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Init ppg extractor and ppg2mel (#375)

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* Init  ppg extractor and ppg2mel

* add preprocess and training

* FIx known issues

* Update __init__.py

Allow to gen audio

* Fix length issue

* Fix bug of preparing fid

* Fix sample issues

* Add UI usage of PPG-vc
This commit is contained in:
Vega
2022-03-03 23:38:12 +08:00
committed by GitHub
parent ad22997614
commit b617a87ee4
57 changed files with 6385 additions and 80 deletions
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27
encoder/inference.py
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@@ -34,8 +34,16 @@ def load_model(weights_fpath: Path, device=None):
_model.load_state_dict(checkpoint["model_state"])
_model.eval()
print("Loaded encoder \"%s\" trained to step %d" % (weights_fpath.name, checkpoint["step"]))
return _model
def set_model(model, device=None):
global _model, _device
_model = model
if device is None:
_device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
_device = device
_model.to(device)
def is_loaded():
return _model is not None
@@ -57,7 +65,7 @@ def embed_frames_batch(frames_batch):
def compute_partial_slices(n_samples, partial_utterance_n_frames=partials_n_frames,
min_pad_coverage=0.75, overlap=0.5):
min_pad_coverage=0.75, overlap=0.5, rate=None):
"""
Computes where to split an utterance waveform and its corresponding mel spectrogram to obtain
partial utterances of <partial_utterance_n_frames> each. Both the waveform and the mel
@@ -85,9 +93,18 @@ def compute_partial_slices(n_samples, partial_utterance_n_frames=partials_n_fram
assert 0 <= overlap < 1
assert 0 < min_pad_coverage <= 1
samples_per_frame = int((sampling_rate * mel_window_step / 1000))
n_frames = int(np.ceil((n_samples + 1) / samples_per_frame))
frame_step = max(int(np.round(partial_utterance_n_frames * (1 - overlap))), 1)
if rate != None:
samples_per_frame = int((sampling_rate * mel_window_step / 1000))
n_frames = int(np.ceil((n_samples + 1) / samples_per_frame))
frame_step = int(np.round((sampling_rate / rate) / samples_per_frame))
else:
samples_per_frame = int((sampling_rate * mel_window_step / 1000))
n_frames = int(np.ceil((n_samples + 1) / samples_per_frame))
frame_step = max(int(np.round(partial_utterance_n_frames * (1 - overlap))), 1)
assert 0 < frame_step, "The rate is too high"
assert frame_step <= partials_n_frames, "The rate is too low, it should be %f at least" % \
(sampling_rate / (samples_per_frame * partials_n_frames))
# Compute the slices
wav_slices, mel_slices = [], []