Update video_predictions.ipynb

Author: Gabefire

examples/prediction_upload/video_predictions.ipynb

@@ -325,7 +325,7 @@
     },
     {
       "metadata": {},
-      "source": "# Create a Label object by identifying the applicable data row in Labelbox and providing a list of annotations\n\nlabels = []\nannotations_list = [\n    checklist_annotation,\n    radio_annotation,\n    bbox_annotation,\n    frame_bbox_with_checklist_subclass,\n    point_annotation,\n    polyline_annotation,\n    global_checklist_annotation,\n    global_radio_annotation,\n    nested_checklist_annotation,\n    nested_radio_annotation,\n    text_annotation,\n]\n\nflatten_list_annotations = [\n    ann for ann_sublist in annotations_list for ann in ann_sublist\n]\n\nlabels.append(\n    lb_types.Label(\n        data=lb_types.VideoData(global_key=global_key),\n        annotations=flatten_list_annotations,\n    ))",
+      "source": "# Create a Label object by identifying the applicable data row in Labelbox and providing a list of annotations\n\nlabels = []\nannotations_list = [\n    checklist_annotation,\n    radio_annotation,\n    bbox_annotation,\n    frame_bbox_with_checklist_subclass,\n    point_annotation,\n    polyline_annotation,\n    global_checklist_annotation,\n    global_radio_annotation,\n    nested_checklist_annotation,\n    nested_radio_annotation,\n    text_annotation,\n]\n\nflatten_list_annotations = [\n    ann for ann_sublist in annotations_list for ann in ann_sublist\n]\n\nlabels.append(\n    lb_types.Label(\n        data={"global_key":global_key},\n        annotations=flatten_list_annotations,\n    ))",
       "cell_type": "code",
       "outputs": [],
       "execution_count": null
@@ -373,4 +373,4 @@
       "execution_count": null
     }
   ]
-}
+}