> ## Documentation Index
> Fetch the complete documentation index at: https://docs.labelbox.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Export image annotations

> How to export image annotations and sample export formats.

<CardGroup cols={2}>
  <Card title="Open In Colab" icon="infinity" iconType="solid" href="https://colab.research.google.com/github/Labelbox/labelbox-notebooks/blob/main/exports/export_data.ipynb" horizontal />

  <Card title="GitHub" icon="github" iconType="solid" href="https://github.com/Labelbox/labelbox-notebooks/blob/main/exports/export_data.ipynb" horizontal />
</CardGroup>

## Export as JSON

<CodeGroup>
  ```python Export theme={null}
  # 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 the export using a callback function

  def json_stream_handler(output: labelbox.BufferedJsonConverterOutput):
    print(output.json)

  export_task.get_buffered_stream(stream_type=labelbox.StreamType.RESULT).start(stream_handler=json_stream_handler)

  # Collect all exported data into a list

  export_json = [data_row.json for data_row in export_task.get_buffered_stream()]

  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))

  ```
</CodeGroup>

## Annotation export formats

### Bounding box

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clrf5csvi6ofm07lsf9pygwvi",
    "feature_schema_id": "clrf5ck4a0b9b071paa9ncu15",
    "name": "bounding_box",
    "annotation_kind": "ImageBoundingBox",
    "classifications": [],
    "bounding_box": {
      "top": 1264.0,
      "left": 2096.0,
      "height": 425.0,
      "width": 144.0
    }
  }
  ```
</CodeGroup>

### Polygon

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clr0x0ol83tvt07ea4has2a4l",
    "feature_schema_id": "clpk2me9t02v707xn08cv4ve5",
    "name": "polygon",
    "annotation_kind": "ImagePolygon",
    "classifications": [],
    "polygon": [
      {
        "x": 1489.581,
        "y": 183.934
      },
      {
        "x": 1489.581,
        "y": 183.934
      }
    ]
  }
  ```
</CodeGroup>

### Polyline

<CodeGroup>
  ```json JSON theme={null}
   {
     "feature_id": "clr0x0ol83tvk07eagehegjde",
     "feature_schema_id": "clpk2me9u02vh07xnfcmtbqvj",
     "name": "polyline",
     "annotation_kind": "ImagePolyline",
     "classifications": [],
     "line": [
       {
         "x": 2534.353,
         "y": 249.471
       },
       {
         "x": 90.929,
         "y": 326.412
       }
     ]
   }
  ```
</CodeGroup>

### Point

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clr0x0ol83tvr07ea2fyl69g9",
    "feature_schema_id": "clpk2me9u02vf07xnbpk45wxa",
    "name": "point",
    "annotation_kind": "ImagePoint",
    "classifications": [],
    "point": {
      "x": 1166.606,
      "y": 1441.768
    }
  }
  ```
</CodeGroup>

### Mask

Regardless of which [tool](/docs/image-editor#segmentation-mask) 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](https://colab.research.google.com/github/Labelbox/labelbox-notebooks/blob/main/exports/composite_mask_export.ipynb) 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".

<Frame caption="A labeled data row containing 8 instances of a segmentation mask named &#x22;Human&#x22;.">
  <img src="https://mintcdn.com/labelbox-1db23ff4/kk7T7t8LC7-TvqwP/images/reference/a52f86f-Screen_Shot_2024-03-04_at_10.08.07_AM.png?fit=max&auto=format&n=kk7T7t8LC7-TvqwP&q=85&s=fa0bbbb153db29a868ae96c87a18777f" width="1380" height="718" data-path="images/reference/a52f86f-Screen_Shot_2024-03-04_at_10.08.07_AM.png" />
</Frame>

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

<CodeGroup>
  ```json JSON theme={null}
  {
    "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
      ]
    }
  }
  ```
</CodeGroup>

#### 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.

<CodeGroup>
  ```python Python theme={null}
  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.show()
  ```
</CodeGroup>

### Relationship

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clur69pfa00023b6rkftlkucz",
    "feature_schema_id": "cltd3vkc201ab07ts1f9dhpkt",
    "name": "relationship",
    "value": "relationship",
    "annotation_kind": "ImageUnidirectionalRelationship",
    "classifications": [],
    "unidirectional_relationship": {
      "source": "clur5tlyq1n2d07dcg9xldg90",
      "target": "clur5tlyr1n2l07dc1jsf15qo"
    }
  }
  ```
</CodeGroup>

### Classification - radio

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clur5tlyr1n2k07dcezk08npu",
    "feature_schema_id": "cltd3vkc201ad07ts3t78873p",
    "name": "radio_question",
    "value": "radio_question",
    "radio_answer": {
      "feature_id": "clur5tlyr1n2y07dcajpyg0d4",
      "feature_schema_id": "cltd3vkc201ag07tsfoc2bdpi",
      "name": "second_radio_answer",
      "value": "second_radio_answer",
      "classifications": []
    }
  }
  ```
</CodeGroup>

### Classification - checklist

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clur5tlyr1n2p07dchs791672",
    "feature_schema_id": "cltd3vkc201aj07tsait4cbzh",
    "name": "checklist_question",
    "value": "checklist_question",
    "checklist_answers": [
      {
        "feature_id": "clur5tlyr1n2z07dc3abv19e8",
        "feature_schema_id": "cltd3vkc201ak07tsfqxc740z",
        "name": "first_checklist_answer",
        "value": "first_checklist_answer",
        "classifications": []
      },
      {
        "feature_id": "clur5tlyr1n3007dc4vbr0628",
        "feature_schema_id": "cltd3vkc201am07ts7s9e7x7k",
        "name": "second_checklist_answer",
        "value": "second_checklist_answer",
        "classifications": []
      }
    ]
  }
  ```
</CodeGroup>

### Classification - free-form text

<CodeGroup>
  ```json JSON theme={null}
  {
    "feature_id": "clur5tlyr1n2g07dc7wdv7p5z",
    "feature_schema_id": "cltd3vkc201ap07ts58gma0bb",
    "name": "free_text",
    "value": "free_text",
    "text_answer": {
      "content": "sample text"
    }
  }
  ```
</CodeGroup>

## Sample project export

<CodeGroup>
  ```json JSON expandable theme={null}
  {
    "data_row": {
      "id": "clf9spzxq029m071nehy60a6v",
      "global_key": "2560px-Kitano_Street_Kobe01s5s4110.jpeg",
      "row_data": "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg",
      "details": {
        "dataset_id": "clf9spwgw04w207ymfwy826qv",
        "dataset_name": "demo_dataset_img",
        "created_at": "2023-03-15T14:46:58.000+00:00",
        "updated_at": "2023-03-15T14:46:58.000+00:00",
        "last_activity_at": "2024-04-08T16:34:01.000+00:00",
        "created_by": "[email protected]"
      }
    },
    "media_attributes": {
      "height": 1707,
      "width": 2560,
      "mime_type": "image/jpeg"
    },
    "attachments": [],
    "metadata_fields": [],
    "embeddings": [
      {
        "id": "cn1cywy1r077807zblvo0m884",
        "name": "my_custom_embedding_2048_dimensions",
        "dimensions": 2048,
        "is_custom": true,
        "values": [
          {
            "value": [
              1.1265901290930636,
              1.0413733599834287,
              1.3041214120015427,
              1.893491997791636 ...
            ]
          }
        ]
      },
      {
        "id": "c200000000000000000000000",
        "name": "Image Embedding V2 (CLIP ViT-B/32)",
        "dimensions": 512,
        "is_custom": false,
        "values": [
          {
            "value": [
              -0.4192526042461395,
              -0.048827216029167175 ...
            ]
          }
        ]
      }
    ],
    "projects": {
      "cltd3vkju021907u63w2odj69": {
        "name": "Image Annotation Import Demo",
        "labels": [
          {
            "label_kind": "Default",
            "version": "1.0.0",
            "id": "clur5tlda1n2a07dc0i0zdd4k",
            "label_details": {
              "created_at": "2024-04-08T16:21:26.000+00:00",
              "updated_at": "2024-04-08T16:34:02.000+00:00",
              "created_by": "[email protected]",
              "content_last_updated_at": "2024-04-08T16:34:00.513+00:00",
              "reviews": []
            },
            "performance_details": {
              "seconds_to_create": 18,
              "seconds_to_review": 6,
              "skipped": false
            },
            "annotations": {
              "objects": [
                {
                  "feature_id": "clur5tlyq1n2d07dcg9xldg90",
                  "feature_schema_id": "cltd3vkc1019r07ts2lru4hi4",
                  "name": "bounding_box",
                  "value": "bounding_box",
                  "annotation_kind": "ImageBoundingBox",
                  "classifications": [],
                  "bounding_box": {
                    "top": 1264.0,
                    "left": 2096.0,
                    "height": 425.0,
                    "width": 144.0
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2f07dcf78sa4y5",
                  "feature_schema_id": "cltd3vkc201a707ts9ullbhfo",
                  "name": "point",
                  "value": "point",
                  "annotation_kind": "ImagePoint",
                  "classifications": [],
                  "point": {
                    "x": 1166.606,
                    "y": 1441.768
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2h07dc1pxnhoj3",
                  "feature_schema_id": "cltd3vkc1019t07ts2bk6hjjj",
                  "name": "bbox_with_radio_subclass",
                  "value": "bbox_with_radio_subclass",
                  "annotation_kind": "ImageBoundingBox",
                  "classifications": [
                    {
                      "feature_id": "clur5tlyr1n2v07dcbnnfh1ah",
                      "feature_schema_id": "cltd3vkc1019u07tsaari5i2k",
                      "name": "sub_radio_question",
                      "value": "sub_radio_question",
                      "radio_answer": {
                        "feature_id": "clur5tlyr1n3607dc98qpagxb",
                        "feature_schema_id": "cltd3vkc1019v07tsbow08f9u",
                        "name": "first_sub_radio_answer",
                        "value": "first_sub_radio_answer",
                        "classifications": []
                      }
                    }
                  ],
                  "bounding_box": {
                    "top": 933.0,
                    "left": 541.0,
                    "height": 191.0,
                    "width": 330.0
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2j07dc50cs4e11",
                  "feature_schema_id": "cltd3vkc201a907ts69dr5m86",
                  "name": "polyline",
                  "value": "polyline",
                  "annotation_kind": "ImagePolyline",
                  "classifications": [],
                  "line": [
                    {
                      "x": 2534.353,
                      "y": 249.471
                    },
                    {
                      "x": 2429.492,
                      "y": 182.092
                    },
                    {
                      "x": 2294.322,
                      "y": 221.962
                    },
                    {
                      "x": 2224.491,
                      "y": 180.463
                    },
                    {
                      "x": 2136.123,
                      "y": 204.716
                    },
                    {
                      "x": 1712.247,
                      "y": 173.949
                    },
                    {
                      "x": 1703.838,
                      "y": 84.438
                    },
                    {
                      "x": 1579.772,
                      "y": 82.61
                    },
                    {
                      "x": 1583.442,
                      "y": 167.552
                    },
                    {
                      "x": 1478.869,
                      "y": 164.903
                    },
                    {
                      "x": 1418.941,
                      "y": 318.149
                    },
                    {
                      "x": 1243.128,
                      "y": 400.815
                    },
                    {
                      "x": 1022.067,
                      "y": 319.007
                    },
                    {
                      "x": 892.367,
                      "y": 379.216
                    },
                    {
                      "x": 670.273,
                      "y": 364.408
                    },
                    {
                      "x": 613.114,
                      "y": 288.16
                    },
                    {
                      "x": 377.559,
                      "y": 238.251
                    },
                    {
                      "x": 368.087,
                      "y": 185.064
                    },
                    {
                      "x": 246.557,
                      "y": 167.286
                    },
                    {
                      "x": 236.648,
                      "y": 285.61
                    },
                    {
                      "x": 90.929,
                      "y": 326.412
                    }
                  ]
                },
                {
                  "feature_id": "clur5tlyr1n2l07dc1jsf15qo",
                  "feature_schema_id": "cltd3vkc1019r07ts2lru4hi4",
                  "name": "bounding_box",
                  "value": "bounding_box",
                  "annotation_kind": "ImageBoundingBox",
                  "classifications": [],
                  "bounding_box": {
                    "top": 1346.0,
                    "left": 2272.0,
                    "height": 358.0,
                    "width": 144.0
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2m07dc4x6xhzep",
                  "feature_schema_id": "cltd3vkc1019z07ts7g1n3o5m",
                  "name": "polygon",
                  "value": "polygon",
                  "annotation_kind": "ImagePolygon",
                  "classifications": [],
                  "polygon": [
                    {
                      "x": 1489.581,
                      "y": 183.934
                    },
                    {
                      "x": 2278.306,
                      "y": 256.885
                    },
                    {
                      "x": 2428.197,
                      "y": 200.437
                    },
                    {
                      "x": 2560.0,
                      "y": 335.419
                    },
                    {
                      "x": 2557.386,
                      "y": 503.165
                    },
                    {
                      "x": 2320.596,
                      "y": 503.103
                    },
                    {
                      "x": 2156.083,
                      "y": 628.943
                    },
                    {
                      "x": 2161.111,
                      "y": 785.519
                    },
                    {
                      "x": 2002.115,
                      "y": 894.647
                    },
                    {
                      "x": 1838.456,
                      "y": 877.874
                    },
                    {
                      "x": 1436.53,
                      "y": 874.636
                    },
                    {
                      "x": 1411.403,
                      "y": 758.579
                    },
                    {
                      "x": 1353.853,
                      "y": 751.74
                    },
                    {
                      "x": 1345.264,
                      "y": 453.461
                    },
                    {
                      "x": 1426.011,
                      "y": 421.129
                    },
                    {
                      "x": 1489.581,
                      "y": 183.934
                    }
                  ]
                },
                {
                  "feature_id": "clur5tlyr1n2n07dc4qot5gbx",
                  "feature_schema_id": "cltd3vkc1019r07ts2lru4hi4",
                  "name": "bounding_box",
                  "value": "bounding_box",
                  "annotation_kind": "ImageBoundingBox",
                  "classifications": [],
                  "bounding_box": {
                    "top": 977.0,
                    "left": 1690.0,
                    "height": 330.0,
                    "width": 225.0
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2q07dc5joc4k7u",
                  "feature_schema_id": "cltd3vkc101a107ts95sk63u0",
                  "name": "mask",
                  "value": "mask",
                  "annotation_kind": "ImageSegmentationMask",
                  "classifications": [],
                  "mask": {
                    "url": "https://api.labelbox.com/api/v1/projects/cltd3vkju021907u63w2odj69/annotations/clur5tlyr1n2q07dc5joc4k7u/index/1/mask"
                  },
                  "composite_mask": {
                    "url": "https://api.labelbox.com/api/v1/tasks/clur6dp8r04ul07wrgp9q4pla/masks/clur5tlyr1n2o07dc99lw3r8p/index/1",
                    "color_rgb": [
                      10,
                      10,
                      125
                    ]
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2r07dc6ym4d4mc",
                  "feature_schema_id": "cltd3vkc201a307tsforlev07",
                  "name": "mask_with_text_subclass",
                  "value": "mask_with_text_subclass",
                  "annotation_kind": "ImageSegmentationMask",
                  "classifications": [
                    {
                      "feature_id": "clur5tlyr1n2x07dc84a12l8i",
                      "feature_schema_id": "cltd3vkc201a407tsfo3agh7x",
                      "name": "sub_free_text",
                      "value": "sub_free_text",
                      "text_answer": {
                        "content": "free text answer sample"
                      }
                    }
                  ],
                  "mask": {
                    "url": "https://api.labelbox.com/api/v1/projects/cltd3vkju021907u63w2odj69/annotations/clur5tlyr1n2r07dc6ym4d4mc/index/1/mask"
                  },
                  "composite_mask": {
                    "url": "https://api.labelbox.com/api/v1/tasks/clur6dp8r04ul07wrgp9q4pla/masks/clur5tlyr1n2o07dc99lw3r8p/index/1",
                    "color_rgb": [
                      105,
                      136,
                      97
                    ]
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2s07dc739a6kqs",
                  "feature_schema_id": "cltd3vkc201a307tsforlev07",
                  "name": "mask_with_text_subclass",
                  "value": "mask_with_text_subclass",
                  "annotation_kind": "ImageSegmentationMask",
                  "classifications": [
                    {
                      "feature_id": "clur5tlyr1n2w07dccdv0g7gg",
                      "feature_schema_id": "cltd3vkc201a407tsfo3agh7x",
                      "name": "sub_free_text",
                      "value": "sub_free_text",
                      "text_answer": {
                        "content": "free text answer sample"
                      }
                    }
                  ],
                  "mask": {
                    "url": "https://api.labelbox.com/api/v1/projects/cltd3vkju021907u63w2odj69/annotations/clur5tlyr1n2s07dc739a6kqs/index/1/mask"
                  },
                  "composite_mask": {
                    "url": "https://api.labelbox.com/api/v1/tasks/clur6dp8r04ul07wrgp9q4pla/masks/clur5tlyr1n2o07dc99lw3r8p/index/1",
                    "color_rgb": [
                      7,
                      85,
                      11
                    ]
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2t07dc0oxlgoc8",
                  "feature_schema_id": "cltd3vkc201a307tsforlev07",
                  "name": "mask_with_text_subclass",
                  "value": "mask_with_text_subclass",
                  "annotation_kind": "ImageSegmentationMask",
                  "classifications": [
                    {
                      "feature_id": "clur5tlyr1n3107dccy5pbudr",
                      "feature_schema_id": "cltd3vkc201a407tsfo3agh7x",
                      "name": "sub_free_text",
                      "value": "sub_free_text",
                      "text_answer": {
                        "content": "free text answer sample"
                      }
                    }
                  ],
                  "mask": {
                    "url": "https://api.labelbox.com/api/v1/projects/cltd3vkju021907u63w2odj69/annotations/clur5tlyr1n2t07dc0oxlgoc8/index/1/mask"
                  },
                  "composite_mask": {
                    "url": "https://api.labelbox.com/api/v1/tasks/clur6dp8r04ul07wrgp9q4pla/masks/clur5tlyr1n2o07dc99lw3r8p/index/1",
                    "color_rgb": [
                      35,
                      34,
                      212
                    ]
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2u07dc5wjmdm3v",
                  "feature_schema_id": "cltd3vkc101a107ts95sk63u0",
                  "name": "mask",
                  "value": "mask",
                  "annotation_kind": "ImageSegmentationMask",
                  "classifications": [],
                  "mask": {
                    "url": "https://api.labelbox.com/api/v1/projects/cltd3vkju021907u63w2odj69/annotations/clur5tlyr1n2u07dc5wjmdm3v/index/1/mask"
                  },
                  "composite_mask": {
                    "url": "https://api.labelbox.com/api/v1/tasks/clur6dp8r04ul07wrgp9q4pla/masks/clur5tlyr1n2o07dc99lw3r8p/index/1",
                    "color_rgb": [
                      232,
                      194,
                      86
                    ]
                  }
                }
              ],
              "classifications": [
                {
                  "feature_id": "clur5tlyr1n2e07dc2bez8p1u",
                  "feature_schema_id": "cltd3vkc201ar07ts3gq6a6sn",
                  "name": "nested_radio_question",
                  "value": "nested_radio_question",
                  "radio_answer": {
                    "feature_id": "clur5tlyr1n3307dcexth5ff7",
                    "feature_schema_id": "cltd3vkc201as07tsh2prgosu",
                    "name": "first_radio_answer",
                    "value": "first_radio_answer",
                    "classifications": [
                      {
                        "feature_id": "clur5tlyr1n3407dc306b5xib",
                        "feature_schema_id": "cltd3vkc201at07tsdjx9dlbw",
                        "name": "sub_radio_question",
                        "value": "sub_radio_question",
                        "radio_answer": {
                          "feature_id": "clur5tlyr1n3507dcef304jmb",
                          "feature_schema_id": "cltd3vkc201au07ts7nk47qny",
                          "name": "first_sub_radio_answer",
                          "value": "first_sub_radio_answer",
                          "classifications": []
                        }
                      }
                    ]
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2g07dc7wdv7p5z",
                  "feature_schema_id": "cltd3vkc201ap07ts58gma0bb",
                  "name": "free_text",
                  "value": "free_text",
                  "text_answer": {
                    "content": "sample text"
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2i07dcd8lx87be",
                  "feature_schema_id": "cltd3vkc201az07ts7st3fn79",
                  "name": "nested_checklist_question",
                  "value": "nested_checklist_question",
                  "checklist_answers": [
                    {
                      "feature_id": "clur5tlyr1n3207dc4u4nfg08",
                      "feature_schema_id": "cltd3vkc201b007tsdhs07baf",
                      "name": "first_checklist_answer",
                      "value": "first_checklist_answer",
                      "classifications": [
                        {
                          "feature_id": "clur5tlyr1n3707dc2cy805ac",
                          "feature_schema_id": "cltd3vkc201b107ts12b1al1j",
                          "name": "sub_checklist_question",
                          "value": "sub_checklist_question",
                          "checklist_answers": [
                            {
                              "feature_id": "clur5tlyr1n3807dcgpgih5qj",
                              "feature_schema_id": "cltd3vkc201b207ts434b9iyx",
                              "name": "first_sub_checklist_answer",
                              "value": "first_sub_checklist_answer",
                              "classifications": []
                            }
                          ]
                        }
                      ]
                    }
                  ]
                },
                {
                  "feature_id": "clur5tlyr1n2k07dcezk08npu",
                  "feature_schema_id": "cltd3vkc201ad07ts3t78873p",
                  "name": "radio_question",
                  "value": "radio_question",
                  "radio_answer": {
                    "feature_id": "clur5tlyr1n2y07dcajpyg0d4",
                    "feature_schema_id": "cltd3vkc201ag07tsfoc2bdpi",
                    "name": "second_radio_answer",
                    "value": "second_radio_answer",
                    "classifications": []
                  }
                },
                {
                  "feature_id": "clur5tlyr1n2p07dchs791672",
                  "feature_schema_id": "cltd3vkc201aj07tsait4cbzh",
                  "name": "checklist_question",
                  "value": "checklist_question",
                  "checklist_answers": [
                    {
                      "feature_id": "clur5tlyr1n2z07dc3abv19e8",
                      "feature_schema_id": "cltd3vkc201ak07tsfqxc740z",
                      "name": "first_checklist_answer",
                      "value": "first_checklist_answer",
                      "classifications": []
                    },
                    {
                      "feature_id": "clur5tlyr1n3007dc4vbr0628",
                      "feature_schema_id": "cltd3vkc201am07ts7s9e7x7k",
                      "name": "second_checklist_answer",
                      "value": "second_checklist_answer",
                      "classifications": []
                    }
                  ]
                }
              ],
              "relationships": [
                {
                  "feature_id": "clur69pfa00023b6rkftlkucz",
                  "feature_schema_id": "cltd3vkc201ab07ts1f9dhpkt",
                  "name": "relationship",
                  "value": "relationship",
                  "annotation_kind": "ImageUnidirectionalRelationship",
                  "classifications": [],
                  "unidirectional_relationship": {
                    "source": "clur5tlyq1n2d07dcg9xldg90",
                    "target": "clur5tlyr1n2l07dc1jsf15qo"
                  }
                }
              ]
            },
            "z_order": [
                "clur5tlyq1n2d07dcg9xldg90",
                "clur5tlyr1n2f07dcf78sa4y5",
                "clur5tlyr1n2j07dc50cs4e11",
                "clur5tlyr1n2l07dc1jsf15qo",
                "clur5tlyr1n2m07dc4x6xhzep",
                "clur5tlyr1n2n07dc4qot5gbx",
                "clur5tlyr1n2q07dc5joc4k7u",
                "clur5tlyr1n2r07dc6ym4d4mc",
                "clur5tlyr1n2s07dc739a6kqs",
                "clur5tlyr1n2u07dc5wjmdm3v"
            ]
          }
        ],
        "project_details": {
          "ontology_id": "cltd3vkbb019q07ts23eedy4o",
          "task_id": "a384279a-45c0-4200-b85a-3c18469b3809",
          "task_name": "Initial review task",
          "batch_id": "3f724e20-da3d-11ee-86a4-0145011952fd",
          "batch_name": "image-demo-batch",
          "workflow_status": "IN_REVIEW",
          "priority": 1,
          "consensus_expected_label_count": 1,
          "workflow_history": [
            {
              "action": "Move",
              "created_at": "2024-04-08T16:21:26.492+00:00",
              "created_by": "[email protected]",
              "previous_task_name": "Initial labeling task",
              "previous_task_id": "22ee463b-fbe3-0791-8159-94083be9dee3",
              "next_task_name": "Initial review task",
              "next_task_id": "a384279a-45c0-4200-b85a-3c18469b3809"
            },
            {
              "action": "Move",
              "created_at": "2024-04-08T16:21:26.481+00:00",
              "created_by": "[email protected]",
              "next_task_name": "Initial labeling task",
              "next_task_id": "22ee463b-fbe3-0791-8159-94083be9dee3"
            }
          ]
        },
        "project_tags": []
      }
    }
  }
  ```
</CodeGroup>

## Sample model run export

<CodeGroup>
  ```json JSON expandable theme={null}
  {
    "data_row": {
      "id": "clo78lhhn3dxb07322mnn8plu",
      "global_key": "2560px-Kitano_Street_Kobe01s.jpeg",
      "row_data": "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg",
      "details": {
        "dataset_id": "clo78lg8f003007321fe52lje",
        "dataset_name": "image_prediction_demo",
        "created_at": "2023-10-26T13:45:24.929+00:00",
        "updated_at": "2023-10-26T13:45:25.965+00:00",
        "created_by": "[email protected]"
      }
    },
    "media_attributes": {
      "height": 1707,
      "width": 2560,
      "mime_type": "image/jpeg",
      "exif_rotation": "1"
    },
    "attachments": [],
    "metadata_fields": [],
     "embeddings": [
      {
        "id": "cn1cywy1r077807zblvo0m884",
        "name": "my_custom_embedding_2048_dimensions",
        "dimensions": 2048,
        "is_custom": true,
        "values": [
          {
            "value": [
              1.1265901290930636,
              1.0413733599834287,
              1.3041214120015427,
              1.893491997791636 ...
            ]
          }
        ]
      },
      {
        "id": "c200000000000000000000000",
        "name": "Image Embedding V2 (CLIP ViT-B/32)",
        "dimensions": 512,
        "is_custom": false,
        "values": [
          {
            "value": [
              -0.4192526042461395,
              -0.048827216029167175 ...
            ]
          }
        ]
      }
    ],
    "experiments": {
      "a2fb1fec-83fb-0858-2cfb-98f4757eae95": {
        "name": "image_model_run_3e5bf56c-31a4-4eed-a731-9ca85e783225",
        "runs": {
          "a2fb1fec-b8a5-0f96-b61e-0d5643fb8dec": {
            "name": "iteration 1",
            "run_data_row_id": "42630da9-0dc4-462b-9aa0-5a17e85ff46a",
            "labels": [
              {
                "label_kind": "Default",
                "version": "1.0.0",
                "id": "clpk3h87e005r14vsp4c33sfq",
                "annotations": {
                  "objects": [
                    {
                      "feature_id": "164937d0-7bb2-0f03-8031-34b57799736b",
                      "feature_schema_id": "clpk3gs0t054y07vig605dopr",
                      "name": "polygon",
                      "value": "polygon",
                      "annotation_kind": "ImagePolygon",
                      "classifications": [],
                      "polygon": [
                        {
                          "x": 1489.581,
                          "y": 183.934
                        },
                        {
                          "x": 2278.306,
                          "y": 256.885
                        },
                        {
                          "x": 2428.197,
                          "y": 200.437
                        },
                        {
                          "x": 2560.0,
                          "y": 335.419
                        },
                        {
                          "x": 2557.386,
                          "y": 503.165
                        },
                        {
                          "x": 2320.596,
                          "y": 503.103
                        },
                        {
                          "x": 2156.083,
                          "y": 628.943
                        },
                        {
                          "x": 2161.111,
                          "y": 785.519
                        },
                        {
                          "x": 2002.115,
                          "y": 894.647
                        },
                        {
                          "x": 1838.456,
                          "y": 877.874
                        },
                        {
                          "x": 1436.53,
                          "y": 874.636
                        },
                        {
                          "x": 1411.403,
                          "y": 758.579
                        },
                        {
                          "x": 1353.853,
                          "y": 751.74
                        },
                        {
                          "x": 1345.264,
                          "y": 453.461
                        },
                        {
                          "x": 1426.011,
                          "y": 421.129
                        },
                        {
                          "x": 1489.581,
                          "y": 183.934
                        }
                      ]
                    },
                    {
                      "feature_id": "2738b5f8-e586-0090-974a-59b6c9b46ee2",
                      "feature_schema_id": "clpk3gs0t055207vi1baq8bke",
                      "name": "mask_with_text_subclass",
                      "value": "mask_with_text_subclass",
                      "annotation_kind": "ImageSegmentationMask",
                      "classifications": [
                        {
                          "feature_id": "9001b75c-bb70-0b40-afbf-9479ecfa9f99",
                          "feature_schema_id": "clpk3gs0t055307vi90s32rhi",
                          "name": "sub_free_text",
                          "value": "sub_free_text",
                          "text_answer": {
                            "content": "free text answer"
                          }
                        }
                      ],
                      "mask": {
                        "url": "https://api.labelbox.com/api/v1/models/a2fb1fec-83fb-0858-2cfb-98f4757eae95/annotations/2738b5f8-e586-0090-974a-59b6c9b46ee2/index/1/mask"
                      },
                      "composite_mask": {
                        "url": "https://api.labelbox.com/api/v1/tasks/clur6mb7a0dz107xod5w53p61/masks/clpk3h7uk005114vsgru34yw7/index/1",
                        "color_rgb": [
                          41,
                          24,
                          175
                        ]
                      }
                    },
                    {
                      "feature_id": "4defcaa5-623f-0589-932a-b703e1116fa4",
                      "feature_schema_id": "clpk3gs0t055807vi49uy1rcm",
                      "name": "polyline",
                      "value": "polyline",
                      "annotation_kind": "ImagePolyline",
                      "classifications": [],
                      "line": [
                        {
                          "x": 2534.353,
                          "y": 249.471
                        },
                        {
                          "x": 2429.492,
                          "y": 182.092
                        },
                        {
                          "x": 2294.322,
                          "y": 221.962
                        },
                        {
                          "x": 2224.491,
                          "y": 180.463
                        },
                        {
                          "x": 2136.123,
                          "y": 204.716
                        },
                        {
                          "x": 1712.247,
                          "y": 173.949
                        },
                        {
                          "x": 1703.838,
                          "y": 84.438
                        },
                        {
                          "x": 1579.772,
                          "y": 82.61
                        },
                        {
                          "x": 1583.442,
                          "y": 167.552
                        },
                        {
                          "x": 1478.869,
                          "y": 164.903
                        },
                        {
                          "x": 1418.941,
                          "y": 318.149
                        },
                        {
                          "x": 1243.128,
                          "y": 400.815
                        },
                        {
                          "x": 1022.067,
                          "y": 319.007
                        },
                        {
                          "x": 892.367,
                          "y": 379.216
                        },
                        {
                          "x": 670.273,
                          "y": 364.408
                        },
                        {
                          "x": 613.114,
                          "y": 288.16
                        },
                        {
                          "x": 377.559,
                          "y": 238.251
                        },
                        {
                          "x": 368.087,
                          "y": 185.064
                        },
                        {
                          "x": 246.557,
                          "y": 167.286
                        },
                        {
                          "x": 236.648,
                          "y": 285.61
                        },
                        {
                          "x": 90.929,
                          "y": 326.412
                        }
                      ]
                    },
                    {
                      "feature_id": "7d129546-45a6-060b-918e-35caec234d31",
                      "feature_schema_id": "clpk3gs0s054s07vi3ddo8had",
                      "name": "bbox_with_radio_subclass",
                      "value": "bbox_with_radio_subclass",
                      "annotation_kind": "ImageBoundingBox",
                      "classifications": [
                        {
                          "feature_id": "cccba37c-b7a8-095b-8679-dd20aece6f90",
                          "feature_schema_id": "clpk3gs0s054t07vi17aih47e",
                          "name": "sub_radio_question",
                          "value": "sub_radio_question",
                          "radio_answer": {
                            "feature_id": "ea336ea5-041c-02b6-9e8b-6ac1098351b1",
                            "feature_schema_id": "clpk3gs0s054u07vicrttdlgj",
                            "name": "first_sub_radio_answer",
                            "value": "first_sub_radio_answer",
                            "classifications": []
                          }
                        }
                      ],
                      "bounding_box": {
                        "top": 933.0,
                        "left": 541.0,
                        "height": 191.0,
                        "width": 330.0
                      }
                    },
                    {
                      "feature_id": "a3e0496d-3963-0d40-af89-48a907fbb48d",
                      "feature_schema_id": "clpk3gs0s054q07vi3c30d1be",
                      "name": "bounding_box",
                      "value": "bounding_box",
                      "annotation_kind": "ImageBoundingBox",
                      "classifications": [],
                      "bounding_box": {
                        "top": 977.0,
                        "left": 1690.0,
                        "height": 330.0,
                        "width": 225.0
                      }
                    },
                    {
                      "feature_id": "f2fc7c1f-7f10-0fc2-b676-fa2591f51a27",
                      "feature_schema_id": "clpk3gs0t055607vi59sshqn0",
                      "name": "point",
                      "value": "point",
                      "annotation_kind": "ImagePoint",
                      "classifications": [],
                      "point": {
                        "x": 1166.606,
                        "y": 1441.768
                      }
                    },
                    {
                      "feature_id": "fb60f23f-8ae1-05b3-a4d8-353839975d59",
                      "feature_schema_id": "clpk3gs0t055007vi4h7fgm59",
                      "name": "mask",
                      "value": "mask",
                      "annotation_kind": "ImageSegmentationMask",
                      "classifications": [],
                      "mask": {
                        "url": "https://api.labelbox.com/api/v1/models/a2fb1fec-83fb-0858-2cfb-98f4757eae95/annotations/fb60f23f-8ae1-05b3-a4d8-353839975d59/index/1/mask"
                      },
                      "composite_mask": {
                        "url": "https://api.labelbox.com/api/v1/tasks/clur6mb7a0dz107xod5w53p61/masks/clpk3h7uk005114vsgru34yw7/index/1",
                        "color_rgb": [
                          186,
                          26,
                          40
                        ]
                      }
                    }
                  ],
                  "classifications": [
                    {
                      "feature_id": "1be71b85-08da-0ade-bbe4-cfdd431d3e8a",
                      "feature_schema_id": "clpk3gs0t055g07viaine2doh",
                      "name": "checklist_question",
                      "value": "checklist_question",
                      "checklist_answers": [
                        {
                          "feature_id": "0104948e-7be5-032d-80ca-87d052346618",
                          "feature_schema_id": "clpk3gs0t055j07vi4h3y9wso",
                          "name": "second_checklist_answer",
                          "value": "second_checklist_answer",
                          "classifications": []
                        },
                        {
                          "feature_id": "cb587406-5db3-0de2-99f0-cf6e6c344f43",
                          "feature_schema_id": "clpk3gs0t055h07vi1hp0acnb",
                          "name": "first_checklist_answer",
                          "value": "first_checklist_answer",
                          "classifications": []
                        }
                      ]
                    },
                    {
                      "feature_id": "5b1f4994-1bad-03a1-bf0f-1a0b4682ea25",
                      "feature_schema_id": "clpk3gs0t055m07vi53ow6auc",
                      "name": "free_text",
                      "value": "free_text",
                      "text_answer": {
                        "content": "sample text"
                      }
                    },
                    {
                      "feature_id": "88f8cd4d-e1ca-0add-a7e8-a7349def31bc",
                      "feature_schema_id": "clpk3gs0t055a07vifk5701ua",
                      "name": "radio_question",
                      "value": "radio_question",
                      "radio_answer": {
                        "feature_id": "ee141c0d-064f-0de8-b746-e61ac14fbe62",
                        "feature_schema_id": "clpk3gs0t055d07vibryq8f4l",
                        "name": "second_radio_answer",
                        "value": "second_radio_answer",
                        "classifications": []
                      }
                    },
                    {
                      "feature_id": "cc8e57d8-5080-0b43-bab1-6e4d78b684de",
                      "feature_schema_id": "clpk3gs0t055o07vifjxs63xi",
                      "name": "nested_radio_question",
                      "value": "nested_radio_question",
                      "radio_answer": {
                        "feature_id": "81690da4-5cb5-037f-9a7b-3dd7fefc5481",
                        "feature_schema_id": "clpk3gs0t055p07vigvkkeii3",
                        "name": "first_radio_answer",
                        "value": "first_radio_answer",
                        "classifications": [
                          {
                            "feature_id": "37453082-23dd-0c38-bdcb-90705102bc6e",
                            "feature_schema_id": "clpk3gs0t055q07vifyau26jb",
                            "name": "sub_radio_question",
                            "value": "sub_radio_question",
                            "radio_answer": {
                              "feature_id": "4b014520-7193-04d9-8d69-f800316b60f2",
                              "feature_schema_id": "clpk3gs0t055r07vi406q70ga",
                              "name": "first_sub_radio_answer",
                              "value": "first_sub_radio_answer",
                              "classifications": []
                            }
                          }
                        ]
                      }
                    },
                    {
                      "feature_id": "f1d18441-41cd-0ff7-9f4f-75384e5a7b51",
                      "feature_schema_id": "clpk3gs0u055w07vifjngez8o",
                      "name": "nested_checklist_question",
                      "value": "nested_checklist_question",
                      "checklist_answers": [
                        {
                          "feature_id": "a3c8745f-8151-0256-8b6d-8ac449797fd7",
                          "feature_schema_id": "clpk3gs0u055x07vibwdt1pk3",
                          "name": "first_checklist_answer",
                          "value": "first_checklist_answer",
                          "classifications": [
                            {
                              "feature_id": "aa00a3ff-1af4-038a-9be5-97a468656bc5",
                              "feature_schema_id": "clpk3gs0u055y07vi3srh1g0l",
                              "name": "sub_checklist_question",
                              "value": "sub_checklist_question",
                              "checklist_answers": [
                                {
                                  "feature_id": "0608a0d7-d9d9-0347-843b-3297e58a25dc",
                                  "feature_schema_id": "clpk3gs0u055z07vifkpvgap4",
                                  "name": "first_sub_checklist_answer",
                                  "value": "first_sub_checklist_answer",
                                  "classifications": []
                                }
                              ]
                            }
                          ]
                        }
                      ]
                    }
                  ],
                  "relationships": []
                }
              }
            ],
            "predictions": [
              {
                "label_kind": "Default",
                "version": "1.0.0",
                "id": "clpk3h87e005r14vsp4c33sfq",
                "annotations": {
                  "objects": [
                    {
                      "feature_id": "028389ae-93ff-4614-a37e-e867a310371c",
                      "feature_schema_id": "clpk3gs0s054q07vi3c30d1be",
                      "name": "bounding_box",
                      "value": "bounding_box",
                      "annotation_kind": "ImageBoundingBox",
                      "classifications": [],
                      "bounding_box": {
                        "top": 977.0,
                        "left": 1690.0,
                        "height": 330.0,
                        "width": 225.0
                      }
                    },
                    {
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    },
    "models": {}
  }
  ```
</CodeGroup>
