Update: display return

yolov8.py

@@ -63,6 +63,6 @@ def xai_yolov8s(image):
     tensor = transform(img_float).unsqueeze(0)
     target_layers = [model.model.model[-2]]  # Adjust to YOLOv8 architecture
     cam_image, renormalized_cam_image = generate_cam_image(model.model, target_layers, tensor, image, boxes)
-    final_image = np.hstack((image, cam_image, renormalized_cam_image))
+    final_image = np.hstack((image, detections_img, renormalized_cam_image))
     caption = "Results using YOLOv8"
     return Image.fromarray(final_image), caption