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README.md

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Launch the tutorial notebooks directly with MyBinder now:
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[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/scikit-image/skimage-tutorials/master?filepath=index.ipynb)
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[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/scikit-image/skimage-tutorials/main?filepath=index.ipynb)
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Or you can setup and run on your local machine:
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1. [Follow the preparation instructions](preparation.md)

_sources/imagexd.txt

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- 14:00—14:30 :doc:`scikit-image: images are arrays <lessons/0_images_are_arrays>`
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- 14:30—14:45 Coffee break
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- 14:45—15:45 scikit-image: `filtering
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<http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/master/book/lessons/1_image_filters.ipynb>`__
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<http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/main/book/lessons/1_image_filters.ipynb>`__
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and `segmentation
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<http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/master/book/lessons/4_segmentation.ipynb>`__
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<http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/main/book/lessons/4_segmentation.ipynb>`__
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- 15:45—16:15 :doc:`scikit-image: RANSAC <lessons/1_ransac>`
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- 16:15—16:25 Coffee break
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- 16:25—16:30 Panorama demo

_sources/lessons/0_installation.txt

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There are two ways of downloading the lecture materials:
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a) Get the `ZIP file from GitHub
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<https://github.com/scikit-image/skimage-tutorials/archive/master.zip>`__
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<https://github.com/scikit-image/skimage-tutorials/archive/main.zip>`__
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b) Clone the repository at
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https://github.com/scikit-image/skimage-tutorial

_sources/lessons/0_preparation.txt

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There are two ways of downloading the lecture materials:
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1. Get the [ZIP file from GitHub](https://github.com/scikit-image/skimage-tutorials/archive/master.zip)
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1. Get the [ZIP file from GitHub](https://github.com/scikit-image/skimage-tutorials/archive/main.zip)
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2. Clone the repository at
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[https://github.com/scikit-image/skimage-tutorials](https://github.com/scikit-image/skimage-tutorials)

workshops/2014-euroscipy/index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://groups.google.com/d/forum/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/CONTRIBUTING.txt)\n",
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"- If you find it useful: cite [our paper](https://peerj.com/articles/453/)!"
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]
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}

workshops/2014-scipy/000_index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://groups.google.com/d/forum/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/CONTRIBUTING.txt)\n",
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"- If you find it useful: cite [our paper](https://peerj.com/articles/453/)!"
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]
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}

workshops/2015-scipy/index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://groups.google.com/d/forum/scikit-image).\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/CONTRIBUTING.txt)\n",
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"- If you find it useful: please [cite our paper](https://peerj.com/articles/453/)!\n",
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"\n",
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"---"

workshops/2015-strata/index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://groups.google.com/d/forum/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/CONTRIBUTING.txt)\n",
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"- If you find it useful: cite [our paper](https://peerj.com/articles/453/)!"
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]
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},

workshops/2016-scipy/000_index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://groups.google.com/d/forum/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/.github/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/.github/CONTRIBUTING.txt)\n",
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"- Read [our paper](https://peerj.com/articles/453/)!"
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]
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}

workshops/2017-odsc/000_index.ipynb

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"\n",
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"# Prerequisites\n",
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"\n",
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"Please refer to the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/master/preparation.md).\n",
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"Please refer to the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/main/preparation.md).\n",
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"\n",
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"\n",
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"# Sections\n",
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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://mail.python.org/mailman/listinfo/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/.github/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/.github/CONTRIBUTING.txt)\n",
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"- Read [our paper](https://peerj.com/articles/453/) (or [this one, for skimage in microscopy](https://ascimaging.springeropen.com/articles/10.1186/s40679-016-0031-0))"
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]
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},

workshops/2017-scipy/000_index.ipynb

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"\n",
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"- Follow the project's progress [on GitHub](https://github.com/scikit-image/scikit-image).\n",
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"- Ask the team questions on the [mailing list](https://mail.python.org/mailman/listinfo/scikit-image)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/master/.github/CONTRIBUTING.txt)\n",
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"- [Contribute!](https://github.com/scikit-image/scikit-image/blob/main/.github/CONTRIBUTING.txt)\n",
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"- Read [our paper](https://peerj.com/articles/453/) (or [this one, for skimage in microscopy](https://ascimaging.springeropen.com/articles/10.1186/s40679-016-0031-0))"
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]
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},

workshops/2018-scipy/index.ipynb

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"\n",
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"# Prerequisites\n",
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"\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/master/preparation.md).\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/main/preparation.md).\n",
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"\n",
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"# Schedule\n",
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"\n",

workshops/2019-euroscipy/README.md

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* Support material for the tutorial _3D image processing with scikit-image_.
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Open it using Binder: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/alexdesiqueira/tutorials/master)
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Open it using Binder: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/alexdesiqueira/tutorials/main)
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Inside Binder's structure, please point to `/2019/euroscipy2019`.
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workshops/2019-euroscipy/euroscipy2019_skimage.ipynb

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"* `segmentation.felzenszwalb`\n",
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"* `segmentation.chan_vese`\n",
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"\n",
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"There are also some supervised and unsupervised thresholding algorithms in `filters`. There is a [segmentation lecture](https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/4_segmentation.ipynb) ([and its solution](https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/solutions/4_segmentation.ipynb)) you may peruse, as well as many [gallery examples](https://scikit-image.org/docs/stable/auto_examples/index.html#segmentation-of-objects) which illustrate all of these segmentation methods.\n",
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"There are also some supervised and unsupervised thresholding algorithms in `filters`. There is a [segmentation lecture](https://github.com/scikit-image/skimage-tutorials/blob/main/lectures/4_segmentation.ipynb) ([and its solution](https://github.com/scikit-image/skimage-tutorials/blob/main/lectures/solutions/4_segmentation.ipynb)) you may peruse, as well as many [gallery examples](https://scikit-image.org/docs/stable/auto_examples/index.html#segmentation-of-objects) which illustrate all of these segmentation methods.\n",
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"[Feature extraction](https://en.wikipedia.org/wiki/Feature_extraction) reduces data required to describe an image or objects by measuring informative features. These include features such as area or volume, bounding boxes, and intensity statistics.\n",
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"source": [
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"## Going beyond\n",
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"[1] A tour/guide on scikit-image's submodules: https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/tour_of_skimage.ipynb\n",
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"[1] A tour/guide on scikit-image's submodules: https://github.com/scikit-image/skimage-tutorials/blob/main/lectures/tour_of_skimage.ipynb\n",
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"[2] scikit-image's gallery examples: https://scikit-image.org/docs/stable/auto_examples/\n",
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workshops/2019-euroscipy/setup.md

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` $ conda activate euroscipy2019_skimage`
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To come back to your master environment,
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`$ conda activate`
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workshops/2019-monash-data-fluency/index.ipynb

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"# Prerequisites\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/master/preparation.md).\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/main/preparation.md).\n",
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"# Schedule\n",
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workshops/2019-scipy/index.ipynb

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"# Prerequisites\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/master/preparation.md).\n",
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"Please see the [preparation instructions](https://github.com/scikit-image/skimage-tutorials/blob/main/preparation.md).\n",
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"# Schedule\n",
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"\n",

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