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content/tutorial-svd.md

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@@ -47,7 +47,18 @@ except ImportError: # Data was in scipy.misc prior to scipy v1.10
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img = face()
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```
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**Note**: If you prefer, you can use your own image as you work through this tutorial. In order to transform your image into a NumPy array that can be manipulated, you can use the `imread` function from the [matplotlib.pyplot](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot) submodule. Alternatively, you can use the [imageio.imread](https://imageio.readthedocs.io/en/stable/_autosummary/imageio.v3.imread.html) function from the `imageio` library. Be aware that if you use your own image, you'll likely need to adapt the steps below. For more information on how images are treated when converted to NumPy arrays, see [A crash course on NumPy for images](https://scikit-image.org/docs/stable/user_guide/numpy_images.html) from the `scikit-image` documentation.
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```{note}
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If you prefer, you can use your own image as you work through this tutorial.
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In order to transform your image into a NumPy array that can be manipulated, you
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can use the `imread` function from the
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[matplotlib.pyplot](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot) submodule.
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Alternatively, you can use the
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[imageio.imread](https://imageio.readthedocs.io/en/stable/_autosummary/imageio.v3.imread.html)
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function from the `imageio` library.
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Be aware that if you use your own image, you'll likely need to adapt the steps below.
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For more information on how images are treated when converted to NumPy arrays,
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see [A crash course on NumPy for images](https://scikit-image.org/docs/stable/user_guide/numpy_images.html) from the `scikit-image` documentation.
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```
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