Python: How to generate log-frequency spectrogram from an audio?

Question

I want to make a log-frequency spectrogram out of this audio. Later, I need this spectrogram for pitch sequence analysis.

This is a sample sequence I want to achieve:

[ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0
  0  0  0  0 18 18 19 19 19 19 19 19 19 19 18  0  0  0  0 19 18 18 18 19
 19 19 19 19 19 19 20 20  0  0  0 25 26 26 26 26 26 26 26 26 25  0  0  0
  0  0 26 25 25 25 25 25 25 25 25 25 25 26 26 27 27 27 27 28 28 28 28 28
 28 28 28 28 27 26 27  0 28 28 28 28 28 28 28 28 28 27 26  0  0 26 26 26
 26 26 26 26 26 26 26 26 26 26 26 26 25 25  0  0  0  0  0  0  0  0  0  0
  0  0  0  0  0 24 24 24 24 24 24 24 24 24 24 24 24 24 24  0  0  0 25 24
 24 23 23 23 23 24 24 24 24 23 23 23 23 23 22 22 22 23 23 23 23 23 23 23
 22 23 23  0  0  0 23 23 23 22 23 23 23 23 23 23 22 22 23 22 23 22 21 21
 21 21 21 21 21 21 21 21 22  0  0  0 21 21 21 21 21 21 21 21 21 21 21 20
  0  0  0  0 19 19 19 19 19 19]

From what I am able to do now, I can only plot the audio using a linear scale spectrogram, with this code:

def make_spectrogram_b(songname, titles, filename):
  x, sr = librosa.load(songname, sr=None) #sr=None, buat dapet aslinya
  duration = librosa.get_duration(filename=songname)

  print("Audio shape: ", x.shape)
  print("Sample rate: ", sr)
  print("Duration of audio: ", duration)

  # compute stft
  window = np.hanning(window_size) # window size = 1024; hop_length = 256
  stft= librosa.core.spectrum.stft(x, n_fft = window_size, hop_length = hop_length, window = window)
  out = 2 * np.abs(stft) / np.sum(window)

  # plot result
  plt.figure(figsize=(12, 4))
  ax = plt.axes()
  ax.set_axis_off()
  librosa.display.specshow(librosa.amplitude_to_db(out, ref=np.max), y_axis='log', x_axis='time',sr=sr)
  plt.savefig(f'spectrogram_data_B/{titles}/{filename[:-3].replace(".", "")}.png', bbox_inches='tight', transparent=True, pad_inches=0.0)
  plt.clf() 

This here is an output sample from code above. My testing result is not so satisfying, as it detects too many zero pitch values, and I think I want to change the spectrogram type.

I read from a book source (Muller, Fundamentals of Music Processing, 2015), that if we want to make a spectrogram for music analysis, we must make a log-frequency spectrogram, as quoted:

To emphasize musical or tonal relationships, the frequency axis is often plotted in a logarithmic fashion, which yields a log-frequency representation. A logarithmic frequency axis also accounts for the fact that human perception of pitch is logarithmic in nature. Finally, in the case of audio signals, the amplitude values are also often visualized using a logarithmic scale, for example, by using a decibel scale. In this way, small intensity values of perceptual relevance become visible in the image. In the following, if not specified otherwise, we use in our visualizations a linear frequency axis and a logarithmic scale to represent amplitudes. The specific scale is not of importance, but only serves the purpose of enhancing the qualitative properties of the visualization.

In Python, how can I plot this log-frequency spectrogram? Or, is there any better way to 'convert' audio given above to a visual representation for pitch analysis?