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https://github.com/KrisKennaway/ii-vision.git
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99c7f6db34
Use these in the audio encoder to generate random video stores to validate.
58 lines
1.6 KiB
Python
58 lines
1.6 KiB
Python
import random
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import numpy as np
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import audioread
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import librosa
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import opcodes
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import video
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class Audio:
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def encode_audio(self, audio):
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for a in audio:
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a = max(-30, min(a * 2, 32)) + 34
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page = random.randint(32, 49)
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content = random.randint(0,255)
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offsets = [random.randint(0, 255) for _ in range(4)]
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yield opcodes.TICK_OPCODES[(a, page)](content, offsets)
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def main():
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filename = "Computer Chronicles - 06x05 - The Apple II.mp4"
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s = video.Video(frame_rate=None)
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au = Audio()
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with audioread.audio_open(filename) as f:
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with open("out.bin", "wb") as out:
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for buf in f.read_data(128 * 1024):
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print(f.channels, f.samplerate, f.duration)
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data = np.frombuffer(buf, dtype='int16').astype(
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'float32').reshape((f.channels, -1), order='F')
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a = librosa.core.to_mono(data)
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a = librosa.resample(a, f.samplerate, 14000).flatten()
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# Normalize to 95%ile
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# norm = max(
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# abs(np.percentile(a, 5, axis=0)),
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# abs(np.percentile(a, 95, axis=0))
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# )
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# print(min(a),max(a))
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# print(norm)
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# XXX how to estimate normalization without reading whole file?
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norm = 12000
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a /= norm # librosa.util.normalize(a)
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a = (a * 32).astype(np.int)
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out.write(bytes(s.emit_stream(au.encode_audio(a))))
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out.write(bytes(s.done()))
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if __name__ == "__main__":
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main()
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