Rendering a float array to 24-bit RGB image (using PIL for example)

Question

x is a numpy.float32 array, with values from -200 to 0. These are dB (decibel) values.

When I do (as recommended here):

Image.fromarray(x, mode='F')

I get a greyscale or sometimes nearly black image.

How to map a float in [-200, 0] to a 24-bit RGB byte array (using a colormap) that can be read with the Python module PIL with Image.fromarray(x, mode='RGB') ?

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Edit:

The required .wav audio file is here, for which we want to plot the spectrogram.

Here is some code to test:

import scipy, numpy as np
import scipy.io.wavfile as wavfile
import numpy as np
from PIL import Image

def stft(x, fftsize=1024, overlap=4): 
    hop = fftsize / overlap
    w = scipy.hanning(fftsize+1)[:-1]
    return np.array([np.fft.rfft(w*x[i:i+fftsize]) for i in range(0, len(x)-fftsize, hop)])
    
def dB(ratio):
    return 20 * np.log10(ratio+1e-10)

def magnitudedB(frame, fftsize=1024):
    w = scipy.hanning(fftsize+1)[:-1]
    ref = np.sum(w) / 2
    return dB(np.abs(frame) / ref)

sr, x = wavfile.read('test.wav')

x = np.float32(x) / 2**15

s = magnitudedB(stft(x)).astype(np.float32).transpose()[::-1,]
print "Max %.1f dB, Min %.1f dB" % (np.max(s), np.min(s))

im = Image.fromarray(s+200, mode='F')
im.show()

Notes:

• The colormap is greyscale, how to get another colormap? like this one

• My only requirement is that the output image can be read into a Tkinter frame / canvas (it works well with PIL's im = Image.fromarray(...) then ImageTk.PhotoImage(image=im)) or wxPython frame / canvas.

Answer 1

Based on the answer here, you can use matplotlib colormaps to transform the numpy array before converting to an image.

#im = Image.fromarray(s+200, mode='F')
from matplotlib import cm
s = (s + 200)/200.0 # input data should range from 0-1
im = Image.fromarray(cm.jet(s, bytes=True))
im.show()

You should probably set the scaling appropriately based on your min/max values.

Sample output: