You could try: src_mono = src_rgb.astype(float).sum(axis=-1) / 3. But that speed does seem slow. Here are the relevant timings on my machine (a recent MacBook Pro) for a 3.1-megapixel-size array: In [16]: a = numpy.empty((2048, 1536, 3), dtype=numpy.uint8)
In [17]: timeit numpy.dot(a.astype(float), numpy.ones(3)/3.) 10 loops, best of 3: 116 ms per loop In [18]: timeit a.astype(float).sum(axis=-1)/3. 10 loops, best of 3: 85.3 ms per loop In [19]: timeit a.astype(float) 10 loops, best of 3: 23.3 ms per loop On Jun 20, 2011, at 4:15 PM, Alex Flint wrote: > At the moment I'm using numpy.dot to convert a WxHx3 RGB image to a grayscale > image: > > src_mono = np.dot(src_rgb.astype(np.float), np.ones(3)/3.); > > This seems quite slow though (several seconds for a 3 megapixel image) - is > there a more specialized routine better suited to this? > > Cheers, > Alex > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
