================================= Getting help on using ``skimage`` ================================= Besides the user guide, there exist other opportunities to get help on using ``skimage``. Examples gallery ---------------- The :ref:`examples_gallery` gallery provides graphical examples of typical image processing tasks. By a quick glance at the different thumbnails, the user may find an example close to a typical use case of interest. Each graphical example page displays an introductory paragraph, a figure, and the source code that generated the figure. Downloading the Python source code enables one to modify quickly the example into a case closer to one's image processing applications. Users are warmly encouraged to report on their use of ``skimage`` on the :ref:`mailing_list`, in order to propose more examples in the future. Contributing examples to the gallery can be done on github (see :ref:`howto_contribute`). Search field ------------ The ``quick search`` field located in the navigation bar of the html documentation can be used to search for specific keywords (segmentation, rescaling, denoising, etc.). Docstrings ---------- Docstrings of ``skimage`` functions are formatted using `Numpy's documentation standard `_, starting with a ``Parameters`` section for the arguments and a ``Returns`` section for the objects returned by the function. Also, most functions include one or more examples. .. _mailing_list: Mailing-list ------------ The scikit-image mailing-list is scikit-image@googlegroups.com (users should join the `Google Group `_ before posting). This mailing-list is shared by users and developers, and it is the right place to ask any question about ``skimage``, or in general, image processing using Python. Posting snippets of code with minimal examples ensures to get more relevant and focused answers. We would love to hear from how you use ``skimage`` for your work on the mailing-list!