Export as Python Annotation Types
Open a Colab to go through the exercise of exporting video annotations.
label_generator = project.label_generator()
# You can iterate thru the paginated labels from generator
label = next(label_generator)
# View some specific fields of the label instance
print("Label ID:", label.uid)
print("Created By:", label.extra['Created By'])
print("Created At:", label.extra['Created At'])
print("Media Type:", label.extra['media_type'])
print("Reviews:", label.extra['Reviews'])
# You can convert to a LabelList for small to medium-sized datasets.
# This is more convenient than the LabelGenerator, but less memory efficient. Read more about the differences here.
labels = labels.as_list()
Export as 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
{
"featureId": "ck9bmeej61emf0yf5bgjb4tjw",
"schemaId": "ck9blmq1lnlxw08895jy7zsk4",
"title": "Car 1",
"value": "car_1",
"color": "#1CE6FF",
"keyframe": false,
"bbox": {
"top": 1164,
"left": 2538,
"height": 222,
"width": 119
}
}
Segment
segments = [{
"keyframes": [{
"frame": 1,
"bbox": {
"top": 80,
"left": 80,
"height": 80,
"width": 80
}
}, {
"frame": 20,
"bbox": {
"top": 125,
"left": 125,
"height": 200,
"width": 300
}
}]
}, {
"keyframes": [{
"frame": 27,
"bbox": {
"top": 80,
"left": 50,
"height": 80,
"width": 50
}
}]
}]
Point
{
"featureId": "ckmv0r56g00023g68s2dgru6l",
"schemaId": "cklifp8jw0tn40y5p3xtr2kk2",
"title": "right_ear",
"value": "right_ear",
"color": "#1CE6FF",
"keyframe": true,
"point": {
"x": 943,
"y": 500
}
Polyline
{
"featureId": "ckt37btlp00063h6b8srqrsr8",
"schemaId": "ckt09rb8q7zsu0yc24y3w85m5",
"title": "Center lane",
"value": "center_lane",
"color": "#2f05f1",
"keyframe": true,
"line": [{
"x": 661.215,
"y": 2146.298
},
{
"x": 961.767,
"y": 1907.624
},
{
"x": 1262.32,
"y": 1668.95
}
],
"classifications": []
}
Mask
{
"featureId": "ck9bmetz800340za5k073bm7w",
"schemaId": "ck9blmq1lnlxz08892qqlmxto",
"title": "Defect",
"value": "defect",
"color": "#FFD7D2",
"keyframe": "true",
"instanceURI": "https://api.labelbox.com/masks/feature/ckmuuw2tq00053g68rbwjpoim?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNjE3MDM4NDAwLCJleHAiOjE2MTk2MzA0MDB9.5YaORL6mWpPqgAb6IbWChm4MQo14obOU8LFWbfCEHR0"
}
Classification - Radio
// For global classifications, do not include the frames section
{
"schemaId": "ckd1295hc00640z0uapvm1xbd", // question schema id
"uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
"dataRow": {
"id": "ckd1299m8cqbs0cq43mju1bvp"
},
"answer": {
"schemaId": "ckd1295jn00760z0u01hw4yz5" // answer schema id
},
"frames": [
{
"start": 7,
"end": 13,
},
{
"start": 18,
"end": 19,
}
]
}
Classification - Checklist
[
{
"frameNumber": 1,
"classifications": [
{
"featureId": "cl89b9sjb00003b6keuil18qx",
"schemaId": "cl89b9kwz11yj070nhmnscwj4",
"title": "Signs in frame",
"value": "signs_in_frame",
"answers": [
{
"featureId": "cl89b9sjb00013b6kvxfa6gmj",
"schemaId": "cl89b9kwz11yk070na20ngv31",
"title": "Stop",
"value": "stop",
"keyframe": true
},
{
"featureId": "cl89b9tq000023b6ke9jh90ym",
"schemaId": "cl89b9kwz11ym070nbr0m7qbs",
"title": "Yield",
"value": "yield",
"keyframe": true
}
]
}
],
"objects": [],
"relationships": []
},
{
"frameNumber": 2,
"classifications": [
{
"featureId": "cl89b9sjb00003b6keuil18qx",
"schemaId": "cl89b9kwz11yj070nhmnscwj4",
"title": "Signs in frame",
"value": "signs_in_frame",
"answers": [
{
"featureId": "cl89b9sjb00013b6kvxfa6gmj",
"schemaId": "cl89b9kwz11yk070na20ngv31",
"title": "Stop",
"value": "stop",
"keyframe": false
},
{
"featureId": "cl89b9tq000023b6ke9jh90ym",
"schemaId": "cl89b9kwz11ym070nbr0m7qbs",
"title": "Yield",
"value": "yield",
"keyframe": false
}
]
}
],
"objects": [],
"relationships": []
}
]
Sample Label payload - Video
[
{
"ID": "cknp36mns00033g68sqqsq844",
"DataRow ID": "cklifdz2e1yf10rco407yaita",
"Labeled Data": "https://storage.labelbox.com/ck52rvx0mpw4g0766wgqvjtl9%2F98c62818-8aad-2da8-aa86-141fb32742f4-lioness_walking.mp4?Expires=1620075890645&KeyName=labelbox-assets-key-3&Signature=Es1jENXKqKPt4nShF89ASvVmLzE",
"Label": {
"frames": "https://api.labelbox.com/v1/frames/cknp36mns00033g68sqqsq844"
},
"Created By": "[email protected]",
"Project Name": "Lioness walking",
"Created At": "2021-04-19T21:04:38.000Z",
"Updated At": "2021-04-19T21:04:45.000Z",
"Seconds to Label": 20,
"External ID": "lioness_walking.mp4",
"Agreement": -1,
"Benchmark Agreement": -1,
"Benchmark ID": null,
"Dataset Name": "lioness_walking",
"Reviews": [],
"View Label": "https://editor.labelbox.com?project=cklifeflvf7dx0795p3rzpa6g&label=cknp36mns00033g68sqqsq844",
"Has Open Issues": 0,
"Skipped": false,
"DataRow Workflow Info": {
"taskName": "Done",
"Workflow History": [
{
"actorId": "cl3lobugu14pw0796fau0dgad",
"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"
},
{
"actorId": "cl1qe5naj3g460z6e0owr6mwj",
"action": "REJECT",
"createdAt": "2022-09-29T13:39:01.077Z",
"previousTaskId": "0ae49522-97f0-4a07-96c6-bd4d50963acd",
"previousTaskName": "Initial review task",
"nextTaskId": "4a0d7f40-0c3f-0cc8-adc4-fd818684facd",
"nextTaskName": "Rework (all rejected)"
},
{
"actorId": "cl3ucfsj22j8l073xaitnh1xe",
"action": "MOVE",
"createdAt": "2022-09-28T18:06:16.881Z",
"previousTaskId": "ea78e526-e429-002e-8b80-b72c4b591152",
"previousTaskName": "Initial labeling task",
"nextTaskId": "0ae49522-97f0-4a07-96c6-bd4d50963acd",
"nextTaskName": "Initial review task"
},
{
"actorId": "cl3ucfsj22j8l073xaitnh1xe",
"action": "MOVE",
"createdAt": "2022-09-28T18:06:16.859Z",
"nextTaskId": "ea78e526-e429-002e-8b80-b72c4b591152",
"nextTaskName": "Initial labeling task"
}
]
}
}
]
// Access per-frame annotation info via Label.frames URL (see above)
{
"frameNumber": 1,
"classifications": [
{
"featureId": "ckmvaolhj2f2p0y8h7it0gpb2",
"schemaId": "ckmvaijzd2elz0y8h06ribh9b",
"title": "Is it daytime?",
"value": "is_it_daytime?",
"answer": {
"featureId": "ckmvaq6p3000c3g68vlqkjo18",
"schemaId": "ckmvaik0p2eml0y8h12z632kq",
"title": "Yes",
"value": "yes",
"keyframe": true
}
}
],
"objects": [
{
"featureId": "ckmvapiqw00083g688yjpvd34",
"schemaId": "cklifp8jw0tn40y5p3xtr2kk2",
"title": "right_ear",
"value": "right_ear",
"color": "#1CE6FF",
"keyframe": true,
"point": {
"x": 1447,
"y": 430
},
"classifications": [
{
"featureId": "ckmvaplfj00093g68elakf0q2",
"schemaId": "cklifp8ly0tnu0y5pd2jrcams",
"title": "Visibility",
"value": "visibility",
"answer": {
"featureId": "ckmvaplfj000a3g68rax7qw9k",
"schemaId": "cklifp8n20to80y5p6pyo0jyu",
"title": "0",
"value": "0",
"keyframe": true
}
}
]
},
{
"featureId": "ckmvaqsco000g3g681txq5v8h",
"schemaId": "ckmvaobyl20s70y8u13eu6nmc",
"title": "Lion",
"value": "lion",
"color": "#997D87",
"keyframe": true,
"bbox": {
"top": 366,
"left": 557,
"height": 571,
"width": 977
},
"classifications": [
{
"featureId": "ckmvaqvbc000h3g68i6d37w8y",
"schemaId": "ckmvaoc0120si0y8uang3hwza",
"title": "Is the lion walking?",
"value": "is_the_lion_walking?",
"answer": {
"featureId": "ckmvaqvbd000i3g68z4c3i78s",
"schemaId": "ckmvaoc1s20tb0y8ub1p79fl8",
"title": "No",
"value": "no",
"keyframe": true
}
}
]
}
]
}