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Copy file name to clipboardExpand all lines: setup.md
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## Data
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The example images used in this lesson are available on [FigShare](https://figshare.com/).
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The example images and a description of the Python environment used in this lesson are available on [FigShare](https://figshare.com/).
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To download the data, please visit [the dataset page for this workshop][figshare-data]
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and click the "Download all" button.
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Unzip the downloaded file, and save the contents as a folder called `data` somewhere you will easily find it again,
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## Software
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1. Download and install the latest [Anaconda
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distribution](https://www.anaconda.com/download/) for your
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operating system. Make sure to choose the Python 3 version (as
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opposed to the one with Python 2). If you wish to use an existing
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installation, be sure to upgrade your scikit-image to at least 0.19.
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You can upgrade to the latest scikit-image using the shell command that follows.
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1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system.
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If you already have a Python 3 setup that you are happy with, you can continue to use that (we recommend that you make sure your Python version is current).
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The next step assumes that `conda` is available to manage your Python environment.
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2. Setup an environment to work in during the lesson.
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In a terminal (Linux/Mac) or the MiniForge Prompt application (Windows), navigate to the location where you saved the unzipped data for the lesson and run the following command:
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::::::::::::::::::::::::::::::::::::::::: callout
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## Updating scikit-image in an existing Anaconda distribution
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