Export video annotations

How to export video annotations and sample export formats.

Export as JSON

# Set the export params to include/exclude certain fields. 
export_params= {
  "attachments": True,
  "metadata_fields": True,
  "data_row_details": True,
  "project_details": True,
  "label_details": True,
  "performance_details": True,
  "interpolated_frames": True
}

# Note: Filters follow AND logic, so typically using one filter is sufficient.
filters= {
  "last_activity_at": ["2000-01-01 00:00:00", "2050-01-01 00:00:00"],
  "workflow_status": "<wkf-status>"
}

export_task = project.export(params=export_params, filters=filters)
export_task.wait_till_done()

# Stream results and errors
if export_task.has_errors():
    export_task.get_buffered_stream(stream_type=lb.StreamType.ERRORS).start(
        stream_handler=lambda error: print(error))

if export_task.has_result():
    # Start export stream
    stream = export_task.get_buffered_stream()

    # Iterate through data rows
    for data_row in stream:
        print(data_row.json)

print("file size: ", export_task.get_total_file_size(stream_type=lb.StreamType.RESULT))
print("line count: ", export_task.get_total_lines(stream_type=lb.StreamType.RESULT))
     

Annotation export formats

Bounding box

{
  "feature_id": "cltd97cag01th14ys6fyyxyk9",
  "feature_schema_id": "cltd977no037j07x5d82dacbc",
  "name": "bbox_video",
  "value": "bbox_video",
  "annotation_kind": "VideoBoundingBox",
  "classifications": [],
  "bounding_box": {
    "top": 617.0,
    "left": 1371.0,
    "height": 419.0,
    "width": 505.0
  }
}

Point

{
  "feature_id": "cltd97cag01to14yslakirofl",
  "feature_schema_id": "cltd977no037l07x56wfu4536",
  "name": "point_video",
  "value": "point_video",
  "annotation_kind": "VideoPoint",
  "classifications": [],
  "point": {
    "x": 660.134,
    "y": 407.926
  }
}

Polyline

 {
   "feature_id": "cltd97cag01tp14ysz3my848t",
   "feature_schema_id": "cltd977np037n07x5d1buckz9",
   "name": "line_video_frame",
   "value": "line_video_frame",
   "annotation_kind": "VideoPolyline",
   "classifications": [],
   "line": [
     {
       "x": 680.0,
       "y": 100.0
     },
     {
       "x": 100.0,
       "y": 190.0
     }
   ]
 }

Mask

Regardless of which tool is used to create a segmentation mask, the annotation will appear in the following form in the export. Whether you use AutoSegment, the brush tool, the pen tool, or the fill tool, all masks take the same format in exports.

Composite masks

Open this Colab for an interactive tutorial on exporting composite masks.

A composite mask is a cloud-hosted PNG file that contains all raster segmentation mask instances on a labeled data row (one composite mask per label).

This screenshot shows an example composite mask in PNG format. Here, the image has eight segmentation mask instances, each using the schema named "Human".

A labeled data row containing 8 instances of a segmentation mask named "Human".

A labeled data row containing 8 instances of a segmentation mask named "Human".

When you export data rows containing segmentation masks, you can use composite_mask.url to access all segmentation masks on that data row. To access a single instance of a segmentation mask, use the color_rgb values. The color_rgb value represents the color of a single annotation or instance mask in a label.

Sample composite masks export
{
  "feature_id": "clsivokxg00043b70xuf7x5tz",
  "feature_schema_id": "clsgbcaqw000j071t2ga23jnc",
  "name": "car",
  "value": "car",
  "annotation_kind": "ImageSegmentationMask",
  "classifications": [],
  "mask": {
    "url": "https://api.labelbox.com/api/v1/projects/clsivnieg050k074i2jqaa0c3/annotations/clsivokxg00043b70xuf7x5tz/index/1/mask"
  },
  "composite_mask": {
    // This URL contains all mask instances on the data row
    "url": "https://api.labelbox.com/api/v1/tasks/clsiw88n205mw072ke4n78y5o/masks/clsivok5f00023b70r1a4fgzy",
    // This RGB reflects a single mask instance
    "color_rgb": [
      31,
      185,
      101
    ]
  }
}

Access mask data

To access the mask data, you must pass your Labelbox API key stored in client.headers in an API request.

When you grab a URL from the mask annotation in the export, the project_id and feature_id will already be in place, as shown above. Here, we provide the framework for structuring a URL with any project ID and feature ID.

import urllib.request
from PIL import Image

# Provide a project ID and feature ID if using instance masks. Alternatively, replace the entire mask_url with a URL grabbed from your export.
project_id = ""
feature_id = ""

mask_url = f"https://api.labelbox.com/api/v1/projects/{project_id}/annotations/{feature_id}/index/1/mask"

# Instead of providing the individual variables, we recommend utilizing the URL from export for composite mask
composite_mask_url = f"https://api.labelbox.com/api/v1/tasks/{task_id}/masks/{composite_mask_id}/index/1"

# Make the API request
req = urllib.request.Request(mask_url, headers=client.headers)

# Optionally, print the image of the mask
image = Image.open(urllib.request.urlopen(req))
image

Classification - Radio

{
  "feature_id": "cltd97cag01tf14ysho6tfl7j",
  "feature_schema_id": "cltd977np038907x5ah8l9ha7",
  "name": "radio_class",
  "value": "radio_class",
  "radio_answer": {
    "feature_id": "cltd97cag01tg14ys171a3qqr",
    "feature_schema_id": "cltd977np038a07x515axagkl",
    "name": "first_radio_answer",
    "value": "first_radio_answer",
    "classifications": []
  }
}

Classification - Checklist

{
  "feature_id": "cltd97cag01tq14ysb4m3nyjo",
  "feature_schema_id": "cltd977nq039107x5dsml2knm",
  "name": "checklist_class_global",
  "value": "checklist_class_global",
  "checklist_answers": [
    {
      "feature_id": "cltd97cag01tr14ysozjbx0c6",
      "feature_schema_id": "cltd977nq039207x5ei1605s1",
      "name": "first_checklist_answer",
      "value": "first_checklist_answer",
      "classifications": []
    },
    {
      "feature_id": "cltd97cag01ts14ys4vvxihnw",
      "feature_schema_id": "cltd977nq039407x50qs3g61l",
      "name": "second_checklist_answer",
      "value": "second_checklist_answer",
      "classifications": []
    }
  ]
}

Classification - Free-form text

{
  "feature_id": "cltd97cag01u314ysx1h72f0h",
  "feature_schema_id": "cltd977nq039707x535ufeo39",
  "name": "free_text",
  "value": "free_text",
  "text_answer": {
    "content": "sample text"
  }
}

Sample project export

{
  "data_row": {
    "id": "clp1jolki07uy0725flku4bmv",
    "global_key": "sample-video-jellyfish.mp4",
    "row_data": "https://storage.googleapis.com/labelbox-datasets/video-sample-data/sample-video-2.mp4",
    "details": {
      "dataset_id": "clp1jokqp000p07307gtfy1w3",
      "dataset_name": "video_demo_dataset",
      "created_at": "2023-11-16T18:48:51.208+00:00",
      "updated_at": "2023-11-16T18:48:51.801+00:00",
      "last_activity_at": "2024-04-08T17:09:54.000+00:00",
      "created_by": "[email protected]"
    }
  },
  "media_attributes": {
    "height": 1080,
    "width": 1920,
    "mime_type": "video/mp4",
    "frame_rate": 10,
    "frame_count": 100
  },
  "attachments": [],
  "metadata_fields": [],
   "embeddings": [
    {
      "id": "c400000000000000000000000",
      "name": "Video Embedding V2 (Google MultiModal)",
      "dimensions": 1408,
      "is_custom": false,
      "values": [
        {
          "value": [
            -0.00489852577,
            0.0287129097 ...
          ]
        }
      ]
    }
  ],
  "projects": {
    "cltd977uu016y08xyggep8aiv": {
      "name": "Video Annotation Import Demo",
      "labels": [
        {
          "label_kind": "Video",
          "version": "1.0.0",
          "id": "cltd97caz01ub14ysq8rf4x8w",
          "label_details": {
            "created_at": "2024-03-04T18:07:33.000+00:00",
            "updated_at": "2024-03-04T18:07:33.000+00:00",
            "created_by": "[email protected]",
            "content_last_updated_at": "2024-03-04T18:07:33.369+00:00",
            "reviews": []
          },
          "performance_details": {
            "seconds_to_create": 0,
            "seconds_to_review": 0,
            "skipped": false
          },
          "annotations": {
            "frames": {
              "29": {
                "objects": {
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": [
                  {
                    "feature_id": "cltd97cag01tc14yspm0lev2d",
                    "feature_schema_id": "cltd977np038307x55dlf3rgs",
                    "name": "checklist_class",
                    "value": "checklist_class",
                    "checklist_answers": [
                      {
                        "feature_id": "cltd97cag01td14ysxw2n8xkz",
                        "feature_schema_id": "cltd977np038407x51hcvdad7",
                        "name": "first_checklist_answer",
                        "value": "first_checklist_answer",
                        "classifications": []
                      },
                      {
                        "feature_id": "cltd97cag01te14ys1jdf1fku",
                        "feature_schema_id": "cltd977np038607x58epu4nb5",
                        "name": "second_checklist_answer",
                        "value": "second_checklist_answer",
                        "classifications": []
                      }
                    ]
                  }
                ]
              },
              "35": {
                "objects": {
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": [
                  {
                    "feature_id": "cltd97cag01tc14yspm0lev2d",
                    "feature_schema_id": "cltd977np038307x55dlf3rgs",
                    "name": "checklist_class",
                    "value": "checklist_class",
                    "checklist_answers": [
                      {
                        "feature_id": "cltd97cag01td14ysxw2n8xkz",
                        "feature_schema_id": "cltd977np038407x51hcvdad7",
                        "name": "first_checklist_answer",
                        "value": "first_checklist_answer",
                        "classifications": []
                      },
                      {
                        "feature_id": "cltd97cag01te14ys1jdf1fku",
                        "feature_schema_id": "cltd977np038607x58epu4nb5",
                        "name": "second_checklist_answer",
                        "value": "second_checklist_answer",
                        "classifications": []
                      }
                    ]
                  }
                ]
              },
              "9": {
                "objects": {
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.00000000000001
                      },
                      {
                        "x": 100.00000000000001,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": [
                  {
                    "feature_id": "cltd97cag01tf14ysho6tfl7j",
                    "feature_schema_id": "cltd977np038907x5ah8l9ha7",
                    "name": "radio_class",
                    "value": "radio_class",
                    "radio_answer": {
                      "feature_id": "cltd97cag01tg14ys171a3qqr",
                      "feature_schema_id": "cltd977np038a07x515axagkl",
                      "name": "first_radio_answer",
                      "value": "first_radio_answer",
                      "classifications": []
                    }
                  }
                ]
              },
              "15": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": [
                  {
                    "feature_id": "cltd97cag01tf14ysho6tfl7j",
                    "feature_schema_id": "cltd977np038907x5ah8l9ha7",
                    "name": "radio_class",
                    "value": "radio_class",
                    "radio_answer": {
                      "feature_id": "cltd97cag01tg14ys171a3qqr",
                      "feature_schema_id": "cltd977np038a07x515axagkl",
                      "name": "first_radio_answer",
                      "value": "first_radio_answer",
                      "classifications": []
                    }
                  }
                ]
              },
              "13": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01ti14ys8wedf89d": {
                    "feature_id": "cltd97cag01ti14ys8wedf89d",
                    "feature_schema_id": "cltd977np037r07x512iteflz",
                    "name": "bbox_class",
                    "value": "bbox_class",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [
                      {
                        "feature_id": "cltd97cag01tj14ysz455nenr",
                        "feature_schema_id": "cltd977np037s07x5csbodf5f",
                        "name": "checklist_class",
                        "value": "checklist_class",
                        "radio_answer": {
                          "feature_id": "cltd97cag01tl14ysnbe8mw75",
                          "feature_schema_id": "cltd977np037v07x54esmdmws",
                          "name": "second_checklist_answer",
                          "value": "second_checklist_answer",
                          "classifications": []
                        }
                      }
                    ],
                    "bounding_box": {
                      "top": 146.0,
                      "left": 98.0,
                      "height": 382.0,
                      "width": 341.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "14": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0000000000001,
                      "left": 1371.0,
                      "height": 418.9999999999999,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "16": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "17": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01to14yslakirofl": {
                    "feature_id": "cltd97cag01to14yslakirofl",
                    "feature_schema_id": "cltd977no037l07x56wfu4536",
                    "name": "point_video",
                    "value": "point_video",
                    "annotation_kind": "VideoPoint",
                    "classifications": [],
                    "point": {
                      "x": 660.134,
                      "y": 407.926
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "18": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "19": {
                "objects": {
                  "cltd97cag01th14ys6fyyxyk9": {
                    "feature_id": "cltd97cag01th14ys6fyyxyk9",
                    "feature_schema_id": "cltd977no037j07x5d82dacbc",
                    "name": "bbox_video",
                    "value": "bbox_video",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 617.0,
                      "left": 1371.0,
                      "height": 419.0,
                      "width": 505.0
                    }
                  },
                  "cltd97cag01tp14ysz3my848t": {
                    "feature_id": "cltd97cag01tp14ysz3my848t",
                    "feature_schema_id": "cltd977np037n07x5d1buckz9",
                    "name": "line_video_frame",
                    "value": "line_video_frame",
                    "annotation_kind": "VideoPolyline",
                    "classifications": [],
                    "line": [
                      {
                        "x": 680.0,
                        "y": 100.0
                      },
                      {
                        "x": 100.0,
                        "y": 190.0
                      }
                    ]
                  }
                },
                "classifications": []
              },
              "10": {
                "objects": {
                  "cltd97cag01ti14ys8wedf89d": {
                    "feature_id": "cltd97cag01ti14ys8wedf89d",
                    "feature_schema_id": "cltd977np037r07x512iteflz",
                    "name": "bbox_class",
                    "value": "bbox_class",
                    "annotation_kind": "VideoBoundingBox",
                    "classifications": [],
                    "bounding_box": {
                      "top": 146.0,
                      "left": 98.0,
                      "height": 382.0,
                      "width": 341.0
                    }
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                    "annotation_kind": "VideoSegmentationMask",
                    "classifications": [],
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            "key_frame_feature_map": {
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                "value": "checklist_class_global",
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                "value": "nested_checklist_question",
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                "value": "nested_radio_question",
                "radio_answer": {
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                "value": "free_text",
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        "priority": 5,
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Sample model run export

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    "global_key": "3548cfa1-1a42-40f9-a246-2aa7c696dcbe",
    "row_data": "https://storage.googleapis.com/labelbox-datasets/video-sample-data/sample-video-2.mp4",
    "details": {
      "dataset_id": "cldtd2mox11dz07wh3gkk9awx",
      "dataset_name": "video_prediction_demo",
      "created_at": "2023-02-06T22:04:54.000+00:00",
      "updated_at": "2023-02-06T22:04:54.000+00:00",
      "created_by": "[email protected]"
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  "media_attributes": {
    "height": 1080,
    "width": 1920,
    "mime_type": "video/mp4",
    "frame_rate": 10,
    "frame_count": 100
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  "attachments": [],
  "metadata_fields": [],
  "experiments": {
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          "name": "iteration 1",
          "run_data_row_id": "999a247e-0b57-415e-af7e-d3a87cc6559b",
          "labels": [
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                        "name": "point_video",
                        "value": "point_video",
                        "annotation_kind": "VideoPoint",
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