+        """Go to previous results page."""
+        if self.current_page <= 0:
+            return
+        self.current_page -= 1
+        self._load_detection_summary()
+        self._populate_results_table()
+        self._update_pagination_controls()
+
+    def _next_page(self):
+        """Go to next results page."""
+        if self.total_pages and self.current_page >= (self.total_pages - 1):
+            return
+        self.current_page += 1
+        self._load_detection_summary()
+        self._populate_results_table()
+        self._update_pagination_controls()
+
+    def _update_pagination_controls(self):
+        """Update pagination label/button enabled state."""
+
+        # Default state (safe)
+        total_pages = max(int(self.total_pages or 0), 1)
+        current_page = min(max(int(self.current_page or 0), 0), total_pages - 1)
+        self.current_page = current_page
+
+        self.page_label.setText(f"Page {current_page + 1}/{total_pages}")
+        self.prev_page_btn.setEnabled(current_page > 0)
+        self.next_page_btn.setEnabled(current_page < (total_pages - 1))
+
     def _load_detection_summary(self):
         """Load latest detection summaries grouped by image + model."""
         try:
-            detections = self.db_manager.get_detections(limit=500)
-            summary_map: Dict[tuple, Dict] = {}
+            # Prefer run summaries (supports zero-detection runs). Fall back to legacy
+            # detection aggregation if the DB/table isn't available.
+            try:
+                self.total_runs = int(self.db_manager.get_detection_run_total())
+            except Exception:
+                self.total_runs = 0
 
-            for det in detections:
-                key = (det["image_id"], det["model_id"])
-                metadata = det.get("metadata") or {}
-                entry = summary_map.setdefault(
-                    key,
+            self.total_pages = (self.total_runs + self.page_size - 1) // self.page_size if self.total_runs > 0 else 1
+
+            offset = int(self.current_page) * int(self.page_size)
+            runs = self.db_manager.get_detection_run_summaries(
+                limit=int(self.page_size),
+                offset=offset,
+            )
+            summary: List[Dict] = []
+            for run in runs:
+                meta = run.get("metadata") or {}
+                classes_raw = run.get("classes")
+                classes = set()
+                if isinstance(classes_raw, str) and classes_raw.strip():
+                    classes = {c.strip() for c in classes_raw.split(",") if c.strip()}
+
+                summary.append(
                     {
-                        "image_id": det["image_id"],
-                        "model_id": det["model_id"],
-                        "image_path": det.get("image_path"),
-                        "image_filename": det.get("image_filename") or det.get("image_path"),
-                        "model_name": det.get("model_name", ""),
-                        "model_version": det.get("model_version", ""),
-                        "last_detected": det.get("detected_at"),
-                        "count": 0,
-                        "classes": set(),
-                        "source_path": metadata.get("source_path"),
-                        "repository_root": metadata.get("repository_root"),
-                    },
+                        "image_id": run.get("image_id"),
+                        "model_id": run.get("model_id"),
+                        "image_path": run.get("image_path"),
+                        "image_filename": run.get("image_filename") or run.get("image_path"),
+                        "model_name": run.get("model_name", ""),
+                        "model_version": run.get("model_version", ""),
+                        "last_detected": run.get("detected_at"),
+                        "count": int(run.get("count") or 0),
+                        "classes": classes,
+                        "source_path": meta.get("source_path"),
+                        "repository_root": meta.get("repository_root"),
+                    }
                 )
 
-                entry["count"] += 1
-                if det.get("detected_at") and (
-                    not entry.get("last_detected") or str(det.get("detected_at")) > str(entry.get("last_detected"))
-                ):
-                    entry["last_detected"] = det.get("detected_at")
-                if det.get("class_name"):
-                    entry["classes"].add(det["class_name"])
-                if metadata.get("source_path") and not entry.get("source_path"):
-                    entry["source_path"] = metadata.get("source_path")
-                if metadata.get("repository_root") and not entry.get("repository_root"):
-                    entry["repository_root"] = metadata.get("repository_root")
-
-            self.detection_summary = sorted(
-                summary_map.values(),
-                key=lambda x: str(x.get("last_detected") or ""),
-                reverse=True,
-            )
+            self.detection_summary = summary
         except Exception as e:
-            logger.error(f"Failed to load detection summary: {e}")
-            QMessageBox.critical(
-                self,
-                "Error",
-                f"Failed to load detection results:\n{str(e)}",
-            )
-            self.detection_summary = []
+            logger.error(f"Failed to load detection run summaries, falling back: {e}")
+            # Disable pagination if we can't page via detection_runs.
+            self.total_runs = 0
+            self.total_pages = 1
+            self.current_page = 0
+            try:
+                detections = self.db_manager.get_detections(limit=int(self.page_size))
+                summary_map: Dict[tuple, Dict] = {}
+
+                for det in detections:
+                    key = (det["image_id"], det["model_id"])
+                    metadata = det.get("metadata") or {}
+                    entry = summary_map.setdefault(
+                        key,
+                        {
+                            "image_id": det["image_id"],
+                            "model_id": det["model_id"],
+                            "image_path": det.get("image_path"),
+                            "image_filename": det.get("image_filename") or det.get("image_path"),
+                            "model_name": det.get("model_name", ""),
+                            "model_version": det.get("model_version", ""),
+                            "last_detected": det.get("detected_at"),
+                            "count": 0,
+                            "classes": set(),
+                            "source_path": metadata.get("source_path"),
+                            "repository_root": metadata.get("repository_root"),
+                        },
+                    )
+
+                    entry["count"] += 1
+                    if det.get("detected_at") and (
+                        not entry.get("last_detected") or str(det.get("detected_at")) > str(entry.get("last_detected"))
+                    ):
+                        entry["last_detected"] = det.get("detected_at")
+                    if det.get("class_name"):
+                        entry["classes"].add(det["class_name"])
+                    if metadata.get("source_path") and not entry.get("source_path"):
+                        entry["source_path"] = metadata.get("source_path")
+                    if metadata.get("repository_root") and not entry.get("repository_root"):
+                        entry["repository_root"] = metadata.get("repository_root")
+
+                self.detection_summary = sorted(
+                    summary_map.values(),
+                    key=lambda x: str(x.get("last_detected") or ""),
+                    reverse=True,
+                )
+            except Exception as inner:
+                logger.error(f"Failed to load detection summary: {inner}")
+                QMessageBox.critical(
+                    self,
+                    "Error",
+                    f"Failed to load detection results:\n{str(inner)}",
+                )
+                self.detection_summary = []
 
     def _populate_results_table(self):
         """Populate the table widget with detection summaries."""

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:

src/model/inference.py

@@ -84,25 +84,19 @@ class InferenceEngine:
 
             # Save detections to database, replacing any previous results for this image/model
             if save_to_db:
-                deleted_count = self.db_manager.delete_detections_for_image(
-                    image_id, self.model_id
-                )
+                deleted_count = self.db_manager.delete_detections_for_image(image_id, self.model_id)
                 if detections:
                     detection_records = []
                     for det in detections:
                         # Use normalized bbox from detection
-                        bbox_normalized = det[
-                            "bbox_normalized"
-                        ]  # [x_min, y_min, x_max, y_max]
+                        bbox_normalized = det["bbox_normalized"]  # [x_min, y_min, x_max, y_max]
 
                         metadata = {
                             "class_id": det["class_id"],
                             "source_path": str(Path(image_path).resolve()),
                         }
                         if repository_root:
-                            metadata["repository_root"] = str(
-                                Path(repository_root).resolve()
-                            )
+                            metadata["repository_root"] = str(Path(repository_root).resolve())
 
                         record = {
                             "image_id": image_id,
@@ -115,16 +109,27 @@ class InferenceEngine:
                         }
                         detection_records.append(record)
 
-                    inserted_count = self.db_manager.add_detections_batch(
-                        detection_records
-                    )
-                    logger.info(
-                        f"Saved {inserted_count} detections to database (replaced {deleted_count})"
-                    )
+                    inserted_count = self.db_manager.add_detections_batch(detection_records)
+                    logger.info(f"Saved {inserted_count} detections to database (replaced {deleted_count})")
                 else:
-                    logger.info(
-                        f"Detection run removed {deleted_count} stale entries but produced no new detections"
+                    logger.info(f"Detection run removed {deleted_count} stale entries but produced no new detections")
+
+                # Always store a run summary so the Results tab can show zero-detection runs.
+                try:
+                    run_metadata = {
+                        "source_path": str(Path(image_path).resolve()),
+                    }
+                    if repository_root:
+                        run_metadata["repository_root"] = str(Path(repository_root).resolve())
+                    self.db_manager.upsert_detection_run(
+                        image_id=image_id,
+                        model_id=self.model_id,
+                        count=len(detections),
+                        metadata=run_metadata,
                     )
+                except Exception as exc:
+                    # Non-fatal: detection records may still be present.
+                    logger.warning(f"Failed to store detection run summary: {exc}")
 
             return {
                 "success": True,
@@ -232,9 +237,7 @@ class InferenceEngine:
             for det in detections:
                 # Get color for this class
                 class_name = det["class_name"]
-                color_hex = bbox_colors.get(
-                    class_name, bbox_colors.get("default", "#00FF00")
-                )
+                color_hex = bbox_colors.get(class_name, bbox_colors.get("default", "#00FF00"))
                 color = self._hex_to_bgr(color_hex)
 
                 # Draw segmentation mask if available and requested
@@ -243,10 +246,7 @@ class InferenceEngine:
                     if mask_normalized and len(mask_normalized) > 0:
                         # Convert normalized coordinates to absolute pixels
                         mask_points = np.array(
-                            [
-                                [int(pt[0] * width), int(pt[1] * height)]
-                                for pt in mask_normalized
-                            ],
+                            [[int(pt[0] * width), int(pt[1] * height)] for pt in mask_normalized],
                             dtype=np.int32,
                         )
 
@@ -270,9 +270,7 @@ class InferenceEngine:
                 label = f"{class_name} {det['confidence']:.2f}"
 
                 # Draw label background
-                (label_w, label_h), baseline = cv2.getTextSize(
-                    label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1
-                )
+                (label_w, label_h), baseline = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
                 cv2.rectangle(
                     img,
                     (x1, y1 - label_h - baseline - 5),

src/model/yolo_wrapper.py

@@ -186,7 +186,7 @@ class YOLOWrapper:
                 raise RuntimeError(f"Failed to load model from {self.model_path}")
 
         prepared_source, cleanup_path = self._prepare_source(source)
-        imgsz = 1088
+        imgsz = 640  # 1088
         try:
             logger.info(f"Running inference on {source} -> prepared_source {prepared_source}")
             results = self.model.predict(

src/utils/image.py

@@ -6,6 +6,9 @@ import cv2
 import numpy as np
 from pathlib import Path
 from typing import Optional, Tuple, Union
+from skimage.restoration import rolling_ball
+from skimage.filters import threshold_otsu
+from scipy.ndimage import median_filter, gaussian_filter
 
 from src.utils.logger import get_logger
 from src.utils.file_utils import validate_file_path, is_image_file
@@ -37,6 +40,8 @@ def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.5) -> np.ndarray:
     a1[a1 > p999] = p999
     a1 /= a1.max()
 
+    # print("Using get_pseudo_rgb")
+
     if 1:
         a2 = a1.copy()
         a2 = a2**gamma
@@ -46,14 +51,75 @@ def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.5) -> np.ndarray:
         p9999 = np.percentile(a3, 99.99)
         a3[a3 > p9999] = p9999
         a3 /= a3.max()
+        out = np.stack([a1, a2, a3], axis=0)
+
+    else:
+        out = np.stack([a1, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
+
+    return out
 
     # return np.stack([a1, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
     # return np.stack([a2, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
-    out = np.stack([a1, a2, a3], axis=0)
     # print(any(np.isnan(out).flatten()))
 
+
+def _get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.3) -> np.ndarray:
+    """
+    Convert a grayscale image to a pseudo-RGB image using a gamma correction.
+
+    Args:
+        arr: Input grayscale image as numpy array
+
+    Returns:
+        Pseudo-RGB image as numpy array
+    """
+    if arr.ndim != 2:
+        raise ValueError("Input array must be a grayscale image with shape (H, W)")
+
+    radius = 80
+    # bg = rolling_ball(arr, radius=radius)
+    a1 = arr.copy().astype(np.float32)
+    a1 = a1.astype(np.float32)
+    # a1 -= bg
+    # a1[a1 < 0] = 0
+    # a1 -= np.percentile(a1, 2)
+    # a1[a1 < 0] = 0
+    p999 = np.percentile(a1, 99.99)
+    a1[a1 > p999] = p999
+    a1 /= a1.max()
+
+    print("Using get_pseudo_rgb")
+
+    if 1:
+        a2 = a1.copy()
+        _a2 = a2**gamma
+        thr = threshold_otsu(_a2)
+        mask = gaussian_filter((_a2 > thr).astype(np.float32), sigma=5)
+        mask[mask > 0.0001] = 1
+        mask[mask <= 0.0001] = 0
+        a2 *= mask
+
+        # bg2 = rolling_ball(a2, radius=radius)
+        # a2 -= bg2
+        a2 -= np.percentile(a2, 2)
+        a2[a2 < 0] = 0
+        a2 /= a2.max()
+
+        a3 = a1.copy()
+        p9999 = np.percentile(a3, 99.99)
+        a3[a3 > p9999] = p9999
+        a3 /= a3.max()
+        out = np.stack([a1, a2, _a2], axis=0)
+
+    else:
+        out = np.stack([a1, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
+
     return out
 
+    # return np.stack([a1, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
+    # return np.stack([a2, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
+    # print(any(np.isnan(out).flatten()))
+
 
 class ImageLoadError(Exception):
     """Exception raised when an image cannot be loaded."""
@@ -330,17 +396,20 @@ class Image:
         return self._channels >= 3
 
     def save(self, path: Union[str, Path], pseudo_rgb: bool = True) -> None:
-
+        # print("Image.save", self.data.shape)
         if self.channels == 1:
+            # print("Image.save grayscale")
             if pseudo_rgb:
                 img = get_pseudo_rgb(self.data)
-                print("Image.save", img.shape)
+                # print("Image.save", img.shape)
+
             else:
                 img = np.repeat(self.data, 3, axis=2)
-
+                # print("Image.save no pseudo", img.shape)
         else:
             raise NotImplementedError("Only grayscale images are supported for now.")
 
+        # print("Image.save imwrite", img.shape)
         imwrite(path, data=img)
 
     def __repr__(self) -> str:

src/utils/image_converters.py

@@ -97,7 +97,7 @@ class UT:
         class_index: int = 0,
     ):
         """Export rois to a file"""
-        with open(path / subfolder / f"{self.stem}.txt", "w") as f:
+        with open(path / subfolder / f"{PREFIX}-{self.stem}.txt", "w") as f:
             for i, roi in enumerate(self.rois):
                 rc = roi.subpixel_coordinates
                 if rc is None:
@@ -129,8 +129,8 @@ class UT:
             self.image = np.max(self.image[channel], axis=0)
             print(self.image.shape)
 
-        print(path / subfolder / f"{self.stem}.tif")
-        with TiffWriter(path / subfolder / f"{self.stem}.tif") as tif:
+        print(path / subfolder / f"{PREFIX}_{self.stem}.tif")
+        with TiffWriter(path / subfolder / f"{PREFIX}-{self.stem}.tif") as tif:
             tif.write(self.image)
 
 
@@ -145,11 +145,19 @@ if __name__ == "__main__":
         action="store_false",
         help="Source does not have labels, export only images",
     )
+    parser.add_argument("--prefix", help="Prefix for output files")
     args = parser.parse_args()
 
+    PREFIX = args.prefix
     # print(args)
     # aa
 
+    # for path in args.input:
+    #     print(path)
+    #     ut = UT(path, args.no_labels)
+    #     ut.export_image(args.output, plane_mode="max projection", channel=0)
+    #     ut.export_rois(args.output, class_index=0)
+
     for path in args.input:
         print("Path:", path)
         if not args.no_labels:

src/utils/image_splitter.py

@@ -5,7 +5,7 @@ from tifffile import imread, imwrite
 from shapely.geometry import LineString
 from copy import deepcopy
 from scipy.ndimage import zoom
-
+from skimage.restoration import rolling_ball
 
 # debug
 from src.utils.image import Image
@@ -160,8 +160,11 @@ class YoloLabelReader:
 
 
 class ImageSplitter:
-    def __init__(self, image_path: Path, label_path: Path):
+    def __init__(self, image_path: Path, label_path: Path, subtract_bg: bool = False):
         self.image = imread(image_path)
+        if subtract_bg:
+            self.image = self.image - rolling_ball(self.image, radius=12)
+            self.image[self.image < 0] = 0
         self.image_path = image_path
         self.label_path = label_path
         if not label_path.exists():
@@ -273,13 +276,14 @@ def main(args):
     if args.output:
         args.output.mkdir(exist_ok=True, parents=True)
         (args.output / "images").mkdir(exist_ok=True)
-        (args.output / "images-zoomed").mkdir(exist_ok=True)
+        # (args.output / "images-zoomed").mkdir(exist_ok=True)
         (args.output / "labels").mkdir(exist_ok=True)
 
     for image_path in (args.input / "images").glob("*.tif"):
         data = ImageSplitter(
             image_path=image_path,
             label_path=(args.input / "labels" / image_path.stem).with_suffix(".txt"),
+            subtract_bg=args.subtract_bg,
         )
 
         if args.split_around_label:
@@ -332,10 +336,20 @@ def main(args):
 
                 if labels is not None:
                     with open(args.output / "labels" / f"{image_path.stem}_{tile_reference}.txt", "w") as f:
+                        print(
+                            f"Writing {len(labels)} labels to {args.output / 'labels' / f'{image_path.stem}_{tile_reference}.txt'}"
+                        )
                         for label in labels:
                             # label.offset_label(tile.shape[1], tile.shape[0])
                             f.write(label.to_string() + "\n")
 
+                            # { debug
+                            if debug:
+                                print(label.to_string())
+                            # } debug
+            # break
+        # break
+
 
 if __name__ == "__main__":
     import argparse
@@ -363,6 +377,7 @@ if __name__ == "__main__":
         default=67,
         help="Padding around the label when splitting around the label.",
     )
+    parser.add_argument("-bg", "--subtract-bg", action="store_true", help="Subtract background from the image.")
     args = parser.parse_args()
 
     main(args)