77 lines
2.2 KiB
Plaintext
77 lines
2.2 KiB
Plaintext
import wave
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import struct
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import numpy as np
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import os
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def data_to_audio(file_path, output_wav, freq_0=1000, freq_1=2000, sample_rate=44100, duration=0.05):
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"""
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Convert file data to audio (simple FSK-style encoding)
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"""
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with open(file_path, 'rb') as f:
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data = f.read()
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# Prepare WAV file
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wav_file = wave.open(output_wav, 'w')
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wav_file.setnchannels(1)
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wav_file.setsampwidth(2)
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wav_file.setframerate(sample_rate)
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def write_tone(freq):
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samples = int(sample_rate * duration)
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for i in range(samples):
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value = int(32767.0 * 0.5 *
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struct.pack('<h', int(32767.0 * 0.5 * (2 ** 0.5) *
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(i / sample_rate * freq * 2.0 * 3.141592653589793))))
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wav_file.writeframesraw(value)
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# Encode data
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for byte in data:
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bits = f'{byte:08b}'
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for bit in bits:
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freq = freq_1 if bit == '1' else freq_0
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write_tone(freq)
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# Close file
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wav_file.close()
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print(f"Audio file saved as: {output_wav}")
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def audio_to_data(input_wav, output_file, freq_0=1000, freq_1=2000, sample_rate=44100, duration=0.05):
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"""
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Decode audio back to binary data
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"""
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wav_file = wave.open(input_wav, 'r')
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frames = wav_file.readframes(-1)
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samples = np.frombuffer(frames, dtype=np.int16)
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samples_per_bit = int(sample_rate * duration)
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bits = ''
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for i in range(0, len(samples), samples_per_bit):
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chunk = samples[i:i + samples_per_bit]
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freq = np.fft.fftfreq(len(chunk), 1/sample_rate)
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spectrum = np.abs(np.fft.fft(chunk))
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peak_freq = freq[np.argmax(spectrum)]
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if abs(peak_freq - freq_1) < abs(peak_freq - freq_0):
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bits += '1'
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else:
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bits += '0'
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# Convert bits to bytes
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byte_data = bytearray([int(bits[i:i+8], 2) for i in range(0, len(bits), 8)])
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# Save to file
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with open(output_file, 'wb') as f:
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f.write(byte_data)
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print(f"Decoded file saved as: {output_file}")
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# Example usage
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input_file = 'example.txt' # Replace with your file
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output_wav = 'output.wav'
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recovered_file = 'recovered.txt'
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data_to_audio(input_file, output_wav)
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audio_to_data(output_wav, recovered_file)
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