Crepe pitch detection in PyTorch
Project description
TorchCrepeV2
My own version of crepe in PyTorch, SOTA pitch tracking tool. Releasing as pip package for ease of usage.
Only full
version of model is supported.
Similar project: https://github.com/maxrmorrison/torchcrepe
Usage
pip install git+https://github.com/gudgud96/torchcrepeV2
from torchcrepeV2 import TorchCrepePredictor
import numpy as np
import matplotlib.pyplot as plt
y, sr = librosa.load("some_audio.wav", sr=16000)
torch_crepe = TorchCrepePredictor(device="cuda")
# all arguments are aligned with original crepe implementation
f = torch_crepe.predict(y=y,
sr=sr,
viterbi=True,
center=True,
step_size=10)
# can add some post-processing
block_size = 100
length = y.shape[0] // 100
if f.shape[-1] != length:
f = np.interp(
np.linspace(0, 1, length, endpoint=False),
np.linspace(0, 1, f.shape[-1], endpoint=False),
f,
)
plt.plot(f, label='torchcrepe')
plt.show()
Results
Tracked pitch nearly identical as compared to crepe
.
TODO
- Optimize inference performance
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