see also Cookbook/Matplotlib/LoadImage to load a PNG image
Python Imaging Library
Apply this patch to make PIL Image objects both export and consume the array interface (from Travis Oliphant):
Index: PIL/Image.py
===================================================================
--- PIL/Image.py (revision 358)
+++ PIL/Image.py (working copy)
@@ -187,6 +187,42 @@
}
+if sys.byteorder == 'little':
+ _ENDIAN = '<'
+else:
+ _ENDIAN = '>'
+
+_MODE_CONV = {
+
+ # official modes
+ "1": ('|b1', None),
+ "L": ('|u1', None),
+ "I": ('%si4' % _ENDIAN, None),
+ "F": ('%sf4' % _ENDIAN, None),
+ "P": ('|u1', None),
+ "RGB": ('|u1', 3),
+ "RGBX": ('|u1', 4),
+ "RGBA": ('|u1', 4),
+ "CMYK": ('|u1', 4),
+ "YCbCr": ('|u1', 4),
+
+ # Experimental modes include I;16, I;16B, RGBa, BGR;15,
+ # and BGR;24. Use these modes only if you know exactly
+ # what you're doing...
+
+}
+
+def _conv_type_shape(im):
+ shape = im.size[::-1]
+ typ, extra = _MODE_CONV[im.mode]
+ if extra is None:
+ return shape, typ
+ else:
+ return shape+(extra,), typ
+
+
+
+
MODES = _MODEINFO.keys()
MODES.sort()
@@ -491,6 +527,22 @@
return string.join(data, "")
##
+ # Returns the array_interface dictionary
+ #
+ # @return A dictionary with keys 'shape', 'typestr', 'data'
+
+ def __get_array_interface__(self):
+ new = {}
+ shape, typestr = _conv_type_shape(self)
+ new['shape'] = shape
+ new['typestr'] = typestr
+ new['data'] = self.tostring()
+ return new
+
+ __array_interface__ = property(__get_array_interface__, None, doc="array interface")
+
+
+ ##
# Returns the image converted to an X11 bitmap. This method
# only works for mode "1" images.
#
@@ -1749,7 +1801,61 @@
return apply(fromstring, (mode, size, data, decoder_name, args))
+
##
+# (New in 1.1.6) Create an image memory from an object exporting
+# the array interface (using the buffer protocol).
+#
+# If obj is not contiguous, then the tostring method is called
+# and frombuffer is used
+#
+# @param obj Object with array interface
+# @param mode Mode to use (will be determined from type if None)
+
+def fromarray(obj, mode=None):
+ arr = obj.__array_interface__
+ shape = arr['shape']
+ ndim = len(shape)
+ try:
+ strides = arr['strides']
+ except KeyError:
+ strides = None
+ if mode is None:
+ typestr = arr['typestr']
+ if not (typestr[0] == '|' or typestr[0] == _ENDIAN or
+ typestr[1:] not in ['u1', 'b1', 'i4', 'f4']):
+ raise TypeError, "cannot handle data-type"
+ typestr = typestr[:2]
+ if typestr == 'i4':
+ mode = 'I'
+ elif typestr == 'f4':
+ mode = 'F'
+ elif typestr == 'b1':
+ mode = '1'
+ elif ndim == 2:
+ mode = 'L'
+ elif ndim == 3:
+ mode = 'RGB'
+ elif ndim == 4:
+ mode = 'RGBA'
+ else:
+ raise TypeError, "Do not understand data."
+ ndmax = 4
+ bad_dims=0
+ if mode in ['1','L','I','P','F']:
+ ndmax = 2
+ elif mode == 'RGB':
+ ndmax = 3
+ if ndim > ndmax:
+ raise ValueError, "Too many dimensions."
+
+ size = shape[:2][::-1]
+ if strides is not None:
+ obj = obj.tostring()
+
+ return frombuffer(mode, size, obj)
+
+##
# Opens and identifies the given image file.
# <p>
# This is a lazy operation; this function identifies the file, but the
Exemple
>>> import Image
>>> im=Image.open('foo1.png')
>>> a=numpy.array(p)
# do something with a ...
>>> im = Image.fromarray(a)
>>> im.save( 'foo2.png' )