57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import torch
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LINE_COLORS = ['w', 'r', 'y', 'cyan', 'm', 'b', 'lime']
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def spec_to_figure(spec, vmin=None, vmax=None):
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if isinstance(spec, torch.Tensor):
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spec = spec.cpu().numpy()
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fig = plt.figure(figsize=(12, 6))
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plt.pcolor(spec.T, vmin=vmin, vmax=vmax)
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return fig
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def spec_f0_to_figure(spec, f0s, figsize=None):
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max_y = spec.shape[1]
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if isinstance(spec, torch.Tensor):
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spec = spec.detach().cpu().numpy()
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f0s = {k: f0.detach().cpu().numpy() for k, f0 in f0s.items()}
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f0s = {k: f0 / 10 for k, f0 in f0s.items()}
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fig = plt.figure(figsize=(12, 6) if figsize is None else figsize)
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plt.pcolor(spec.T)
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for i, (k, f0) in enumerate(f0s.items()):
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plt.plot(f0.clip(0, max_y), label=k, c=LINE_COLORS[i], linewidth=1, alpha=0.8)
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plt.legend()
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return fig
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def dur_to_figure(dur_gt, dur_pred, txt):
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dur_gt = dur_gt.long().cpu().numpy()
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dur_pred = dur_pred.long().cpu().numpy()
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dur_gt = np.cumsum(dur_gt)
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dur_pred = np.cumsum(dur_pred)
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fig = plt.figure(figsize=(12, 6))
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for i in range(len(dur_gt)):
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shift = (i % 8) + 1
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plt.text(dur_gt[i], shift, txt[i])
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plt.text(dur_pred[i], 10 + shift, txt[i])
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plt.vlines(dur_gt[i], 0, 10, colors='b') # blue is gt
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plt.vlines(dur_pred[i], 10, 20, colors='r') # red is pred
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return fig
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def f0_to_figure(f0_gt, f0_cwt=None, f0_pred=None):
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fig = plt.figure()
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f0_gt = f0_gt.cpu().numpy()
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plt.plot(f0_gt, color='r', label='gt')
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if f0_cwt is not None:
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f0_cwt = f0_cwt.cpu().numpy()
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plt.plot(f0_cwt, color='b', label='cwt')
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if f0_pred is not None:
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f0_pred = f0_pred.cpu().numpy()
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plt.plot(f0_pred, color='green', label='pred')
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plt.legend()
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return fig
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