def process_audio(func_name, audio_io):
"""
Check inputs and return spectrogram images
Check that inputs are in correct format (single-channel,
between 5-20 seconds), and convert to images
Args:
func_name (str): name of calling function (for printing)
audio_io (bytes):
Returns:
array of 299x299 images, each representing up to
5s of the original audio
"""
print(f"runserver.py: {func_name}() checking inputs")
# Just return error if no data was posted
if not audio_io:
return {"error": "No data was given with post?"}
# Make sure we can load the data given to us
print(f"runserver.py: {func_name}() loading samples")
try:
audio = Audio.from_bytesio(
audio_io, sample_rate=22050, resample_type="kaiser_fast"
)
except:
return {"error": "Unable to load audio, multi-chennel input is ignored"}
print(
f"runserver.py: {func_name}() loaded samples at sample_rate {audio.sample_rate}"
)
# Check the duration is between 5 and 20 seconds
duration = audio.duration()
if duration < 5:
return {"error": "Audio is shorter than 5 seconds"}
elif duration > 20:
return {"error": "Audio is longer than 20 seconds"}
# 1. split audio into 5 second chunks
# 2. generate spectrograms
# 3. generate images
audio_splits = birds_detector.split_audio(audio)
spectrograms = [Spectrogram.from_audio(x) for x in audio_splits]
images = [x.to_image(shape=(224, 224)) for x in spectrograms]
print(f"runserver.py: {func_name}(), opening audio as spectrograms")
return {"images": images}
def test_load_pathlib_and_bytesio_are_almost_equal(veryshort_wav_pathlib,
veryshort_wav_bytesio):
s_pathlib = Audio.from_file(veryshort_wav_pathlib)
s_bytesio = Audio.from_bytesio(veryshort_wav_bytesio)
np.testing.assert_allclose(s_pathlib.samples, s_bytesio.samples, atol=1e-7)
def test_load_veryshort_wav_bytesio(veryshort_wav_bytesio):
s = Audio.from_bytesio(veryshort_wav_bytesio, sample_rate=22050)
assert s.samples.shape == (3133, )
