LabelBox JSON Annotation Format

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LabelBox JSON

LabelBox JSON

LabelBox hosts a free online "label it yourself" tool and is a popular solution for outsourced labeling. Their key differentiator is that you can bring your own labeling team. This is important for domains where labeling needs to be done by a specially trained expert (for example, labeling crop diseases or medical images).

You can export from LabelBox in two formats, CSV or JSON. No computer vision models will accept these formats directly. But fear not, Roboflow supports importing LabelBox JSON annotations and can convert them to any format your machine learning model requires.

LabelBox JSON

Use Roboflow to convert

LabelBox JSON

to the following formats.

Tensorflow TFRecord

YOLO Darknet TXT

YOLOv5 PyTorch TXT

Google Cloud AutoML Vision CSV

Sagemaker GroundTruth Manifest

Scaled-YOLOv4 TXT

OpenAI CLIP Classification

RetinaNet Keras CSV

Tensorflow Object Detection CSV

Multiclass Classification CSV

YOLOv4 PyTorch TXT

Use Roboflow to convert the following formats to

LabelBox JSON

format.

Here are pre-configured models that use

LabelBox 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.

labelbox.json

[{
    "ID": "a9b7c5d3e1f",
    "DataRow ID": "xy10z8a6b4c",
    "Labeled Data": "https://storage.labelbox.com/IMG_001.JPG",
    "Label": {
        "helmet": [{
            "geometry": [{
                "x": 690,
                "y": 1497
            }, {
                "x": 931,
                "y": 1497
            }, {
                "x": 931,
                "y": 1633
            }, {
                "x": 690,
                "y": 1633
            }]
        }, {
            "geometry": [{
                "x": 1079,
                "y": 1445
            }, {
                "x": 1324,
                "y": 1445
            }, {
                "x": 1324,
                "y": 1564
            }, {
                "x": 1079,
                "y": 1564
            }]
        }]
    },
    "Project Name": "Boggle",
    "External ID": "IMG_001.JPG"
}]