Formats
COCO Run-Length Encoding (RLE)
Instance Segmentation
IMPORTEXPORT
FEATURED
Instance Segmentation

COCO Run-Length Encoding (RLE)

A version of the COCO JSON format with segmentation masks encoded with run-length encoding.

Overview

A version of the COCO JSON format with segmentation masks encoded with run-length encoding.

‍

Format Description

Below, learn the structure of COCO Run-Length Encoding (RLE).



{
    "info": {
        "description": "Exported from Darwin",
        "url": "n/a",
        "version": "n/a",
        "year": 2022,
        "contributor": "n/a",
        "date_created": "2022/07/03"
    },
    "licenses": [
        {
            "url": "n/a",
            "id": 0,
            "name": "placeholder license"
        }
    ],
    "images": [
        {
            "license": 0,
            "file_name": "2020-02-09--20-26-30(GMT-0700)--18s.mkv-0005.png1920x1080.png",
            "coco_url": "n/a",
            "height": 1080,
            "width": 1920,
            "date_captured": "",
            "flickr_url": "n/a",
            "darwin_url": "https://darwin.v7labs.com/api/images/437470172/original",
            "darwin_workview_url": "https://darwin.v7labs.com/workview?dataset=484903&image=86",
            "id": 290,
            "tag_ids": []
        }
    ],
    "annotations": [
        {
            "id": 8944,
            "image_id": 290,
            "category_id": 8,
            "segmentation": [
                [
                    1550.78,
                    748.65,
                    1548.38,
                    770.21,
                    1638.96,
                    779.7,
                    1640.35,
                    757.28,
                    1640.83,
                    726.62,
                    1557.96,
                    718.72
                ]
            ],
            "area": 4641.607800000347,
            "bbox": [
                1548.38,
                718.72,
                92.44999999999982,
                60.98000000000002
            ],
            "iscrowd": 0,
            "extra": {}
        },
     ]
 }

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 COCO Run-Length Encoding (RLE). Read our dedicated guides to learn how to merge and split COCO Run-Length Encoding (RLE) detections.

Split detections in COCO Run-Length Encoding (RLE)

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Merge detections in COCO Run-Length Encoding (RLE)

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Supported Models

Below, see model architectures that require data in the COCO Run-Length Encoding (RLE) 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.

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On this page

Convert Data from COCO Run-Length Encoding (RLE)

Convert to...

Convert Data to COCO Run-Length Encoding (RLE)

Convert from...
Formats
COCO Run-Length Encoding (RLE)

What is COCO Run-Length Encoding (RLE)?

A version of the COCO JSON format with segmentation masks encoded with run-length encoding.

‍

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COCO Run-Length Encoding (RLE)

Below, we show how to convert data to and from

COCO Run-Length Encoding (RLE)

. We also list popular models that use the

COCO Run-Length Encoding (RLE)

data format. Our conversion tools are free to use.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to COCO Run-Length Encoding (RLE)

Use Roboflow to convert
COCO Run-Length Encoding (RLE)
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

COCO Run-Length Encoding (RLE)
 to 
Segment Anything 2

Convert Data from COCO Run-Length Encoding (RLE)

Use Roboflow to convert the following formats to
COCO Run-Length Encoding (RLE)
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

Cogniac
to
COCO Run-Length Encoding (RLE)
YOLOv8 PyTorch TXT
to
COCO Run-Length Encoding (RLE)
Unity Perception JSON
to
COCO Run-Length Encoding (RLE)
LabelBox Video JSON
to
COCO Run-Length Encoding (RLE)
IBM Cloud Annotations JSON
to
COCO Run-Length Encoding (RLE)
SuperAnnotate JSON
to
COCO Run-Length Encoding (RLE)
LabelMe JSON
to
COCO Run-Length Encoding (RLE)
Multiclass Classification CSV
to
COCO Run-Length Encoding (RLE)
Kaggle Wheat CSV
to
COCO Run-Length Encoding (RLE)
Google Cloud AutoML Vision CSV
to
COCO Run-Length Encoding (RLE)
OIDv4 TXT
to
COCO Run-Length Encoding (RLE)
RetinaNet Keras CSV
to
COCO Run-Length Encoding (RLE)
Tensorflow Object Detection CSV
to
COCO Run-Length Encoding (RLE)
Sagemaker GroundTruth Manifest
to
COCO Run-Length Encoding (RLE)
Udacity TXT
to
COCO Run-Length Encoding (RLE)
VoTT JSON
to
COCO Run-Length Encoding (RLE)
VoTT CSV
to
COCO Run-Length Encoding (RLE)
YOLO Darknet TXT
to
COCO Run-Length Encoding (RLE)
OpenImages CSV
to
COCO Run-Length Encoding (RLE)
YOLO Keras TXT
to
COCO Run-Length Encoding (RLE)
Marmot XML
to
COCO Run-Length Encoding (RLE)
Pascal VOC XML
to
COCO Run-Length Encoding (RLE)
Supervisely JSON
to
COCO Run-Length Encoding (RLE)
LabelBox JSON
to
COCO Run-Length Encoding (RLE)
Scale AI JSON
to
COCO Run-Length Encoding (RLE)
COCO JSON
to
COCO Run-Length Encoding (RLE)
CreateML JSON
to
COCO Run-Length Encoding (RLE)
YOLOv10 PyTorch TXT
to
COCO Run-Length Encoding (RLE)
PaliGemma JSONL
to
COCO Run-Length Encoding (RLE)
YOLOv11 PyTorch TXT
to
COCO Run-Length Encoding (RLE)
OpenAI GPT-4o Object Detection JSONL
to
COCO Run-Length Encoding (RLE)
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
COCO Run-Length Encoding (RLE)
data format
.

What computer vision models use COCO Run-Length Encoding (RLE)?

The

No items found.

models all use the

COCO Run-Length Encoding (RLE)

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.


{
    "info": {
        "description": "Exported from Darwin",
        "url": "n/a",
        "version": "n/a",
        "year": 2022,
        "contributor": "n/a",
        "date_created": "2022/07/03"
    },
    "licenses": [
        {
            "url": "n/a",
            "id": 0,
            "name": "placeholder license"
        }
    ],
    "images": [
        {
            "license": 0,
            "file_name": "2020-02-09--20-26-30(GMT-0700)--18s.mkv-0005.png1920x1080.png",
            "coco_url": "n/a",
            "height": 1080,
            "width": 1920,
            "date_captured": "",
            "flickr_url": "n/a",
            "darwin_url": "https://darwin.v7labs.com/api/images/437470172/original",
            "darwin_workview_url": "https://darwin.v7labs.com/workview?dataset=484903&image=86",
            "id": 290,
            "tag_ids": []
        }
    ],
    "annotations": [
        {
            "id": 8944,
            "image_id": 290,
            "category_id": 8,
            "segmentation": [
                [
                    1550.78,
                    748.65,
                    1548.38,
                    770.21,
                    1638.96,
                    779.7,
                    1640.35,
                    757.28,
                    1640.83,
                    726.62,
                    1557.96,
                    718.72
                ]
            ],
            "area": 4641.607800000347,
            "bbox": [
                1548.38,
                718.72,
                92.44999999999982,
                60.98000000000002
            ],
            "iscrowd": 0,
            "extra": {}
        },
     ]
 }
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