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SuperAnnotate JSON
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.

SuperAnnotate JSON

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