Spaces:
Runtime error
Runtime error
| import matplotlib | |
| matplotlib.use("Agg") | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| def split_title_line(title_text, max_words=5): | |
| """ | |
| A function that splits any string based on specific character | |
| (returning it with the string), with maximum number of words on it | |
| """ | |
| seq = title_text.split() | |
| return "\n".join([" ".join(seq[i:i + max_words]) for i in range(0, len(seq), max_words)]) | |
| def plot_alignment(alignment, path, title=None, split_title=False, max_len=None): | |
| if max_len is not None: | |
| alignment = alignment[:, :max_len] | |
| fig = plt.figure(figsize=(8, 6)) | |
| ax = fig.add_subplot(111) | |
| im = ax.imshow( | |
| alignment, | |
| aspect="auto", | |
| origin="lower", | |
| interpolation="none") | |
| fig.colorbar(im, ax=ax) | |
| xlabel = "Decoder timestep" | |
| if split_title: | |
| title = split_title_line(title) | |
| plt.xlabel(xlabel) | |
| plt.title(title) | |
| plt.ylabel("Encoder timestep") | |
| plt.tight_layout() | |
| plt.savefig(path, format="png") | |
| plt.close() | |
| def plot_spectrogram(pred_spectrogram, path, title=None, split_title=False, target_spectrogram=None, max_len=None, auto_aspect=False): | |
| if max_len is not None: | |
| target_spectrogram = target_spectrogram[:max_len] | |
| pred_spectrogram = pred_spectrogram[:max_len] | |
| if split_title: | |
| title = split_title_line(title) | |
| fig = plt.figure(figsize=(10, 8)) | |
| # Set common labels | |
| fig.text(0.5, 0.18, title, horizontalalignment="center", fontsize=16) | |
| #target spectrogram subplot | |
| if target_spectrogram is not None: | |
| ax1 = fig.add_subplot(311) | |
| ax2 = fig.add_subplot(312) | |
| if auto_aspect: | |
| im = ax1.imshow(np.rot90(target_spectrogram), aspect="auto", interpolation="none") | |
| else: | |
| im = ax1.imshow(np.rot90(target_spectrogram), interpolation="none") | |
| ax1.set_title("Target Mel-Spectrogram") | |
| fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax1) | |
| ax2.set_title("Predicted Mel-Spectrogram") | |
| else: | |
| ax2 = fig.add_subplot(211) | |
| if auto_aspect: | |
| im = ax2.imshow(np.rot90(pred_spectrogram), aspect="auto", interpolation="none") | |
| else: | |
| im = ax2.imshow(np.rot90(pred_spectrogram), interpolation="none") | |
| fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax2) | |
| plt.tight_layout() | |
| plt.savefig(path, format="png") | |
| plt.close() | |