palemoon-dev/build/pypng/exnumpy.py

#!/usr/bin/env python
# $URL: http://pypng.googlecode.com/svn/trunk/code/exnumpy.py $
# $Rev: 126 $

# Numpy example.
# Original code created by Mel Raab, modified by David Jones.

'''
  Example code integrating RGB PNG files, PyPNG and NumPy
  (abstracted from Mel Raab's functioning code)
'''

# http://www.python.org/doc/2.4.4/lib/module-itertools.html
import itertools

import numpy
import png


''' If you have a PNG file for an RGB image,
    and want to create a numpy array of data from it.
'''
# Read the file "picture.png" from the current directory.  The `Reader`
# class can take a filename, a file-like object, or the byte data
# directly; this suggests alternatives such as using urllib to read
# an image from the internet:
# png.Reader(file=urllib.urlopen('http://www.libpng.org/pub/png/PngSuite/basn2c16.png'))
pngReader=png.Reader(filename='picture.png')
# Tuple unpacking, using multiple assignment, is very useful for the
# result of asDirect (and other methods).
# See
# http://docs.python.org/tutorial/introduction.html#first-steps-towards-programming
row_count, column_count, pngdata, meta = pngReader.asDirect()
bitdepth=meta['bitdepth']
plane_count=meta['planes']

# Make sure we're dealing with RGB files
assert plane_count == 3

''' Boxed row flat pixel:
      list([R,G,B, R,G,B, R,G,B],
           [R,G,B, R,G,B, R,G,B])
    Array dimensions for this example:  (2,9)

    Create `image_2d` as a two-dimensional NumPy array by stacking a
    sequence of 1-dimensional arrays (rows).
    The NumPy array mimics PyPNG's (boxed row flat pixel) representation;
    it will have dimensions ``(row_count,column_count*plane_count)``.
'''
# The use of ``numpy.uint16``, below, is to convert each row to a NumPy
# array with data type ``numpy.uint16``.  This is a feature of NumPy,
# discussed further in 
# http://docs.scipy.org/doc/numpy/user/basics.types.html .
# You can use avoid the explicit conversion with
# ``numpy.vstack(pngdata)``, but then NumPy will pick the array's data
# type; in practice it seems to pick ``numpy.int32``, which is large enough
# to hold any pixel value for any PNG image but uses 4 bytes per value when
# 1 or 2 would be enough.
# --- extract 001 start
image_2d = numpy.vstack(itertools.imap(numpy.uint16, pngdata))
# --- extract 001 end
# Do not be tempted to use ``numpy.asarray``; when passed an iterator
# (`pngdata` is often an iterator) it will attempt to create a size 1
# array with the iterator as its only element.
# An alternative to the above is to create the target array of the right
# shape, then populate it row by row:
if 0:
    image_2d = numpy.zeros((row_count,plane_count*column_count),
                           dtype=numpy.uint16)
    for row_index, one_boxed_row_flat_pixels in enumerate(pngdata):
        image_2d[row_index,:]=one_boxed_row_flat_pixels

del pngReader
del pngdata


''' Reconfigure for easier referencing, similar to
        Boxed row boxed pixel:
            list([ (R,G,B), (R,G,B), (R,G,B) ],
                 [ (R,G,B), (R,G,B), (R,G,B) ])
    Array dimensions for this example:  (2,3,3)

    ``image_3d`` will contain the image as a three-dimensional numpy
    array, having dimensions ``(row_count,column_count,plane_count)``.
'''
# --- extract 002 start
image_3d = numpy.reshape(image_2d,
                         (row_count,column_count,plane_count))
# --- extract 002 end


''' ============= '''

''' Convert NumPy image_3d array to PNG image file.

    If the data is three-dimensional, as it is above, the best thing
    to do is reshape it into a two-dimensional array with a shape of
    ``(row_count, column_count*plane_count)``.  Because a
    two-dimensional numpy array is an iterator, it can be passed
    directly to the ``png.Writer.write`` method.
'''

row_count, column_count, plane_count = image_3d.shape
assert plane_count==3

pngfile = open('picture_out.png', 'wb')
try:
    # This example assumes that you have 16-bit pixel values in the data
    # array (that's what the ``bitdepth=16`` argument is for).
    # If you don't, then the resulting PNG file will likely be
    # very dark.  Hey, it's only an example.
    pngWriter = png.Writer(column_count, row_count,
                           greyscale=False,
                           alpha=False,
                           bitdepth=16)
    # As of 2009-04-13 passing a numpy array that has an element type
    # that is a numpy integer type (for example, the `image_3d` array has an
    # element type of ``numpy.uint16``) generates a deprecation warning.
    # This is probably a bug in numpy; it may go away in the future.
    # The code still works despite the warning.
    # See http://code.google.com/p/pypng/issues/detail?id=44
# --- extract 003 start
    pngWriter.write(pngfile,
                    numpy.reshape(image_3d, (-1, column_count*plane_count)))
# --- extract 003 end
finally:
    pngfile.close()