How to export image annotations and sample export formats.
Open this Colab for an interactive tutorial on exporting annotations.
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,
"label_details": True,
"performance_details": 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": "Done"
}
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)
labels = project.export_labels(download=True)
# Optionally, provide a date range as an optional parameter
# This will export only labels created between the supplied dates
# Date range can be formatted as "YYYY-MM-DD" or "YYYY-MM-DD hh:mm:ss"
labels = project.export_labels(download=True, start="2022-09-28", end="2022-10-04")
Annotation export formats
Bounding box
{
"feature_id": "clkmxp0cd00033b6l8stcqsrv",
"feature_schema_id": "clgz75v2k008o0710bittgnxl",
"name": "bounding_box",
"annotation_kind": "ImageBoundingBox",
"classifications": [],
"bounding_box": {
"top": 977,
"left": 1690,
"height": 330,
"width": 225
}
}
{
"featureId": "ck9bmeej61emf0yf5bgjb4tjw",
"schemaId": "ck9blmq1lnlxw08895jy7zsk4",
"title": "Blue bird",
"value": "blue_bird",
"color": "#FF8000",
"bbox": {
"top": 186,
"left": 192,
"height": 300,
"width": 519
}
}
Cuboid
{
"featureId": "cl8xbe6ji00013b6jityjn1vjk",
"schemaId": "cl8xbe09b0tbe07zs3kdna7xa",
"color": "#1CE6FF",
"title": "cuboid",
"value": "cuboid",
"cuboid": {
"center": {
"x": 589.1436087437497,
"y": 301.76757252135343
},
"rotation": {
"x": -0.23864773605446826,
"y": 0.30897007369484236,
"z": 0.6676434268107659
},
"size": {
"x": 25,
"y": 25,
"z": 35
},
"projection": "orthographic",
"front": {
"top_left": {
"x": 591.3950896879612,
"y": 290.64520273387444
},
"top_right": {
"x": 609.9605298942264,
"y": 304.8447036383389
},
"bottom_left": {
"x": 575.442287473622,
"y": 309.66849343648477
},
"bottom_right": {
"x": 594.0077276798871,
"y": 323.8679943409492
}
},
"back": {
"top_left": {
"x": 584.2794898076123,
"y": 279.66715070175763
},
"top_right": {
"x": 602.8449300138775,
"y": 293.8666516062221
},
"bottom_left": {
"x": 568.326687593273,
"y": 298.69044140436796
},
"bottom_right": {
"x": 586.8921277995382,
"y": 312.8899423088324
}
}
},
"instanceURI": "https://api.labelbox.com/masks/feature/cl8xbe6ji00013b6jityjn1vjk?token=eyJhbGciOiJIUzI1NiIsInkgkfjg6IkpXVCJ9.eyJ1c2VySWQiOiJjbDc1Znp0dmszbmljMDd6bjR1Mm1mN3ZrIiwib3JnYW5pemF0aW9uSWQiOiJjbDc1Znp0djkzbmliMDd6bmJndnYwMGw4IiwiaWF0IjoxNjY1MDc2NTI1LCJleHAiOjE2Njc2Njg1MjV9.1BeHjFyzzYCarcELRk6uh1lhioyjghKaej8r4othtKoNM"
}
Polygon
{
"feature_id": "clkmxp1r600063b6l7cv2qhdj",
"feature_schema_id": "clgz75v2l008w0710b8oh5k0t",
"name": "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,
"y": 335.419
},
{
"x": 1345.264,
"y": 453.461
},
{
"x": 1426.011,
"y": 421.129
},
{
"x": 1489.581,
"y": 183.934
}
]
}
{
"featureId": "ck9blnafk1d070yf5bhq4q1fv",
"schemaId": "ck9blmq1lnlxv0889cu4r18mx",
"title": "Black bird",
"value": "black_bird",
"color": "#006FA6",
"polygon": [
{
"x": 3665.814,
"y": 351.628
},
{
"x": 3762.93,
"y": 810.419
},
{
"x": 3042.93,
"y": 914.233
},
{
"x": 2996.047,
"y": 864
},
{
"x": 3036.233,
"y": 753.488
}
],
"instanceURI": "https://api.labelbox.com/masks/feature/ckmuuwhfh00083g68sdwpwa04?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3MDM4NDAwLCJleHAiOjE2MTk2MzA0MDB9.5YaORL6mWpPqgAb6IbWChm4MQo14obOU8LFWbfCEHR0"
}
Polyline
{
"feature_id": "cldne8lok01wb13ydkjk4vt0f",
"feature_schema_id": "clgz75v2m009207106kvj5jh2",
"name": "polyline",
"annotation_kind": "ImagePolyline",
"classifications": [],
"line": [
{
"x": 2534.353,
"y": 249.471
},
{
"x": 2429.492,
"y": 182.092
},
{
"x": 1703.838,
"y": 84.438
},
{
"x": 236.648,
"y": 285.61
},
{
"x": 90.929,
"y": 326.412
}
]
}
{
"featureId": "ckmuuwb1p00073g68vg3t615r",
"schemaId": "ckmuuvs5r5njc0y623c4s1dob",
"title": "Tree branch",
"value": "tree_branch",
"color": "#008941",
"line": [
{
"x": 198.027,
"y": 1979.196
},
{
"x": 321.472,
"y": 1801.743
},
{
"x": 465.491,
"y": 1655.152
}
],
}
Point
{
"feature_id": "clkmxp37q00093b6l7cya4u0s",
"feature_schema_id": "clgz75v2l0090071079smgebc",
"name": "point",
"annotation_kind": "ImagePoint",
"classifications": [],
"point": {
"x": 1166.606,
"y": 1441.768
}
}
{
"featureId": "ck9bmemy91hic10bogwc6sygv",
"schemaId": "ck9blmq1lnlxy0889stzln2ms",
"title": "Bird eye",
"value": "bird_eye",
"color": "#D4FF00",
"point": {
"x": 116,
"y": 98
},
"instanceURI": "https://api.labelbox.com/masks/feature/ckmuuw0st00043g68jfguoplb?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3MDM4NDAwLCJleHAiOjE2MTk2MzA0MDB9.5YaORL6mWpPqgAb6IbWChm4MQo14obOU8LFWbfCEHR0"
}
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 AutoSegment, the brush tool, the pen tool, or the fill tool, all masks will take the same format in exports.
{
"feature_id": "cldne8ls7000013yhm5a0rs7c",
"feature_schema_id": "clgz75v2l008y071011it2stu",
"name": "mask",
"annotation_kind": "ImageSegmentationMask",
"classifications": [],
"mask": {
"url": "https://api.labelbox.com/api/v1/projects/<project_id>/annotations/<feature_id>/index/1/mask"
}
}
{
"featureId": "ck9bmetz800340za5k073bm7w",
"schemaId": "ck9blmq1lnlxz08892qqlmxto",
"title": "Orange bird",
"value": "orange_bird",
"color": "#2BFF00",
"instanceURI": "https://api.labelbox.com/masks/feature/ckmuuw2tq00053g68rbwjpoim?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3MDM4NDAwLCJleHAiOjE2MTk2MzA0MDB9.5YaORL6mWpPqgAb6IbWChm4MQo14obOU8LFWbfCEHR0"
}
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
image = Image.open(urllib.request.urlopen(req))
image
Relationship
{
"feature_id": "cll2p55nv000a3b6lta3i8e9h",
"feature_schema_id": "clkl85mti10h507wl49gxfile",
"name": "relationship",
"annotation_kind": "ImageUnidirectionalRelationship",
"classifications": [],
"unidirectional_relationship": {
"source": "cll2p50qa00043b6ljihk0adn",
"target": "cll2p53pi00073b6l6wx78484"
}
}
{
"featureId":"cl12o1opb000g3g6acccvuqui",
"schemaId":"cl12nq1ik004g0z4lf84q58rm",
"data":
{
"source":"cl12nurbd00013g6an63jifsv",
"target":"cl12nv4ab00073g6as6jkwcj3"
},
"relationshipType":"unidirectional",
"version": 1
}
Classification - Radio
{
"feature_id": "clgz76772000n14vmfatp9uy6",
"feature_schema_id": "clgz75v2m00940710fh7u2wt7",
"name": "radio_question",
"radio_answer": {
"feature_id": "clgz76772000o14vmn22j6kqr",
"feature_schema_id": "clgz75v2m00970710ertig931",
"name": "second_radio_answer",
"classifications": []
}
}
{
"featureId": "ckmuuwmp4000a3g68rmku827s",
"schemaId": "ckmuuvs5p5nj40y629l1570bi",
"title": "Is it daytime?",
"value": "is_it_daytime?",
"answer": {
"featureId": "ckmuuwmp400093g68qof3hnt8",
"schemaId": "ckmuuvs7u5njg0y629iiuc216",
"title": "Yes",
"value": "yes"
}
}
Classification - Checklist
{
"feature_id": "clgz76772000t14vm0k2pozsv",
"feature_schema_id": "clgz75v2m009a0710drqi6alc",
"name": "checklist_question",
"checklist_answers": [
{
"feature_id": "clgz76772000u14vm0qx29zr8",
"name": "first_checklist_answer",
"classifications": []
},
{
"feature_id": "clgz76773000v14vmfjhi336q",
"name": "second_checklist_answer",
"classifications": []
}
]
}
{
"featureId": "cl89b1d3g00013b6k8388lpol",
"schemaId": "cl89b186w0xg107xkga0fdf4j",
"scope": "global",
"title": "Attributes",
"value": "attributes",
"answers": [
{
"featureId": "cl89b1dln00033b6ky6j9cb62",
"schemaId": "cl89b186w0xg407xk4yvkf3o8",
"title": "Crowded",
"value": "crowded"
},
{
"featureId": "cl89b1e3z00063b6kll28e559",
"schemaId": "cl89b186w0xg607xk8ogy304a",
"title": "Foot traffic",
"value": "foot_traffic"
},
{
"featureId": "cl89b1ekd000a3b6kbiipqxi7",
"schemaId": "cl89b186w0xg807xke5kg606w",
"title": "Vehicle traffic",
"value": "vehicle_traffic"
}
]
}
Classification - Free-form text
{
"feature_id": "clgz76773001014vmnnf77r4y",
"feature_schema_id": "clgz75v2m009g0710byeu79hm",
"name": "free_text",
"text_answer": {
"content": "sample text"
}
}
{
"featureId": "ckmuzkkhw000a3g68xegct9wz",
"schemaId": "ckmuzjtfa64bq0y839bn8ci4l",
"title": "Free-form text",
"value": "free-form_text",
"answer": "Correct text answer"
}
Sample project export
{
"data_row": {
"id": "cldne7kx70313070d6jr772pr",
"global_key": "95ca3193-ed43-4fdb-bec6-a2e55ee0a58a",
"row_data": "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg",
"details": {
"dataset_id": "cldne7kht0311070dgdth3vu5",
"created_at": "2023-02-02",
"updated_at": "2023-02-02",
"created_by": "[email protected]"
}
},
"media_attributes": {
"height": 1707,
"width": 2560,
"mime_type": "image/jpeg"
},
"attachments": [],
"metadata_fields": [],
"projects": {
"cldne7lhq03ml07ywd2joff88": {
"project_name": "image_annotion_import",
"labels": [
{
"label_kind": "Default",
"version": "1.0.0",
"id": "cldne8lp601wg13ydzhay24e8",
"label_details": {
"created_at": "2023-02-02T17:50:54+00:00",
"updated_at": "2023-02-15T23:32:42+00:00",
"created_by": "[email protected]",
"reviews": []
},
"performance_details": {
"seconds_to_create": 167,
"seconds_to_review": 0,
"skipped": false
},
"annotations": {
"objects": [
{
"feature_id": "cldne8lok01w513ydagy8aifu",
"name": "bounding_box",
"annotation_kind": "ImageBoundingBox",
"classifications": [],
"bounding_box": {
"top": 977.0,
"left": 1690.0,
"height": 330.0,
"width": 225.0
}
},
{
"feature_id": "cldne8lok01w613ydxnt0cr8m",
"name": "bbox_with_radio_subclass",
"annotation_kind": "ImageBoundingBox",
"classifications": [
{
"feature_id": "cldne8lok01w713ydoiibtxcp",
"name": "sub_radio_question",
"radio_answer": {
"feature_id": "cldne8lok01w813ydp7f9rjwt",
"name": "first_sub_radio_answer",
"classifications": []
}
}
],
"bounding_box": {
"top": 933.0,
"left": 541.0,
"height": 191.0,
"width": 330.0
}
},
{
"feature_id": "cldne8lok01w913ydo7olanp5",
"name": "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": "cldne8lok01wa13ydnlp7vexi",
"name": "point",
"annotation_kind": "ImagePoint",
"classifications": [],
"point": {
"x": 1166.606,
"y": 1441.768
}
},
{
"feature_id": "cldne8lok01wb13ydkjk4vt0f",
"name": "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": "cldne8ls7000013yhm5a0rs7c",
"name": "mask",
"annotation_kind": "ImageSegmentationMask",
"classifications": [],
"mask": {
"url": "https://api.lb-stage.xyz/masks/feature/cldne8ls7000013yhm5a0rs7c"
}
},
{
"feature_id": "cle6b609p00013b6jytx5r94a",
"name": "relation_1",
"annotation_kind": "ImageUnidirectionalRelationship",
"classifications": [],
"unidirectional_relationship": {
"source": "cldne8ls7000013yhm5a0rs7c",
"target": "cldne8lok01w613ydxnt0cr8m"
}
}
],
"classifications": [
{
"feature_id": "cldne8lok01vz13ydw0tcq8gm",
"name": "radio_question",
"radio_answer": {
"feature_id": "cldne8lok01w013yd8qr488zr",
"name": "second_radio_answer",
"classifications": []
}
},
{
"feature_id": "cldne8lok01w113ydavz7l6s7",
"name": "checklist_question",
"checklist_answers": [
{
"feature_id": "cldne8lok01w213ydx9oowveg",
"name": "first_checklist_answer",
"classifications": []
},
{
"feature_id": "cldne8lok01w313yd0kujyoj8",
"name": "second_checklist_answer",
"classifications": []
}
]
},
{
"feature_id": "cldne8lok01w413yd5mgbxd66",
"name": "free_text",
"text_answer": {
"content": "sample text"
}
},
{
"feature_id": "cldne8lok01wc13ydrib64w54",
"name": "nested_radio_question",
"radio_answer": {
"feature_id": "cldne8lok01wd13ydya257yv4",
"name": "first_radio_answer",
"classifications": [
{
"feature_id": "cldne8lok01we13yd96g0nwha",
"name": "sub_radio_question",
"radio_answer": {
"feature_id": "cldne8lok01wf13ydg14zgpi9",
"name": "first_sub_radio_answer",
"classifications": []
}
}
]
}
}
],
"relationships": [
{
"feature_id": "cle6b609p00013b6jytx5r94a",
"name": "relation_1",
"annotation_kind": "ImageUnidirectionalRelationship",
"classifications": [],
"unidirectional_relationship": {
"source": "cldne8ls7000013yhm5a0rs7c",
"target": "cldne8lok01w613ydxnt0cr8m"
}
}
]
}
}
],
"project_details": {
"ontology_id": "cldne7l9q033l070k2oeq220q",
"batch_id": "1c8c5d90-a322-11ed-b508-4931e5b4efe3",
"priority": 1,
"consensus_expected_label_count": 1,
"workflow_history": []
}
}
}
}
[
{
"ID": "ckn95nnx000073g68fufpnw7a",
"DataRow ID": "ckn93aswv1nfw0rfz18rq00mt",
"Labeled Data": "https://storage.labelbox.com/ck2yve0h0005b07274s4f0v02%2Fca0697fd-a922-a004-3dfd-4c572921ab2a-eva-waardenburg-v-3NQ3pmWkY-unsplash.jpg?Expires=1598717540394&KeyName=labelbox-assets-key-1&Signature=ozyDhfwJNhP_Yijj4rZIan05nS8",
"Label": {
"objects": [
{
"featureId": "ckn94on8s00013g68cgjl632a",
"schemaId": "ckn94hhay0opt0y6993fb64bl",
"title": "Sample object 1",
"value": "sample_object_1",
"color": "#ffb31c",
"bbox": {
"top": 1099,
"left": 2010,
"height": 690,
"width": 591
},
"instanceURI": "https://api.labelbox.com/masks/feature/ckn94on8s00013g68cgjl632a?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3OTAzMDU5LCJleHAiOjE2MjA0OTUwNTl9.r6Qw2Qx_wbtflEwnZm-7XzPP-AbZn5VuIQ4_ETjBqJc"
},
{
"featureId": "ckn94pfs700033g68hidmdqsg",
"schemaId": "ckn94hhay0opv0y69fbpg76bs",
"title": "Sample object 2",
"value": "sample_object_2",
"color": "#FF34FF",
"instanceURI": "https://api.labelbox.com/masks/feature/ckn94pfs700033g68hidmdqsg?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3OTAzMDU5LCJleHAiOjE2MjA0OTUwNTl9.r6Qw2Qx_wbtflEwnZm-7XzPP-AbZn5VuIQ4_ETjBqJc"
}
],
"classifications": [
{
"featureId": "ckn95n44p00063g682vrko4pp",
"schemaId": "ckn94hhax0opr0y6936u2db78",
"title": "Is it daytime?",
"value": "is_it_daytime?",
"answer": {
"featureId": "ckn95n44o00053g68a1dckji7",
"schemaId": "ckn94hhbn0opx0y69bwh6b3je",
"title": "yes",
"value": "yes"
}
}
]
},
"Created By": "[email protected]",
"Project Name": "Beginner tutorial project",
"Created At": "2021-04-08T17:29:33.000Z",
"Updated At": "2021-04-08T17:30:34.000Z",
"Seconds to Label": 149.852,
"External ID": "layers-testing",
"Agreement": -1,
"Benchmark Agreement": -1,
"Benchmark ID": null,
"Dataset Name": "image-layers-sample.json",
"Reviews": [],
"View Label": "https://editor.labelbox.com?project=ckn889kbvt35m0789527t5rr5&label=ckn95nnx000073g68fufpnw7a",
"Has Open Issues": 0,
"Skipped": false,
"DataRow Workflow Info": {
"taskName": "Done",
"Workflow History": [
{
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"action": "APPROVE",
"createdAt": "2022-09-29T15:46:23.269Z",
"previousTaskId": "0ae49522-97f0-4a07-96c6-bd4d50963acd",
"previousTaskName": "Initial review task"
},
{
"actorId": "cl3lobugu14pw0796fau0dgad",
"action": "REWORK",
"createdAt": "2022-09-29T14:23:59.735Z",
"previousTaskId": "4a0d7f40-0c3f-0cc8-adc4-fd818684facd",
"previousTaskName": "Rework (all rejected)",
"nextTaskId": "0ae49522-97f0-4a07-96c6-bd4d50963acd",
"nextTaskName": "Initial review task"
},
{
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"action": "REJECT",
"createdAt": "2022-09-29T13:39:01.077Z",
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"previousTaskName": "Initial review task",
"nextTaskId": "4a0d7f40-0c3f-0cc8-adc4-fd818684facd",
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},
{
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"action": "MOVE",
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},
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"nextTaskId": "ea78e526-e429-002e-8b80-b72c4b591152",
"nextTaskName": "Initial labeling task"
}
]
}
}
]
Sample model run export
{
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"global_key": "5e3648e7-a888-4f03-b3e6-b277d42a795a",
"row_data": "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg",
"details": {
"dataset_id": "cldw8hrhr1r6107xz65bxd2ah",
"created_at": "2023-02-08",
"updated_at": "2023-02-08",
"created_by": "[email protected]"
}
},
"media_attributes": {
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"mime_type": "image/jpeg"
},
"attachments": [],
"metadata_fields": [],
"experiments": {
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"runs": {
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"run_data_row_id": "78e2c7ca-eaba-48da-b582-a1fe5565dea1",
"labels": [
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"version": "1.0.0",
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"classifications": [
{
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"classifications": []
}
}
],
"bounding_box": {
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}
},
{
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},
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}
},
{
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"name": "mask",
"annotation_kind": "ImageSegmentationMask",
"classifications": [],
"mask": {
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}
},
{
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}
},
{
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"name": "free_text",
"text_answer": {
"content": "sample text"
}
},
{
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]
}
},
{
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"name": "nested_checklist_question",
"checklist_answers": [
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}
]
}
]
}
]
},
{
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"name": "checklist_question",
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},
{
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"classifications": []
}
]
}
],
"relationships": []
}
}
],
"predictions": [
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},
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}
}
],
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}
},
{
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}
},
{
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"classifications": [
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},
{
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},
{
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},
{
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}
]
},
{
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"classifications": [
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"radio_answer": {
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}
}
]
}
},
{
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"name": "nested_checklist_question",
"checklist_answers": [
{
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}
]
}
]
}
]
}
],
"relationships": []
}
}
]
}
}
}
}
}