Last updated: Sat Nov 26 13:49:28 BRST 2016


Git Download

The most up-to-date SIP version can be downloaded from Git. These instructions should work for any Unix, althought they have been tested on Ubuntu Linux and Mac OS. For Ubuntu users, there is an automation step below.

  1. Download animal from Git:
    • git clone git://
    For write access:
    • git clone ssh://
  2. Download SIP itself from Git:
    • git clone git://
    For write access:
    • git clone ssh://
  3. Install Animal:
    • cd animal
    • Make sure you have installed automake and autoconf. The following command bootstraps the build system
    • ./
    • ./configure
    • make
    • sudo make install
    • Now rehash the library cache so that SIP can find it:
    • sudo ldconfig
  4. Install SIP itself:
    • cd ../siptoolbox
    • ./
    • ./configure
    • make
    • sudo make install
    Optionally, to automatically load SIP at scilab startup, type, as a regular user:
    • make autoload

Ubuntu users: try the following automator script:

wget -O- | sh

Additional instructions, including a web view of the repository can be found at [Souceforge generic instructions].

This is the development homepage of the SIP toolbox. Here you can find advanced and backstage information on SIP, and have an idea of what SIP might become in some time from now.

Please keep the following notes in mind when dealing with the SIP development version.

  • SIP is beta software, and consider the development version as alpha software: it is intended for developers and advanced users, it is not stable, and will change very fast. Excuse us for programming errors, which may be frequent. Please contribute with corrections, suggestions, and code.
  • Please read the *.txt files that come with the SIP development source, before any serious attempt to use or modify it. They have many information that are not in this home page.
  • There might be some personal comments throughout the code.
SIGN UP the SIP developer's e-mail list. Please consider becoming a contributor/developer. Send your code, suggestions and bugfixes to this list, and we might include it in the next SIP release, with your name in it.

The following text (in Portuguese) has information on SIP's design and internals. Appendix B shows step-by-step how to add a new routine to SIP.

To Do

Old windows port

There is a new complete tasklist at Sourceforge:

TO-DO List

To see where you can contribute, browse the open tasks which are unassigned. Please don't hesitate in suggesting other tasks.

We need somebody to port SIP for windows.

I've been working a lot with distance transforms and related entities such as skeletonization, Voronoi diagrams, and level sets, since these are the subject of my grad research.

Another important addition currently under development is the use of SciLab integer types. This will make SIP much more efficient.

Making a true-size fast image display is one of the most important improvements to be made. Image display is still not good in SIP/SciLab, because Matplot uses rectangle primitives instead of pixel buffer X11 primitive. Please help us!

Many other additions and improvements need to be made. See the to-do list above.

I have a dream that one day SIP/SciLab will be the standard free prototyping environment for image processing, used and developed by people all over the world. There are, of course, many obstacles to overcome before this dream come true.

Some years ago, SIP had only a single developer - me. There are very few (if any) software that got robust with a team of a single person. Free, open-source software relies on joint development to be as good as commercial software. ImageMagick has about 5 developers, GIMP has about 100, and KDE about 1000. I try to make SIP as useful as I can, but cannot make any miracle alone. A single person developing free software is not like a company which is paid for doing what people want. As such, I have my personal interests with SIP, and must give end-user needs a lesser priority. (In the last months this has been changing. We now have three active co-developers contributing with code and testing: Jocelyn Druel, Leandro Estrozi and Bruno Pincon).

My primary objective with SIP is for learning. I want to improve my knowledge of computer vision algorithms and some C programming, while having some fun making a useful package. Making a lightning-fast, rock-solid and shiny package is not my direct objective. But this does not mean that SIP cannot be all that. It just means that I personally will not be much concerned with those issues.

SIP is free software, and as such I invite you to help me develop it. If you need a very fast package with very easy installation procedure, you are invited to contribute. If you need a particular image processing routine, please write it and send it to me. It's an advantage you get being able to directly shape SIP to your particular needs. In addition, if your contribution is continued, I am willing to share the authorship with you. For my part, I'll be concentrated in the algorithms I use for my particular research and interests. Of course, I will be accepting suggestions and feature requests, but I will give priority to the stuff I have personal interest.

The format of the SIP development branch is sip-dev-YYYYMMDD, according to the date of the release.

The versioning of the SIP stable branch follows the overall GNU recommendation. The format is Major.Minor.Patchlevel. However, the interpretation of the numbers is not standard, so for SIP it is described in the table bellow.

Number Why it changes Period of Change (ideally)
Major The software goes to a totally new level of stability and functionality 1 - 2 years
Minor Significant functionality has been added 1 - 2 months
Patchlevel Bugfixes and minor improvement 1 - 2 weeks

When the Major number is zero, we consider that SIP is in a special evolving stage. In that stage, changes and improvements in occur at a fast pace. The software is useful and fairly stable, but has not reached the final objective. In the case of SIP, the final objective is to make a complete image processing package, with functions for every task in this area: image I/O, segmentation, grayscale image processing, binary image processing, shape classification and recognition, etc.

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