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NumPy Cookbook

You're reading from  NumPy Cookbook

Product type Book
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Pages 226 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts 3. Get to Grips with Commonly Used Functions 4. Connecting NumPy with the Rest of the World 5. Audio and Image Processing 6. Special Arrays and Universal Functions 7. Profiling and Debugging 8. Quality Assurance 9. Speed Up Code with Cython 10. Fun with Scikits Index

Using the buffer protocol


C-based Python objects have a so called "buffer interface". Python objects can expose their data for direct access without the need to copy it. The buffer protocol enables us to communicate with other Python software such as the Python Imaging Library (PIL) . We will see an example of saving a PIL image from a NumPy array.

Getting ready

Install PIL and SciPy, if necessary. Check the See Also section of this recipe for instructions.

How to do it...

First, we need a NumPy array with which to play.

  1. Create an array from image data.

    In previous chapters, we saw how to load the "Lena" sample image of Lena Soderberg. We will create an array filled with zeroes, and populate the alpha channel with the image data:

    lena = scipy.misc.lena()
    data = numpy.zeros((lena.shape[0], lena.shape[1], 4), dtype=numpy.int8)
    data[:,:,3] = lena.copy()
  2. Save the data as a PIL image.

    Now, we will use the PIL API to save the data as a RGBA image:

    img = Image.frombuffer("RGBA", lena.shape, data)
    img.save...
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