Supervise.ly is a platform for computer vision that offers AI assisted labeling and integration with Jupyter notebooks.
Unfortunately, the platform is quite proprietary (including their JSON-based annotation format). This makes it hard to use your labeled data elsewhere. That's where Roboflow comes in! Export your labels from Supervisely and drop them into Roboflow to seamlessly convert them into any other format and use them with dozens of machine learning models.
Below, learn the structure of Supervisely JSON.
{
"description": "",
"tags": [
{
"id": 12345,
"name": "train",
"value": null,
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z"
}
],
"size": {
"height": 191,
"width": 264
},
"objects": [
{
"id": 12345,
"classId": 67890,
"description": "",
"geometryType": "polygon",
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z",
"tags": [],
"classTitle": "helmet",
"points": {
"exterior": [
[
184,
30
],
[
259,
30
],
[
260,
134
],
[
185,
131
]
],
"interior": []
}
},
{
"id": 12346,
"classId": 67891,
"description": "",
"geometryType": "rectangle",
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z",
"tags": [],
"classTitle": "person",
"points": {
"exterior": [
[
63,
49
],
[
124,
62
]
],
"interior": []
}
}
]
}With Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in Supervisely JSON. Read our dedicated guides to learn how to merge and split Supervisely JSON detections.
Below, see model architectures that require data in the Supervisely JSON format when training a new model.
On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.