text stringlengths 0 5.54k |
|---|
n_fft: int = 2048 |
hop_length: int = 512 |
top_db: int = 80 |
n_iter: int = 32 |
) |
Parameters |
x_res (int) — x resolution of spectrogram (time) |
y_res (int) — y resolution of spectrogram (frequency bins) |
sample_rate (int) — sample rate of audio |
n_fft (int) — number of Fast Fourier Transforms |
hop_length (int) — hop length (a higher number is recommended for lower than 256 y_res) |
top_db (int) — loudest in decibels |
n_iter (int) — number of iterations for Griffin Linn mel inversion |
audio_slice_to_image |
< |
source |
> |
( |
slice: int |
) |
→ |
PIL Image |
Parameters |
slice (int) — slice number of audio to convert (out of get_number_of_slices()) |
Returns |
PIL Image |
grayscale image of x_res x y_res |
Convert slice of audio to spectrogram. |
get_audio_slice |
< |
source |
> |
( |
slice: int = 0 |
) |
→ |
np.ndarray |
Parameters |
slice (int) — slice number of audio (out of get_number_of_slices()) |
Returns |
np.ndarray |
audio as numpy array |
Get slice of audio. |
get_number_of_slices |
< |
source |
> |
( |
) |
→ |
int |
Returns |
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