Formats
LabelMe JSON
Object Detection
IMPORTEXPORT
FEATURED
Object Detection

LabelMe JSON

The native format of LabelMe, an open source graphical image annotation tool written in Python and available for Windows, Mac, and Linux.

Overview

LabelMe is an actively developed open source graphical image annotation tool inspired by the app of the same name released in 2012 by MIT CSAIL.

‍

It is capable of annotating images for object detection, segmentation, and classification (along with polygon, circle, line, and point annotations). It also supports annotating videos.

‍

The app is cross-platform and runs on Ubuntu, macOS, and Windows using Qt4 (or Qt5) and Python (2 or 3). A docker container is also available.


Also check out our LabelMe Tutorial.

Format Description

Below, learn the structure of LabelMe JSON.

labelme.chess.json
{
  "version": "4.5.6",
  "flags": {},
  "shapes": [
    {
      "label": "black-bishop",
      "points": [
        [
          250.5,
          44.0
        ],
        [
          285.0,
          112.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-knight",
      "points": [
        [
          128.5,
          44.0
        ],
        [
          168.5,
          110.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-king",
      "points": [
        [
          110.5,
          153.5
        ],
        [
          160.0,
          253.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-bishop",
      "points": [
        [
          91.0,
          295.0
        ],
        [
          136.5,
          366.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-pawn",
      "points": [
        [
          242.0,
          253.5
        ],
        [
          277.5,
          306.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-queen",
      "points": [
        [
          317.0,
          33.0
        ],
        [
          357.0,
          117.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-bishop",
      "points": [
        [
          367.5,
          1.5
        ],
        [
          401.0,
          69.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-rook",
      "points": [
        [
          484.5,
          56.5
        ],
        [
          522.5,
          113.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-king",
      "points": [
        [
          557.0,
          108.0
        ],
        [
          614.5,
          206.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-pawn",
      "points": [
        [
          384.0,
          153.0
        ],
        [
          412.5,
          204.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-bishop",
      "points": [
        [
          388.5,
          242.0
        ],
        [
          428.0,
          310.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-pawn",
      "points": [
        [
          517.5,
          249.5
        ],
        [
          553.0,
          303.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-knight",
      "points": [
        [
          466.5,
          356.5
        ],
        [
          516.0,
          430.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    }
  ],
  "imagePath": "0af.jpg",
  "imageData": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBg...",
  "imageHeight": 512,
  "imageWidth": 765
}

Split and Merge Datasets

With Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in LabelMe JSON. Read our dedicated guides to learn how to merge and split LabelMe JSON detections.

Split detections in LabelMe JSON

No items found.

Merge detections in LabelMe JSON

No items found.

Supported Models

Below, see model architectures that require data in the LabelMe 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.

No items found.

On this page

Convert Data from LabelMe JSON

Convert to...

Convert Data to LabelMe JSON

Convert from...
Formats
LabelMe JSON

What is LabelMe JSON?

LabelMe is an actively developed open source graphical image annotation tool inspired by the app of the same name released in 2012 by MIT CSAIL.

‍

It is capable of annotating images for object detection, segmentation, and classification (along with polygon, circle, line, and point annotations). It also supports annotating videos.

‍

The app is cross-platform and runs on Ubuntu, macOS, and Windows using Qt4 (or Qt5) and Python (2 or 3). A docker container is also available.


Also check out our LabelMe Tutorial.

Deploy Models with Ease on Roboflow

With Roboflow, you can deploy a computer vision model without having to build your own infrastructure.

Get Started Today

LabelMe JSON

Below, we show how to convert data to and from

LabelMe JSON

. We also list popular models that use the

LabelMe JSON

data format. Our conversion tools are free to use.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to LabelMe JSON

Use Roboflow to convert
LabelMe 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

LabelMe JSON
 to 
YOLOv8 PyTorch TXT
LabelMe JSON
 to 
YOLOv8 Oriented Bounding Boxes
LabelMe JSON
 to 
PaliGemma JSONL
LabelMe JSON
 to 
YOLOv10 PyTorch TXT
LabelMe JSON
 to 
YOLOv9 PyTorch TXT
LabelMe JSON
 to 
Florence-2
LabelMe JSON
 to 
YOLOv11 PyTorch TXT
LabelMe JSON
 to 
OpenAI GPT-4o Object Detection JSONL
LabelMe JSON
 to 
COCO Run-Length Encoding (RLE)
LabelMe JSON
 to 
Tensorflow TFRecord
LabelMe JSON
 to 
COCO JSON
LabelMe JSON
 to 
Pascal VOC XML
LabelMe JSON
 to 
CreateML JSON
LabelMe JSON
 to 
YOLO Darknet TXT
LabelMe JSON
 to 
YOLOv7 PyTorch TXT
LabelMe JSON
 to 
YOLOv5 PyTorch TXT
LabelMe JSON
 to 
Google Cloud AutoML Vision CSV
LabelMe JSON
 to 
Sagemaker GroundTruth Manifest
LabelMe JSON
 to 
meituan/yolov6
LabelMe JSON
 to 
Scaled-YOLOv4 TXT
LabelMe JSON
 to 
YOLO Keras TXT
LabelMe JSON
 to 
OpenAI CLIP Classification
LabelMe JSON
 to 
RetinaNet Keras CSV
LabelMe JSON
 to 
Tensorflow Object Detection CSV
LabelMe JSON
 to 
Multiclass Classification CSV
LabelMe JSON
 to 
YOLOv4 PyTorch TXT
LabelMe JSON
 to 
YOLOv5 Oriented Bounding Boxes

Convert Data from LabelMe JSON

Use Roboflow to convert the following formats to
LabelMe 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
LabelMe JSON
data format
.

What computer vision models use LabelMe JSON?

The

No items found.

models all use the

LabelMe 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.
labelme.chess.json
{
  "version": "4.5.6",
  "flags": {},
  "shapes": [
    {
      "label": "black-bishop",
      "points": [
        [
          250.5,
          44.0
        ],
        [
          285.0,
          112.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-knight",
      "points": [
        [
          128.5,
          44.0
        ],
        [
          168.5,
          110.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-king",
      "points": [
        [
          110.5,
          153.5
        ],
        [
          160.0,
          253.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-bishop",
      "points": [
        [
          91.0,
          295.0
        ],
        [
          136.5,
          366.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-pawn",
      "points": [
        [
          242.0,
          253.5
        ],
        [
          277.5,
          306.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-queen",
      "points": [
        [
          317.0,
          33.0
        ],
        [
          357.0,
          117.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "white-bishop",
      "points": [
        [
          367.5,
          1.5
        ],
        [
          401.0,
          69.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-rook",
      "points": [
        [
          484.5,
          56.5
        ],
        [
          522.5,
          113.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-king",
      "points": [
        [
          557.0,
          108.0
        ],
        [
          614.5,
          206.0
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-pawn",
      "points": [
        [
          384.0,
          153.0
        ],
        [
          412.5,
          204.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-bishop",
      "points": [
        [
          388.5,
          242.0
        ],
        [
          428.0,
          310.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-pawn",
      "points": [
        [
          517.5,
          249.5
        ],
        [
          553.0,
          303.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "black-knight",
      "points": [
        [
          466.5,
          356.5
        ],
        [
          516.0,
          430.5
        ]
      ],
      "group_id": null,
      "shape_type": "rectangle",
      "flags": {}
    }
  ],
  "imagePath": "0af.jpg",
  "imageData": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBg...",
  "imageHeight": 512,
  "imageWidth": 765
}
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