LabelBox Video JSON Annotation Format

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LabelBox Video JSON

LabelBox Video JSON

LabelBox is an enterprise labeling solution. Their key differentiator is that you can bring your own labeling team and host their software on-premises behind your company's firewall. This is important for sensitive domains where labeling needs to be done by a specially trained expert (for example, aerospace and defense).

If you have labeled a video, they will export a JSON file containing the annotations for each frame. Roboflow Pro supports importing LabelBox Video JSON annotations and can convert them to any format your machine learning model requires.

LabelBox Video JSON

Use Roboflow to convert

LabelBox Video JSON

to the following formats.

LabelBox Video JSON

LabelBox Video JSON

Tensorflow TFRecord

LabelBox Video JSON

LabelBox Video JSON

YOLO Darknet TXT

LabelBox Video JSON

LabelBox Video JSON

YOLOv5 PyTorch TXT

LabelBox Video JSON

Google Cloud AutoML Vision CSV

LabelBox Video JSON

Sagemaker GroundTruth Manifest

LabelBox Video JSON

Scaled-YOLOv4 TXT

LabelBox Video JSON

LabelBox Video JSON

OpenAI CLIP Classification

LabelBox Video JSON

RetinaNet Keras CSV

LabelBox Video JSON

Tensorflow Object Detection CSV

LabelBox Video JSON

Multiclass Classification CSV

LabelBox Video JSON

YOLOv4 PyTorch TXT

Use Roboflow to convert the following formats to

LabelBox Video JSON

format.

Here are pre-configured models that use

LabelBox Video JSON

. 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.

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": []
    }]
}]