Formats
LabelBox Video JSON
IMPORTEXPORT
FEATURED

LabelBox Video JSON

LabelBox is an outsourced label management service, specializing in on-premise "bring your own labeler" solutions.
Formats

LabelBox Video JSON

Below, we show how to convert data to and from

LabelBox Video JSON

. We also list popular models that use the

LabelBox Video JSON

data format. Our conversion tools are free to use.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to LabelBox Video JSON

Use Roboflow to convert
LabelBox Video JSON
to the following formats.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get a solution with:

Free data conversion

SOC II Type 2 Compliant

Trusted by 250,000+ developers

Convert Data from LabelBox Video JSON

Use Roboflow to convert the following formats to
LabelBox Video JSON
format.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get:

Free data conversion

SOC II Type 1 Compliant

Trusted by 250,000+ developers

Roboflow is a trusted solution for converting and managing your data. Today, over 100,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

Once your data is in Roboflow, just add the link from your dataset and you're ready to go. We even include the code to export to common inference formats like TFLite, ONNX, and CoreML.

Below are pre-configured models that use the
LabelBox Video JSON
data format
.

What computer vision models use LabelBox Video JSON?

The

No items found.

models all use the

LabelBox Video JSON

data format.

We don't currently have models that use this annotation format.
To see our entire list of computer vision models, check out the Roboflow Model Library.
somevideo.json
[{
    "frameNumber": 1,
    "classifications": [],
    "objects": [{
        "featureId": "ckikg6eriqgb",
        "schemaId": "ckikenbqvmx8",
        "title": "Helmet",
        "value": "helmet",
        "color": "#008941",
        "bbox": {
            "top": 49,
            "left": 861,
            "height": 78,
            "width": 168
        },
        "classifications": []
    }, {
    "frameNumber": 2,
    "classifications": [],
    "objects": [{
        "featureId": "ckikg6eriqgc",
        "schemaId": "ckikenbqvmx8",
        "title": "Person",
        "value": "person",
        "color": "#CC0041",
        "bbox": {
            "top": 149,
            "left": 63,
            "height": 24,
            "width": 68
        },
        "classifications": []
    }, {
        "featureId": "ckikg6lvs27l",
        "schemaId": "ckikenbqvmx8",
        "title": "Helmet",
        "value": "helmet",
        "color": "#008941",
        "bbox": {
            "top": 662,
            "left": 597,
            "height": 162,
            "width": 266
        },
        "classifications": []
    }]
}]