showing annotated images for detect target message bug fix

modules/detect_target/detect_target_factory.py

@@ -3,6 +3,7 @@
 """
 
 import enum
+import torch
 
 from . import base_detect_target
 from . import detect_target_ultralytics
@@ -27,8 +28,25 @@ def create_detect_target(
     save_name: str,
 ) -> tuple[bool, base_detect_target.BaseDetectTarget | None]:
     """
-    Construct detect target class at runtime.
+    Factory function to create a detection target object.
+
+    Parameters:
+    detect_target_option: Enumeration value to specify the type of detection.
+    device: Target device for inference ("cpu" or CUDA device index).
+    model_path: Path to the model file.
+    override_full: Force full precision floating point calculations.
+    local_logger: Logger instance for logging events.
+    show_annotations: Whether to display annotated images.
+    save_name: Prefix for saving logs or annotated images.
+
+    Returns:
+    Tuple containing success status and the instantiated detection object (if successful).
     """
+    # Fall back to CPU if no GPU is available
+    if device != "cpu" and not torch.cuda.is_available():
+        local_logger.warning("CUDA not available. Falling back to CPU.")
+        device = "cpu"
+
     match detect_target_option:
         case DetectTargetOption.ML_ULTRALYTICS:
             return True, detect_target_ultralytics.DetectTargetUltralytics(

modules/detect_target/detect_target_ultralytics.py

@@ -111,6 +111,12 @@ def run(
             self.__counter += 1
 
         if self.__show_annotations:
-            cv2.imshow("Annotated", image_annotated)  # type: ignore
+            if image_annotated is None:
+                self.__local_logger.error("Annotated image is invalid.")
+                return False, detections
+
+            # Display the annotated image in a named window
+            cv2.imshow("Annotated", image_annotated)
+            cv2.waitKey(1)  # Short delay to process GUI events
 
         return True, detections