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https://github.com/openmv/openmv.git
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75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
# This work is licensed under the MIT license.
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# Copyright (c) 2013-2023 OpenMV LLC. All rights reserved.
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# https://github.com/openmv/openmv/blob/master/LICENSE
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#
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import image
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import audio
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from ulab import numpy as np
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from ulab import utils
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CHANNELS = 1
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SIZE = 256 // (2 * CHANNELS)
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raw_buf = None
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fb = image.Image(SIZE + 50, SIZE, image.RGB565, copy_to_fb=True)
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audio.init(channels=CHANNELS, frequency=16000, gain_db=80)
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def audio_callback(buf):
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# NOTE: do Not call any function that allocates memory.
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global raw_buf
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if raw_buf is None:
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raw_buf = buf
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# Start audio streaming
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audio.start_streaming(audio_callback)
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def draw_fft(img, fft_buf):
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fft_buf = (fft_buf / max(fft_buf)) * SIZE
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fft_buf = np.log10(fft_buf + 1) * 20
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color = (0xFF, 0x0F, 0x00)
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for i in range(0, SIZE):
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img.draw_line(i, SIZE, i, SIZE - int(fft_buf[i]), color, 1)
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def draw_audio_bar(img, level, offset):
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blk_size = SIZE // 10
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color = (0xFF, 0x00, 0xF0)
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blk_space = blk_size // 4
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for i in range(0, int(round(level / 10))):
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fb.draw_rectangle(
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SIZE + offset,
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SIZE - ((i + 1) * blk_size) + blk_space,
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20,
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blk_size - blk_space,
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color,
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1,
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True,
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)
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while True:
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if raw_buf is not None:
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pcm_buf = np.frombuffer(raw_buf, dtype=np.int16)
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raw_buf = None
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if CHANNELS == 1:
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fft_buf = utils.spectrogram(pcm_buf)
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l_lvl = int((np.mean(abs(pcm_buf[1::2])) / 32768) * 100)
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else:
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fft_buf = utils.spectrogram(pcm_buf[0::2])
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l_lvl = int((np.mean(abs(pcm_buf[1::2])) / 32768) * 100)
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r_lvl = int((np.mean(abs(pcm_buf[0::2])) / 32768) * 100)
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fb.clear()
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draw_fft(fb, fft_buf)
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draw_audio_bar(fb, l_lvl, 0)
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if CHANNELS == 2:
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draw_audio_bar(fb, r_lvl, 25)
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fb.flush()
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# Stop streaming
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audio.stop_streaming()
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