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from denoiser.enhance import *
def enhance_new(args, in_file, out_file, model=None, local_out_dir=None):
# Load model
if not model:
model = pretrained.get_model(args).to(args.device)
model.eval()
dset = Audioset([(in_file, None)], with_path=True,
sample_rate=model.sample_rate, channels=model.chin, convert=True)
if dset is None:
return
loader = distrib.loader(dset, batch_size=1)
distrib.barrier()
with ProcessPoolExecutor(1) as pool:
iterator = LogProgress(logger, loader, name="Generate enhanced files")
pendings = []
for data in iterator:
# Get batch data
noisy_signals, filenames = data
noisy_signals = noisy_signals.to(args.device)
# Forward
estimate = get_estimate(model, noisy_signals, args)
for estimate, noisy, filename in zip(estimate, noisy_signals, filenames):
write(estimate, out_file, sr=model.sample_rate)
if pendings:
print('Waiting for pending jobs...')
for pending in LogProgress(logger, pendings, updates=5, name="Generate enhanced files"):
pending.result()
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