CreateML JSON Annotation Format

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CreateML JSON

When Apple released CreateML in 2018 it was a groundbreaking innovation. For the first time, developers could easily train a machine learning model with no code. No code, that is, except for the one-off scripts they needed to write to munge their data into the proper JSON format that was adopted from Apple's acquired machine learning framework, Turi Create.

Fortunately, Roboflow can both read and write CreateML JSON files so you can truly train a model and export it for use with an Apple iOS device via CoreML without writing a single line of code.

CreateML JSON

Use Roboflow to convert

CreateML JSON

to the following formats.

Google Cloud AutoML Vision CSV

CreateML JSON

Sagemaker GroundTruth Manifest

Tensorflow Object Detection CSV

CreateML JSON

Multiclass Classification CSV

CreateML JSON

YOLOv4 PyTorch TXT

Here are pre-configured models that use

CreateML 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.

createml.json

[
    {
        "image": "0001.jpg",
        "annotations": [
            {
                "label": "helmet",
                "coordinates": {
                    "x": 162.5,
                    "y": 45,
                    "width": 79,
                    "height": 88
                }
            },
            {
                "label": "person",
                "coordinates": {
                    "x": 145.5,
                    "y": 176,
                    "width": 251,
                    "height": 350
                }
            }
        ]
    }
]

PRODUCT

DOCS & Support

CreateML JSON