Geospatial Development By Example with Python
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Installing packages and required software

In this topic, we will go through the installation process of every package used in the book.

OpenCV

OpenCV is an optimized C/C++ library intended for video and image processing with hundreds of functions ranging from simple image resizing to object recognition, face detection, and so on. OpenCV is a big library, and we will use its capabilities of reading, transforming, and writing images. It's a good choice because its development is active, and it has a large user community and very good documentation.

Windows

Here is the installation procedure for Windows:

  1. Go to http://www.lfd.uci.edu/~gohlke/pythonlibs/.
  2. Press Ctrl + F to open the search dialog of your browser and then search for OpenCV.
  3. You will find a list of files; choose opencv_python‑2.4.11‑cp27‑none‑win32.whl or any OpenCV version that contains cp27 and win32. This means that this is the 32-bit version for Python 2.7.
  4. Save the downloaded file to a known location.
  5. Open Windows Command Prompt and run the following command:
    c:\Python27\scripts\pip install path_to_the_file_you_downloaded.whl
    
  6. You should see an output telling you that the installation was successful, as follows:
    Processing c:\downloads\opencv_python-2.4.12-cp27-none-win32.whl
    Installing collected packages: opencv-python
    Successfully installed opencv-python-2.4.12
    

    Tip

    You can drag and drop a file into the command prompt to enter its full path.

Ubuntu Linux

Here is the installation process for Ubuntu Linux:

  1. Open a new terminal with Ctrl + T.
  2. Then, enter the following command:
    sudo apt-get install python-opencv