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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

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