curl --request GET \
--url https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text)const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));false{
"analyzed_clip_count": 1,
"axes": [
{
"axis": "<string>",
"categories": [
{
"category": "<string>",
"concept_count": 1,
"example_concepts": [
"<string>"
],
"label": "<string>"
}
],
"concept_count": 1,
"concepts": [
{
"category": "<string>",
"clip_count": 1,
"clip_percent": 50,
"concept": "<string>",
"interaction": {
"clip_count": 1,
"clip_percent": 50
}
}
]
}
],
"content_diversity": "<string>",
"coverage_percent": 50,
"dataset": "<string>",
"object_actions": {
"combination_count": 1,
"combinations": [
{
"action_verb": "<string>",
"clip_count": 1,
"clip_percent": 50,
"object": "<string>"
}
]
}
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}Get dataset content diversity
Returns canonical environment, visible-object, and action-verb concepts,
together with object interaction and action-verb/object distributions across
analyzed clips. Descriptive categories are included as optional ways to
group the concepts. This endpoint characterizes content composition; it does
not directly detect duplicate video or determine task completion. Use
axis to request one independent concept type.
For field examples and comparison guidance, see Understand quality metrics.
curl --request GET \
--url https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text)const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.hebbianrobotics.com/api/v1beta/quality/content-diversity', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));false{
"analyzed_clip_count": 1,
"axes": [
{
"axis": "<string>",
"categories": [
{
"category": "<string>",
"concept_count": 1,
"example_concepts": [
"<string>"
],
"label": "<string>"
}
],
"concept_count": 1,
"concepts": [
{
"category": "<string>",
"clip_count": 1,
"clip_percent": 50,
"concept": "<string>",
"interaction": {
"clip_count": 1,
"clip_percent": 50
}
}
]
}
],
"content_diversity": "<string>",
"coverage_percent": 50,
"dataset": "<string>",
"object_actions": {
"combination_count": 1,
"combinations": [
{
"action_verb": "<string>",
"clip_count": 1,
"clip_percent": 50,
"object": "<string>"
}
]
}
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}{
"code": "<string>",
"message": "<string>"
}Authorizations
Bearer access token issued through OAuth 2.0 client credentials.
Query Parameters
Dataset ID from GET /api/v1beta/quality/datasets.
Opaque content_diversity token from an earlier response. Omit to use
the latest measurement.
Return only one diversity axis: environments, objects, or
action_verbs.
Omit it to receive all three independent distributions.
environments, objects, action_verbs Response
Published concepts and clip distributions by diversity axis
Dataset content diversity and measurement completeness.
Use this response to inspect which concepts are present and how frequently they occur across analyzed clips. It does not directly detect duplicate video or determine whether a task was completed correctly.
Number of distinct clips that produced usable content observations. This
is the denominator for every clip_percent in axes and
object_actions.
x >= 0Independent distributions for environment, object, and action-verb
concepts. An axis query parameter limits this array to one requested
type.
Show child attributes
Show child attributes
Opaque content-diversity token. Matching tokens identify results from the same content-diversity measurement.
Percentage of the planned analysis that successfully produced values
used in this response, in [0, 100]. This is measurement completeness,
not the percentage of footage that passed quality control. null when
the planned result count cannot be determined reliably. Non-null values
are rounded to two decimal places.
0 <= x <= 100Dataset ID used in the request.
Observed action-verb and object combinations. Independent object and action-verb distributions are derived from the same activity records.
Show child attributes
Show child attributes
