Mercurial > releases > comm-beta / file revision / build/pypng/exnumpy.py@5576f057ebbd3e81298c72d4bf55e50a2cacb4b5

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build/pypng/exnumpy.py

author | Neil Rashbrook <neil@parkwaycc.co.uk> |

Mon, 30 Mar 2015 00:42:42 +0100 | |

changeset 21680 | 5576f057ebbd3e81298c72d4bf55e50a2cacb4b5 |

parent 8729 | 923b924c9422bddc54a3d8c08b765da58dddeedd |

permissions | -rw-r--r-- |

Bug 962910 Find bar should use a system key event listener r=Ratty a=IanN
a=Ratty for checkin to a CLOSED TREE

#!/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()