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<h1 align="center">Using Pysolotools to Convert From SOLO to COCO</h1>

The SOLO format was created by us to be able to efficiently store all of the data, annotations, and metrics generated by the Perception toolkit. However, in order to use existing computer vision models, your data will need to be converted into a format that those models can ingest. One of the most common interchagne formats is the [COCO](https://cocodataset.org/#home) format. This guide will walk you through the entire process of converting a dataset from the SOLO format into the COCO format. We will use Unity's Computer Vision Team's pysolotools to accomplish this task. Pysolotools is a Python package that provides a variety of tools for processing, analyzing, and converting SOLO datasets generated using the Perception package.
The SOLO format was created by us to be able to efficiently store all of the data, annotations, and metrics generated by the Perception toolkit. However, in order to use existing computer vision models, your data will need to be converted into a format that those models can ingest. One of the most common interchange formats is the [COCO](https://cocodataset.org/#home) format. This guide will walk you through the entire process of converting a dataset from the SOLO format into the COCO format. We will use Unity's Computer Vision Team's pysolotools to accomplish this task. Pysolotools is a Python package that provides a variety of tools for processing, analyzing, and converting SOLO datasets generated using the Perception package.

## Set up your python environment
The first step that we will need to do is to setup our python environment. To avoid a python configuration nightmare, we highly recommend using a virtual python environment for development. For this tutorial we will use anaconda, but this is just a recommendation and not mandatory. For more information about Anaconda environments, and why you should use one, please see [here](https://conda.io/projects/conda/en/latest/user-guide/install/download.html).
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