# This work is licensed under the MIT license. # Copyright (c) 2013-2023 OpenMV LLC. All rights reserved. # https://github.com/openmv/openmv/blob/master/LICENSE # import image import audio from ulab import numpy as np from ulab import utils CHANNELS = 1 SIZE = 256 // (2 * CHANNELS) raw_buf = None fb = image.Image(SIZE + 50, SIZE, image.RGB565, copy_to_fb=True) audio.init(channels=CHANNELS, frequency=16000, gain_db=24, highpass=0.9883) def audio_callback(buf): # NOTE: do Not call any function that allocates memory. global raw_buf if raw_buf is None: raw_buf = buf # Start audio streaming audio.start_streaming(audio_callback) def draw_fft(img, fft_buf): fft_buf = (fft_buf / max(fft_buf)) * SIZE fft_buf = np.log10(fft_buf + 1) * 20 color = (0xFF, 0x0F, 0x00) for i in range(0, SIZE): img.draw_line(i, SIZE, i, SIZE - int(fft_buf[i]), color, 1) def draw_audio_bar(img, level, offset): blk_size = SIZE // 10 color = (0xFF, 0x00, 0xF0) blk_space = blk_size // 4 for i in range(0, int(round(level / 10))): fb.draw_rectangle( SIZE + offset, SIZE - ((i + 1) * blk_size) + blk_space, 20, blk_size - blk_space, color, 1, True, ) while True: if raw_buf is not None: pcm_buf = np.frombuffer(raw_buf, dtype=np.int16) raw_buf = None if CHANNELS == 1: fft_buf = utils.spectrogram(pcm_buf) l_lvl = int((np.mean(abs(pcm_buf[1::2])) / 32768) * 100) else: fft_buf = utils.spectrogram(pcm_buf[0::2]) l_lvl = int((np.mean(abs(pcm_buf[1::2])) / 32768) * 100) r_lvl = int((np.mean(abs(pcm_buf[0::2])) / 32768) * 100) fb.clear() draw_fft(fb, fft_buf) draw_audio_bar(fb, l_lvl, 0) if CHANNELS == 2: draw_audio_bar(fb, r_lvl, 25) fb.flush() # Stop streaming audio.stop_streaming()