Skip to main content

The official Pytorch implementation of Fast Context-based Pitch Estimation (FCPE)

Project description

TorchFCPE

Useage

from torchfcpe import spawn_bundled_infer_model
import torch
import librosa

# configure device and target hop_size
device = 'cpu'
sr = 16000
hop_size = 160

# load audio
audio, sr = librosa.load('test.wav', sr=sr)
audio = librosa.to_mono(audio)
audio_length = len(audio)
f0_target_length=(audio_length // hop_size) + 1
audio = torch.from_numpy(audio).float().unsqueeze(0).unsqueeze(-1).to(device)

# load model
model = spawn_bundled_infer_model(device=device)

# infer
f0 = model.infer(
    audio,
    sr=sr,
    decoder_mode='local_argmax',
    threshold=0.006,
    f0_min=80,
    f0_max=880,
    interp_uv=False,
    output_interp_target_length=f0_target_length,
)

print(f0)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

torchfcpe-0.0.2-py3-none-any.whl (40.2 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page