Open In Colab
GitHub
Export JSON annotations
# 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))
Prompt export format
Humans generate prompts
{
"feature_id": "cldne96y301wy13yd0wp5z87y",
"feature_schema_id": "cljg9my6h01000741aemmcln8",
"name": "sample_name",
"text_answer": {
"content": "sample text"
}
}
Response export formats
Response - Radio
{
"feature_id": "cldne96y201wq13ydu0qcc2up",
"feature_schema_id": "cljggfygv0chn070w1v131s3v",
"name": "sample_radio_name",
"radio_answer": {
"feature_id": "cldne96y201wr13yd23kr1pcr",
"feature_schema_id": "cljgggcs200083b6lqbpml10p",
"name": "first_radio_answer",
"classifications": []
}
}
Response - Checklist
{
"feature_id": "cldne96y201wu13ydohrclpra",
"feature_schema_id": "cljgegd1p07m4073cfmfy5xkx",
"name": "checklist_question",
"checklist_answers": [
{
"feature_id": "cldne96y301wv13ydatuxugbt",
"name": "first_checklist_answer",
"classifications": []
},
{
"feature_id": "cldne96y301ww13yds4zkk49u",
"name": "second_checklist_answer",
"classifications": []
},
{
"feature_id": "cldne96y301wx13ydvb5x2w6o",
"name": "third_checklist_answer",
"classifications": []
}
]
}
Response - Text
{
"feature_id": "cldne96y301wy13yd0wp5z87y",
"feature_schema_id": "cljg9my6h01000741aemmcln8",
"name": "sample_name",
"text_answer": {
"content": "sample text"
}
}
Sample project export
{
"data_row": {
"id": "clpvnouh04uyy0723mmru42qn",
"global_key": "clpvnou2v03js07xsghfo2nzc",
"row_data": "{\"type\":\"application/llm.prompt-response-creation\",\"version\":1}",
"details": {
"dataset_id": "clpvnou0z004c0724pd4cmw8g",
"dataset_name": "test-humans-generate-prompts-reponses-dataset",
"created_at": "2023-12-07T20:34:06.540+00:00",
"updated_at": "2023-12-07T20:34:06.815+00:00",
"last_activity_at": "2024-04-10T15:21:31.000+00:00",
"created_by": "[email protected]"
}
},
"media_attributes": {
"mime_type": "application/llm.prompt-response-creation"
},
"attachments": [],
"metadata_fields": [],
"projects": {
"clpvnotzb03jo07xs48r7ewka": {
"name": "Andrea-test-humans-generate-prompts-responses",
"labels": [
{
"label_kind": "Default",
"version": "1.0.0",
"id": "clutyida4041a07h4a8ojbu1g",
"label_details": {
"created_at": "2024-04-10T15:21:31.000+00:00",
"updated_at": "2024-04-10T15:21:31.000+00:00",
"created_by": "[email protected]",
"content_last_updated_at": "2024-04-10T15:21:31.137+00:00",
"reviews": []
},
"performance_details": {
"seconds_to_create": 28,
"seconds_to_review": 0,
"skipped": false
},
"annotations": {
"objects": [],
"classifications": [
{
"feature_id": "clutykado00013b6rw65zj51e",
"feature_schema_id": "clutyjef000xk07wfeurhc2qb",
"name": "Is this a shirt?",
"value": "Is this a shirt?",
"text_answer": {
"content": "Potentially this is a shirt, but keep in mind this is not a good quality prompt"
}
},
{
"feature_id": "clutykap700033b6rmmlkpo6u",
"feature_schema_id": "clutyjef000xm07wf5ym80ud6",
"name": "Yes",
"value": "yes",
"radio_answer": {
"feature_id": "clutykap700023b6rhktauyzc",
"feature_schema_id": "clutyjef000xn07wf6smvc54b",
"name": "Red shirt",
"value": "red_shirt",
"classifications": []
}
}
],
"relationships": []
}
}
],
"project_details": {
"ontology_id": "clpvnqsqz01kv07zydvbscxzq",
"task_id": "14b02ec0-71f3-4d1f-b720-c6318e9a9346",
"task_name": "Initial review task",
"batch_id": "00870bc0-9540-11ee-a202-8d3b90bd1707",
"batch_name": "batch_clpvnotzb03jo07xs48r7ewka",
"workflow_status": "IN_REVIEW",
"priority": 5,
"consensus_expected_label_count": 2,
"workflow_history": [
{
"action": "Move",
"created_at": "2024-04-10T15:21:31.517+00:00",
"created_by": "[email protected]",
"previous_task_name": "Initial labeling task",
"previous_task_id": "1d0062f9-dfd9-0f86-baed-823235868a8c",
"next_task_name": "Initial review task",
"next_task_id": "14b02ec0-71f3-4d1f-b720-c6318e9a9346"
},
{
"action": "Move",
"created_at": "2024-04-10T15:21:31.506+00:00",
"created_by": "[email protected]",
"next_task_name": "Initial labeling task",
"next_task_id": "1d0062f9-dfd9-0f86-baed-823235868a8c"
}
]
},
"project_tags": []
}
}
}