Hi Stefan:
  "segmentation lesson from the skimage_tutorial repo" did you means this?(https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/4_segmentation.ipynb), I am writing a simple imageprocessing book, It may be useful for me.

Best regards
YXDragon
----- 原始邮件 -----
发件人：Stefan van der Walt <stefanv@berkeley.edu>
收件人：Alexandre Fioravante de Siqueira <siqueiraaf@gmail.com>, scikit-image@python.org
主题：Re: [scikit-image] Code for the short course 'Image Processing using Python', @ IAMG2017
日期：2017年09月21日 05点16分

Hi Alex

On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote:
as I said in an old previous e-mail, I presented a short course using scikit-image for processing microscopy images at IAMG2017 (short course 8 at <http://iamg2017.com/courses/>).
An alpha version of the codes is now available; please feel free to check it at <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>.

Thanks for sharing these!

Since it is still very raw, I'd be glad to receive your comments, suggestions and ideas!

I'd say 1) stick to gray, viridis, and other reliable colormaps and 2) plot the found features so that they are easier to observe (currently just pixels inside a big image).

You may also want to take a look at the segmentation lesson from the skimage_tutorial repo, which has a few sketches to clarify the workings of watershed.

Best regards
Stéfan

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