Interpret numpy.fft.fft2 output My goal is to obtain a plot with the spatial frequencies of an image - kind of like doing a fourier transformation on it. I don't care about the position on the image of features with the frequency f (for instance); I'd just like to have a graphic which tells me how much of every frequency I have (the amplitude for a frequency band could be represented by the sum of contrasts with that frequency).

I am trying to do this via the numpy.fft.fft2 function.

Here is a link to a minimal example portraying my use case.

As it turns out I only get distinctly larger values for frequencies[:30,:30], and of these the absolute highest value is frequencies[0,0]. How can I interpret this? 


What exactly does the amplitude of each value stand for?
What does it mean that my highest value is in frequency[0,0] What is a 0 Hz frequency?
Can I bin the values somehow so that my frequency spectrum is orientation agnostic?
You actually did a two dimensional Fourier transform there. The 0 Hz frequency is the ,,DC offset'' of your signal, that is, its average value. In computers, it's no wonder that there's a high average value, because signals are often defined using positive numbers.

In a 2D Fourier transform, the coefficients of the transformed correspond to products of 1D Fourier basis elements, that is, signals with a period equal to the length of the signal. You could call these overtones.

2D Products of two such signals are not ,,orientation agnostic''. In fact, they have obvious orientation along the edges of the signal. It is not entirely clear what you are asking for here.