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| import gradio | |
| import numpy as np | |
| import torch | |
| from hifi_gan_bwe import BandwidthExtender | |
| MAX_LENGTH = 30.0 | |
| model = BandwidthExtender.from_pretrained("hifi-gan-bwe-10-42890e3-vctk-48kHz") | |
| def extend(audio): | |
| fs, x = audio | |
| x = x[:int(MAX_LENGTH * fs)] | |
| x = x.astype(np.float32) / 32767.0 | |
| if len(x.shape) == 1: | |
| x = x[:, np.newaxis] | |
| with torch.no_grad(): | |
| y = np.stack([model(torch.from_numpy(x), fs) for x in x.T]).T | |
| y = (y * 32767.0).astype(np.int16) | |
| fs = int(model.sample_rate) | |
| return fs, y | |
| gradio.Interface( | |
| fn=extend, | |
| examples=[["examples/example.wav"]], | |
| title="HiFi-GAN+", | |
| description=""" | |
| An audio bandwidth extension model from the paper | |
| [Bandwidth Extension is All You Need](https://doi.org/10.1109/ICASSP39728.2021.9413575) | |
| by Su, et al. | |
| For more information, see this | |
| [blog post](https://brentspell.com/2022/hifi-gan-bwe). | |
| """, | |
| thumbnail="https://brentspell.com/favicon-32x32.png", | |
| inputs="audio", | |
| outputs="audio", | |
| ).launch() | |