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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

CONVERT To
CONVERT From
MODELS
EXAMPLE
Use Roboflow to convert
LabelBox Video JSON
to the following formats.
LabelBox Video JSON
 to 
Pascal VOC XML
LabelBox Video JSON
 to 
Tensorflow TFRecord
LabelBox Video JSON
 to 
COCO JSON
LabelBox Video JSON
 to 
YOLO Darknet TXT
LabelBox Video JSON
 to 
CreateML JSON
LabelBox Video JSON
 to 
YOLOv7 PyTorch TXT
LabelBox Video JSON
 to 
YOLOv5 PyTorch TXT
LabelBox Video JSON
 to 
Google Cloud AutoML Vision CSV
LabelBox Video JSON
 to 
Sagemaker GroundTruth Manifest
LabelBox Video JSON
 to 
meituan/yolov6
LabelBox Video JSON
 to 
Scaled-YOLOv4 TXT
LabelBox Video JSON
 to 
YOLO Keras TXT
LabelBox Video JSON
 to 
OpenAI CLIP Classification
LabelBox Video JSON
 to 
RetinaNet Keras CSV
LabelBox Video JSON
 to 
Tensorflow Object Detection CSV
LabelBox Video JSON
 to 
Multiclass Classification CSV
LabelBox Video JSON
 to 
YOLOv4 PyTorch TXT
LabelBox Video JSON
 to 
YOLOv5 Oriented Bounding Boxes
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": []
    }]
}]