Export video annotations

How to export video annotations and sample export formats.

Open this Colab for an interactive tutorial on exporting annotations.

πŸ“˜

Deprecating Export V1

Starting in April 2024, we will begin sunsetting Export V1 for customers on a rolling basis. For more details, see this guide.

Export as JSON

# Set the export params to include/exclude certain fields.
# Make sure each of these fields are correctly grabbed 
export_params= {
  "attachments": True,
  "metadata_fields": True,
  "data_row_details": True,
  "project_details": True,
  "performance_details": True,
  "label_details": True,
  "interpolated_frames": True
}

# You can set the range for last_activity_at and label_created_at. 
# For context, last_activity_at captures the creation and modification of labels, metadata, 
# status, comments and reviews.
# Note: This is an AND logic between the filters, so usually 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_v2(params=export_params, filters=filters)
export_task.wait_till_done()

if export_task.errors:
  print(export_task.errors)

export_json = export_task.result
print("results: ", export_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": False
}

# 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>"
}

client.enable_experimental = True

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


# Return JSON output strings from export task results/errors, one by one:

# Callback used for JSON Converter
def json_stream_handler(output: lb.JsonConverterOutput):
  print(output.json_str)


if export_task.has_errors():
  export_task.get_stream(
  
  converter=lb.JsonConverter(),
  stream_type=lb.StreamType.ERRORS
  ).start(stream_handler=lambda error: print(error))

if export_task.has_result():
  export_json = export_task.get_stream(
    converter=lb.JsonConverter(),
    stream_type=lb.StreamType.RESULT
  ).start(stream_handler=json_stream_handler)

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

Composite masks

A composite mask is a cloud-hosted PNG file that contains all segmentation mask instances on a labeled frame.

The first screenshot below is an example of a composite mask in PNG format. In this example, 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 that contain 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" represents the color of a single annotation or instance mask in a label.

Note: we will soon deprecate the individual mask URLs and only provide the "composite_mask.url" and "color_rgb" in the export.

The green arrow indicates how to identify a single mask instance (e.g., "Human 1") and the yellow arrow indicates how to access the composite mask (all mask instances) on a given frame.

The green arrow indicates how to identify a single mask instance (e.g., "Human 1") and the yellow arrow indicates how to access the composite mask (all mask instances) on a given frame.

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

{
  "feature_id": "clsg9gro500033b6wv9zxdlyr",
  "feature_schema_id": "clj4ios61064e07zibsb72fqg",
  "name": "seg",
  "value": "seg",
  "annotation_kind": "VideoSegmentationMask",
  "classifications": [],
  "mask": {
    "url": "https://api.labelbox.com/api/v1/projects/clj4ilpqt050y07zkg97shekd/annotations/clsg9gro500033b6wv9zxdlyr/index/1/mask"
  },
  "composite_mask": {
    // This URL includes all mask instances in the frame
    "url": "https://api.labelbox.com/api/v1/tasks/clsiwfcj805o1074ihihkcv4j/masks/clsg9goze00013b6wssdgj4ii",
    // This RGB reflects a single mask instance
    "color_rgb": [
      162,
      30,
      86
    ]
  }
}

How to 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. 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"

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

# Optionally, print the image of the mask (for a specific frame)
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": [],
  "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
                    }
                  },
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                "value": "checklist_class_global",
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                "value": "nested_checklist_question",
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                "value": "nested_radio_question",
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                "value": "free_text",
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      "project_details": {
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        "workflow_status": "DONE",
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Sample model run export

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    "id": "cldtd2nai107407y5979xbu97",
    "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": {
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    "mime_type": "video/mp4",
    "frame_rate": 10,
    "frame_count": 100
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  "attachments": [],
  "metadata_fields": [],
  "experiments": {
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      "runs": {
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          "name": "iteration 1",
          "run_data_row_id": "999a247e-0b57-415e-af7e-d3a87cc6559b",
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                        "name": "point_video",
                        "value": "point_video",
                        "annotation_kind": "VideoPoint",
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