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import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import torch
LINE_COLORS = ['w', 'r', 'orange', 'k', 'cyan', 'm', 'b', 'lime', 'g', 'brown', 'navy']
def spec_to_figure(spec, vmin=None, vmax=None, title='', f0s=None, dur_info=None):
if isinstance(spec, torch.Tensor):
spec = spec.cpu().numpy()
H = spec.shape[1] // 2
fig = plt.figure(figsize=(12, 6))
plt.title(title)
plt.pcolor(spec.T, vmin=vmin, vmax=vmax)
if dur_info is not None:
assert isinstance(dur_info, dict)
txt = dur_info['txt']
dur_gt = dur_info['dur_gt']
if isinstance(dur_gt, torch.Tensor):
dur_gt = dur_gt.cpu().numpy()
dur_gt = np.cumsum(dur_gt).astype(int)
for i in range(len(dur_gt)):
shift = (i % 8) + 1
plt.text(dur_gt[i], shift * 4, txt[i])
plt.vlines(dur_gt[i], 0, H // 2, colors='b') # blue is gt
plt.xlim(0, dur_gt[-1])
if 'dur_pred' in dur_info:
dur_pred = dur_info['dur_pred']
if isinstance(dur_pred, torch.Tensor):
dur_pred = dur_pred.cpu().numpy()
dur_pred = np.cumsum(dur_pred).astype(int)
for i in range(len(dur_pred)):
shift = (i % 8) + 1
plt.text(dur_pred[i], H + shift * 4, txt[i])
plt.vlines(dur_pred[i], H, H * 1.5, colors='r') # red is pred
plt.xlim(0, max(dur_gt[-1], dur_pred[-1]))
if f0s is not None:
ax = plt.gca()
ax2 = ax.twinx()
# ax.set_xticks()
if not isinstance(f0s, dict):
f0s = {'f0': f0s}
for i, (k, f0) in enumerate(f0s.items()):
if f0 is not None:
if isinstance(f0, torch.Tensor):
f0 = f0.cpu().numpy()
ax2.plot(
np.arange(len(f0)) + 0.5, f0, label=k, c=LINE_COLORS[i], linewidth=1, alpha=0.5)
ax2.set_ylim(0, 1000)
ax2.legend()
return fig
def align_to_figure(align, dur_info):
if isinstance(align, torch.Tensor):
align = align.cpu().numpy()
H = align.shape[1]
fig = plt.figure(figsize=(12, 6))
plt.pcolor(align.T, vmin=0, vmax=1)
if dur_info is not None:
assert isinstance(dur_info, dict)
txt = dur_info['txt']
dur_gt = dur_info['dur_gt']
if isinstance(dur_gt, torch.Tensor):
dur_gt = dur_gt.cpu().numpy()
dur_gt = np.cumsum(dur_gt).astype(int) // 2
for i in range(len(dur_gt)):
plt.text(dur_gt[i], i, txt[i], color='red')
plt.vlines(dur_gt[i], 0, H, colors='b') # blue is gt
# plt.xlim(0, dur_gt[-1])
return fig
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