Grayscale image to NumPy array for Fourier transform
fft, image-processing, numpy, python, python-imaging-library
Solution
You want to use the mode 'L' instead of 'LA' as the parameter to the convert() method. 'LA' leaves an alpha channel and then the numpy.asarray doesn't work as you intended. If you need the alpha channel, then you will need a different method to convert to a numpy array. Otherwise, use mode 'L'.
Problem
Currently I'm using PIL and NumPy. I have a colored `png` image and I want to: - Read it in in grayscale - Convert to NumPy array - Perform a FFT on array - Display the image This is what I'm trying (in IPython w/ `--pylab` flag): ``` In [1]: import Image In [2]: img = Image.open('ping.png').convert('LA') In [3]: img_as_np = np.asarray(img) In [4]: img_as_np Out[4]: array(<Image.Image image mode=LA size=1000x1000 at 0x105802950>, dtype=object) In [5]: img_fft = fft.fft2(img_as_np) // IndexError: index out of range for array ```