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SuperAnnotate JSON

What is SuperAnnotate JSON?

SuperAnnotate is a provider of outsourced labeling annotation services and develops a self-serve labeling tool (formerly known as annotate.online) which is available for download on Windows, Linux, and Mac. Their tool has support for advanced labeling functions like video frame annotation and using a trained model to pre-suggest annotations.

You can use Roboflow to convert SuperAnnotate's custom JSON format to any format your computer vision models expect.

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SuperAnnotate JSON

Below, we show how to convert data to and from

SuperAnnotate JSON

. We also list popular models that use the

SuperAnnotate JSON

data format. Our conversion tools are free to use.

Convert Data to SuperAnnotate JSON

Use Roboflow to convert

SuperAnnotate 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

Sagemaker GroundTruth Manifest

SuperAnnotate JSON

Google Cloud AutoML Vision CSV

OpenAI CLIP Classification

SuperAnnotate JSON

RetinaNet Keras CSV

SuperAnnotate JSON

Tensorflow Object Detection CSV

SuperAnnotate JSON

Multiclass Classification CSV

SuperAnnotate JSON

YOLOv4 PyTorch TXT

SuperAnnotate JSON

YOLOv5 Oriented Bounding Boxes

Convert Data from SuperAnnotate JSON

Use Roboflow to convert the following formats to

SuperAnnotate 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

SuperAnnotate JSON

data format

What computer vision models use SuperAnnotate JSON?

The

No items found.

models all use the

SuperAnnotate 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.

annotations.json

{
    "mask.jpg": [{
        "type": "bbox",
        "classId": 1,
        "probability": 100,
        "points": {
            "x1": 67.8,
            "x2": 187.6,
            "y1": 166.6,
            "y2": 274.1
        },
        "groupId": 0,
        "pointLabels": {},
        "locked": false,
        "visible": true,
        "attributes": []
    }, {
        "type": "polyline",
        "classId": 2,
        "probability": 100,
        "points": [148.7, 321.1, 164.5, 328.3, 220.4, 335.5, 280.6, 344.8, 330.1, 341.9, 373.1, 330.5, 375.3, 336.2, 377.4, 369.9, 382.4, 384.9, 377.4, 409.3, 360.2, 425.1, 318.6, 451.6, 279.9, 473.8, 262.7, 488.2, 252, 499.6, 241.9, 502.5, 223.3, 496.8, 210.4, 486, 181.7, 453.8, 165.9, 443, 155.9, 431.5, 148, 419.4, 132.3, 410, 123.7, 397.8, 139.4, 346.2, 151.6, 319.7, 150.9, 321.1],
        "groupId": 0,
        "pointLabels": {},
        "locked": false,
        "visible": true,
        "attributes": []
    }, {
        "type": "polygon",
        "classId": 2,
        "probability": 100,
        "points": [493.7, 355.6, 506.1, 366.1, 567.3, 384.2, 648.5, 352.7, 649.5, 372.8, 659, 386.1, 649.5, 402.4, 631.3, 424.4, 618.9, 451.1, 612.2, 456.9, 585.4, 474.1, 570.1, 477.9, 552, 466.4, 527.1, 454, 491.8, 402.4, 494.6, 377.5, 493.7, 355.6],
        "groupId": 0,
        "pointLabels": {},
        "locked": false,
        "visible": true,
        "attributes": []
    }, {
        "type": "meta",
        "name": "lastAction",
        "timestamp": 1600628979793
    }]
}

classes.json

[{
    "attribute_groups": [],
    "color": "#32a852",
    "id": 1,
    "name": "no-mask",
    "opened": true
}, {
    "attribute_groups": [],
    "color": "#d6d619",
    "id": 2,
    "name": "mask",
    "opened": true
}]