def test_txt(self):
# save activations as txt file
run_save(self.bin, sample_file, tmp_act, args=['--sep', ' '])
act = Activations(tmp_act, sep=' ', fps=100)
self.assertTrue(np.allclose(act, self.activations, atol=1e-5))
# reload from file
run_load(self.bin, tmp_act, tmp_result, args=['--sep', ' '])
result = np.loadtxt(tmp_result)
self.assertTrue(np.allclose(result, self.result, atol=1e-5))
def test_txt(self):
for sf, true_act, true_res in zip([sample_file, sample2_file],
self.activations, self.results):
# save activations as txt file
run_save(self.bin, sf, tmp_act, args=['--sep', ' '])
act = Activations(tmp_act, sep=' ', fps=0)
self.assertTrue(np.allclose(act, true_act, atol=1e-5))
# reload from file
run_load(self.bin, tmp_act, tmp_result, args=['--sep', ' '])
self.assertEqual(load_key(tmp_result), true_res)
def test_binary(self):
# save activations as binary file
run_program([self.bin, '--save', 'single', sample_file, '-o', tmp_act])
act = Activations(tmp_act)
self.assertTrue(np.allclose(act, self.activations, atol=1e-5))
self.assertEqual(act.fps, self.activations.fps)
# reload from file
run_program([self.bin, '--load', 'single', tmp_act, '-o', tmp_result])
result = np.loadtxt(tmp_result)
self.assertTrue(np.allclose(result, self.result, atol=1e-5))
def setUp(self):
self.bin = pj(program_path, 'KeyRecognition')
self.activations = [
Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.key_cnn.npz', 'sample2.key_cnn.npz']
]
self.results = [
load_key(pj(DETECTIONS_PATH, df)) for df in
['sample.key_recognition.txt', 'sample2.key_recognition.txt']
]
def test_binary(self):
# save activations as binary file
run_save(self.bin, sample_file, tmp_act)
act = Activations(tmp_act)
self.assertTrue(np.allclose(act, self.activations, atol=1e-5))
self.assertEqual(act.fps, self.activations.fps)
# reload from file
run_load(self.bin, tmp_act, tmp_result)
result = np.loadtxt(tmp_result)
self.assertTrue(np.allclose(result, self.result, atol=1e-5))
def setUp(self):
self.bin = pj(program_path, "DCChordRecognition")
self.activations = [
Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.deep_chroma.npz', 'sample2.deep_chroma.npz']
]
self.results = [
load_chords(pj(DETECTIONS_PATH, df))
for df in ['sample.dc_chord_recognition.txt',
'sample2.dc_chord_recognition.txt']
]
def test_binary(self):
for sf, true_act, true_res in zip([sample_file, sample2_file],
self.activations, self.results):
# save activations as binary file
run_save(self.bin, sf, tmp_act)
act = Activations(tmp_act)
self.assertTrue(np.allclose(act, true_act, atol=1e-5))
self.assertEqual(act.fps, true_act.fps)
# reload from file
run_load(self.bin, tmp_act, tmp_result)
self.assertEqual(load_key(tmp_result), true_res)
def test_binary(self):
for sf, true_act, true_res in zip([sample_file, sample2_file],
self.activations, self.results):
# save activations as binary file
run_program([self.bin, '--save', 'single', sf, '-o', tmp_act])
act = Activations(tmp_act)
self.assertTrue(np.allclose(act, true_act, atol=1e-5))
self.assertEqual(act.fps, true_act.fps)
# reload from file
run_program(
[self.bin, '--load', 'single', tmp_act, '-o', tmp_result])
self._check_results(load_chords(tmp_result), true_res)
def test_txt(self):
# save activations as txt file
run_program([
self.bin, '--save', '--sep', ' ', 'single', sample_file, '-o',
tmp_act
])
act = Activations(tmp_act, sep=' ', fps=100)
self.assertTrue(np.allclose(act, self.activations, atol=1e-5))
# reload from file
run_program([
self.bin, '--load', '--sep', ' ', 'single', tmp_act, '-o',
tmp_result
])
result = np.loadtxt(tmp_result)
self.assertTrue(np.allclose(result, self.result, atol=1e-5))
def test_txt(self):
for sf, true_act, true_res in zip([sample_file, sample2_file],
self.activations, self.results):
# save activations as txt file
run_program([
self.bin, '--save', '--sep', ' ', 'single', sf, '-o', tmp_act
])
act = Activations(tmp_act, sep=' ', fps=100)
self.assertTrue(np.allclose(act, true_act, atol=1e-5))
# reload from file
run_program([
self.bin, '--load', '--sep', ' ', 'single', tmp_act, '-o',
tmp_result
])
self._check_results(load_chords(tmp_result), true_res)
def setUp(self):
self.bin = pj(program_path, "SuperFluxNN")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.super_flux_nn.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.super_flux_nn.txt"))
def setUp(self):
self.bin = pj(program_path, "SpectralOnsetDetection")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.spectral_flux.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.spectral_flux.txt"))
def setUp(self):
self.bin = pj(program_path, "PianoTranscriptor")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "stereo_sample.notes_brnn.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "stereo_sample.piano_transcriptor.txt"))
def setUp(self):
self.bin = pj(program_path, "BeatDetector")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.beats_blstm.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.beat_detector.txt"))
def setUp(self):
self.bin = pj(program_path, "OnsetDetectorLL")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.onsets_rnn.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.onset_detector_ll.txt"))
def setUp(self):
self.bin = pj(program_path, "MMBeatTracker")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.beats_blstm_mm.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.mm_beat_tracker.txt"))
def setUp(self):
self.bin = pj(program_path, "LogFiltSpecFlux")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.log_filt_spec_flux.npz"))
self.result = np.loadtxt(
pj(DETECTIONS_PATH, "sample.log_filt_spec_flux.txt"))
This file contains tests for the madmom.features.key module.
"""
from __future__ import absolute_import, division, print_function
import unittest
from os.path import join as pj
from madmom.features import Activations
from madmom.features.key import *
from . import AUDIO_PATH, ACTIVATIONS_PATH
sample_file = pj(AUDIO_PATH, 'sample.wav')
sample2_file = pj(AUDIO_PATH, 'sample2.wav')
sample_key_act = Activations(pj(ACTIVATIONS_PATH, 'sample.key_cnn.npz'))
sample2_key_act = Activations(pj(ACTIVATIONS_PATH, 'sample2.key_cnn.npz'))
class TestHelperFunctions(unittest.TestCase):
def test_key_prediction_to_label_function(self):
self.assertEqual(key_prediction_to_label(sample_key_act), 'Ab major')
self.assertEqual(
key_prediction_to_label(sample_key_act[0]), 'Ab major')
self.assertEqual(
key_prediction_to_label(np.roll(sample_key_act[0], 1)), 'A minor')
self.assertEqual(
key_prediction_to_label(np.roll(sample_key_act[0], -3)), 'F major')
self.assertEqual(key_prediction_to_label(sample2_key_act), 'A minor')
def setUp(self):
self.bin = pj(program_path, "ComplexFlux")
self.activations = Activations(
pj(ACTIVATIONS_PATH, "sample.complex_flux.npz"))
self.result = np.loadtxt(pj(DETECTIONS_PATH,
"sample.complex_flux.txt"))
"""
from __future__ import absolute_import, division, print_function
import numpy as np
import unittest
from . import AUDIO_PATH, ACTIVATIONS_PATH
from madmom.audio.chroma import DeepChromaProcessor, CLPChroma
from madmom.features import Activations
from os.path import join as pj
from madmom.audio.signal import Signal
sample_files = [pj(AUDIO_PATH, sf) for sf in ['sample.wav', 'sample2.wav']]
sample_acts = [
Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.deep_chroma.npz', 'sample2.deep_chroma.npz']
]
sample_file = pj(AUDIO_PATH, 'sample.wav')
sample_file_22050 = pj(AUDIO_PATH, 'sample_22050.wav')
sample_act_deep_chroma = Activations(
pj(ACTIVATIONS_PATH, 'sample.deep_chroma.npz'))
class TestDeepChromaProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = DeepChromaProcessor()
def test_process(self):
for f, a in zip(sample_files, sample_acts):
self.assertTrue(np.allclose(self.processor(f), a))
"""
This file contains tests for the madmom.features.notes module.
"""
from __future__ import absolute_import, division, print_function
import unittest
from os.path import join as pj
from . import AUDIO_PATH, ACTIVATIONS_PATH, ANNOTATIONS_PATH
from madmom.features import Activations
from madmom.features.notes import *
sample_file = pj(AUDIO_PATH, "stereo_sample.wav")
sample_act = Activations(pj(ACTIVATIONS_PATH, "stereo_sample.notes_brnn.npz"))
NOTES = np.array([[0.147, 72, 3.323, 63], [1.567, 41, 0.223, 29],
[2.526, 77, 0.93, 72], [2.549, 60, 0.211, 28],
[2.563, 65, 0.202, 34], [2.577, 56, 0.234, 31],
[3.369, 75, 0.78, 64], [3.449, 43, 0.272, 35]])
class TestLoadNotesFunction(unittest.TestCase):
def test_values(self):
result = load_notes(pj(ANNOTATIONS_PATH, 'stereo_sample.notes'))
self.assertTrue(np.allclose(result, NOTES))
class TestExpandNotesFunction(unittest.TestCase):
def test_values(self):
"""
from __future__ import absolute_import, division, print_function
import unittest
from os.path import join as pj
from madmom.features import Activations
from madmom.features.chords import *
from madmom.io import load_chords
from . import ACTIVATIONS_PATH, AUDIO_PATH, DETECTIONS_PATH
sample_files = [pj(AUDIO_PATH, sf) for sf in ['sample.wav', 'sample2.wav']]
sample_cnn_acts = [Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.cnn_chord_features.npz',
'sample2.cnn_chord_features.npz']]
sample_cnn_labels = [load_chords(pj(DETECTIONS_PATH, df))
for df in ['sample.cnn_chord_recognition.txt',
'sample2.cnn_chord_recognition.txt']]
sample_deep_chroma_acts = [Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.deep_chroma.npz',
'sample2.deep_chroma.npz']]
sample_deep_chroma_labels = [load_chords(pj(DETECTIONS_PATH, df))
for df in ['sample.dc_chord_recognition.txt',
'sample2.dc_chord_recognition.txt']]
"""
from __future__ import absolute_import, division, print_function
import unittest
from os.path import join as pj
from madmom.features import Activations
from madmom.features.chords import *
from . import AUDIO_PATH, ACTIVATIONS_PATH, DETECTIONS_PATH
sample_files = [pj(AUDIO_PATH, sf) for sf in ['sample.wav', 'sample2.wav']]
sample_cnn_acts = [
Activations(pj(ACTIVATIONS_PATH, af)) for af in
['sample.cnn_chord_features.npz', 'sample2.cnn_chord_features.npz']
]
sample_cnn_labels = [
load_chords(pj(DETECTIONS_PATH, df)) for df in
['sample.cnn_chord_recognition.txt', 'sample2.cnn_chord_recognition.txt']
]
sample_deep_chroma_acts = [
Activations(pj(ACTIVATIONS_PATH, af))
for af in ['sample.deep_chroma.npz', 'sample2.deep_chroma.npz']
]
sample_deep_chroma_labels = [
load_chords(pj(DETECTIONS_PATH, df)) for df in
from os.path import join as pj
from madmom.ml.hmm import HiddenMarkovModel
from madmom.audio.chroma import CLPChroma
from madmom.features import Activations
from madmom.features.downbeats import *
from madmom.models import PATTERNS_BALLROOM
from . import ACTIVATIONS_PATH, ANNOTATIONS_PATH, AUDIO_PATH, DETECTIONS_PATH
from .test_utils import DETECTION_FILES
sample_file = pj(AUDIO_PATH, "sample.wav")
sample_beats = np.loadtxt(pj(ANNOTATIONS_PATH, "sample.beats"))
sample_det_file = pj(DETECTIONS_PATH, 'sample.dbn_beat_tracker.txt')
sample_beat_det = np.loadtxt(sample_det_file)
sample_bar_act = Activations(pj(ACTIVATIONS_PATH, "sample.bar_tracker.npz"))
sample_downbeat_act = Activations(
pj(ACTIVATIONS_PATH, "sample.downbeats_blstm.npz"))
sample_pattern_features = Activations(
pj(ACTIVATIONS_PATH, "sample.gmm_pattern_tracker.npz"))
class TestRNNDownBeatProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = RNNDownBeatProcessor()
def test_process(self):
downbeat_act = self.processor(sample_file)
self.assertTrue(
np.allclose(downbeat_act, sample_downbeat_act, atol=1e-5))
from madmom.audio.signal import SignalProcessor, FramedSignalProcessor
from madmom.audio.filters import LogarithmicFilterbank
from madmom.audio.stft import ShortTimeFourierTransformProcessor
from madmom.audio.spectrogram import (Spectrogram, SpectrogramProcessor,
FilteredSpectrogramProcessor,
LogarithmicFilteredSpectrogram,
LogarithmicSpectrogramProcessor)
from madmom.features import Activations
from madmom.features.onsets import *
sample_file = pj(AUDIO_PATH, 'sample.wav')
sample_spec = Spectrogram(sample_file, circular_shift=True)
sample_log_filt_spec = LogarithmicFilteredSpectrogram(
sample_spec, num_bands=24, mul=1, add=1)
sample_cnn_act = Activations(pj(ACTIVATIONS_PATH, 'sample.onsets_cnn.npz'))
sample_rnn_act = Activations(pj(ACTIVATIONS_PATH, 'sample.onsets_rnn.npz'))
sample_brnn_act = Activations(pj(ACTIVATIONS_PATH, 'sample.onsets_brnn.npz'))
sample_superflux_act = Activations(pj(ACTIVATIONS_PATH,
'sample.super_flux.npz'))
class TestHighFrequencyContentFunction(unittest.TestCase):
def test_values(self):
odf = high_frequency_content(sample_log_filt_spec)
self.assertTrue(np.allclose(odf[:6], [8.97001563, 9.36399107,
8.64144536, 8.34977449,
8.21097918, 8.40412515]))
