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import numpy
import numpy as np
from scipy.signal import firwin, lfilter, decimate
import soundfile
def load_pdm_file(filename):
with open(filename, 'rb') as f:
byte_data = np.frombuffer(f.read(), dtype=np.uint8)
bit_data = np.unpackbits(byte_data)
# Convert to +1 (for 1s) and -1 (for 0s)
#pdm_signal = 2 * bit_data - 1
pdm_signal = bit_data
return pdm_signal
def pdm_to_pcm(pdm_signal, decimation_factor=64):
# Design a low-pass filter
fir_filter = firwin(numtaps=101, cutoff=0.5/decimation_factor)
# Filter the PDM signal
filtered = lfilter(fir_filter, [1.0], pdm_signal)
# Decimate (downsample)
pcm_signal = filtered[::decimation_factor]
return pcm_signal
def parse():
import argparse
parser = argparse.ArgumentParser(description='Process an input file and write to an output file.')
parser.add_argument('-i', '--input', type=str, required=True, help='Path to the input file')
parser.add_argument('-o', '--output', type=str, required=True, help='Path to the output file')
parser.add_argument('--samplerate', type=int, default=16000)
parser.add_argument('--oversample', type=int, default=64)
args = parser.parse_args()
return args
def main():
args = parse()
pdm_path = args.input
out_path = args.output
pdm_data = load_pdm_file(pdm_path)
# Convert to PCM
oversample = args.oversample
samplerate = args.samplerate
pcm_data = pdm_to_pcm(pdm_data, decimation_factor=oversample)
# Normalize and save to WAV
pcm_data = np.expand_dims(pcm_data, axis=1)
#print(pcm_data.shape)
pcm_data -= numpy.mean(pcm_data) # remove DC offset
print(numpy.min(pcm_data), numpy.max(pcm_data), numpy.mean(pcm_data), pcm_data.dtype)
soundfile.write(out_path, pcm_data, samplerate)
print('Wrote', out_path)
if __name__ == '__main__':
main()
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