def test_read_chord_annotations(self):
chords = load_chords(pj(DETECTIONS_PATH,
'sample2.dc_chord_recognition.txt'))
_compare_labels(self, chords,
np.array([(0.0, 1.6, 'F:maj'),
(1.6, 2.5, 'A:maj'),
(2.5, 4.1, 'D:maj')],
dtype=SEGMENT_DTYPE))
chords = load_chords(pj(DETECTIONS_PATH,
'sample.dc_chord_recognition.txt'))
_compare_labels(self, chords,
np.array([(0.0, 2.9, 'G#:maj')],
dtype=SEGMENT_DTYPE))
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=100)
self.assertTrue(np.allclose(act, true_act, atol=1e-5))
# reload from file
run_load(self.bin, tmp_act, tmp_result, args=['--sep', ' '])
self._check_results(load_chords(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_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._check_results(load_chords(tmp_result), true_res)
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_run(self):
for sf, true_res in zip([sample_file, sample2_file], self.results):
run_single(self.bin, sf, tmp_result)
self._check_results(load_chords(tmp_result), true_res)
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']]
def _compare_labels(test_case, labels, reference_labels):
test_case.assertTrue(
np.allclose(labels['start'], reference_labels['start']))
