def test_multiannotator_events():
event_data1 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 0.4]]),
"seconds",
["event A", "event B"],
"open",
np.array([1.0, 1.0]),
)
event_data2 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 0.4]]),
"seconds",
["", "a great label"],
"open",
np.array([0.0, 1.0]),
)
event_data3 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 20.0]]), # invalid because > duration
"seconds",
["", "a great label"],
"open",
np.array([0.0, 1.0]),
)
multiannotator_data = annotations.MultiAnnotator(
["01", "02", "03"], [event_data1, event_data2, event_data3]
)
jam = jams_utils.jams_converter(
events=multiannotator_data, metadata={"duration": 10.0}
)
assert jam.validate()
def load_annotation(fhandle: TextIO) -> annotations.MultiAnnotator:
"""
Load an annotation file.
Args:
fhandle (str or file-like): path or file-like object pointing to an annotation file
Returns:
* annotations.MultiAnnotator - sound events with start time, end time, label and confidence
"""
df = pd.read_csv(fhandle)
annotators = []
annotations_ = []
for id, dfa in df.groupby("annotator"):
intervals = dfa[["onset", "offset"]].values
label = dfa["event_label"].tolist()
events = annotations.Events(
intervals=intervals,
intervals_unit="seconds",
labels=label,
labels_unit="open",
confidence=np.ones((len(label),)),
)
annotators.append(f"{id:02d}")
annotations_.append(events)
return annotations.MultiAnnotator(annotators=annotators, annotations=annotations_)
def load_events(fhandle: TextIO) -> annotations.Events:
"""Load an TUT Sound events 2017 annotation file
Args:
fhandle (str or file-like): File-like object or path to the sound
events annotation file
Returns:
Events: sound events annotation data
"""
times = []
labels = []
confidence = []
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
offset = (
0 if len(line) == 3 else 2
) # ann files in dev and eval have different format
times.append([float(line[offset]), float(line[offset + 1])])
labels.append(line[offset + 2])
confidence.append(1.0)
events_data = annotations.Events(
np.array(times), "seconds", labels, "open", np.array(confidence)
)
return events_data
def test_events():
event_data1 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 0.4]]),
"seconds",
["event A", "event B"],
"open",
np.array([1.0, 1.0]),
)
event_data2 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 0.4]]),
"seconds",
["", "a great label"],
"open",
np.array([0.0, 1.0]),
)
event_data3 = annotations.Events(
np.array([[0.2, 0.3], [0.3, 20.0]]), # invalid because > duration
"seconds",
["", "a great label"],
"open",
np.array([0.0, 1.0]),
)
event_data4 = ("jazz", "wrong format")
event_data5 = ["wrong format too"]
event_data6 = [("wrong", "description")]
jam1 = jams_utils.jams_converter(events=event_data1, metadata={"duration": 10.0})
assert jam1.validate()
jam2 = jams_utils.jams_converter(events=event_data2, metadata={"duration": 10.0})
assert jam2.validate()
jam3 = jams_utils.jams_converter(events=event_data3, metadata={"duration": 10.0})
assert jam3.validate()
with pytest.raises(TypeError):
jams_utils.jams_converter(events=event_data4)
with pytest.raises(TypeError):
jams_utils.jams_converter(events=event_data5)
with pytest.raises(TypeError):
jams_utils.jams_converter(events=event_data6)
def test_repr():
class TestAnnotation(annotations.Annotation):
def __init__(self):
self.a = ["a", "b", "c"]
self.b = np.array([[1, 2], [1, 4]])
self._c = "hidden"
test_track = TestAnnotation()
assert test_track.__repr__() == """TestAnnotation(a, b)"""
event_data = annotations.Events(np.array([[1.0, 2.0], [3.0, 4.0]]),
"seconds", ["Siren", "Dog"], "open")
assert (event_data.__repr__(
) == "Events(confidence, intervals, intervals_unit, labels, labels_unit)")
def load_events(fhandle: TextIO) -> annotations.Events:
"""Load an URBAN-SED sound events annotation file
Args:
fhandle (str or file-like): File-like object or path to the sound events annotation file
Raises:
IOError: if txt_path doesn't exist
Returns:
Events: sound events annotation data
"""
times = []
labels = []
confidence = []
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
times.append([float(line[0]), float(line[1])])
labels.append(line[2])
confidence.append(1.0)
events_data = annotations.Events(np.array(times), "seconds", labels,
"open", np.array(confidence))
return events_data
def test_events():
# test good data
intervals = np.array([[1.0, 2.0], [1.5, 3.0], [2.0, 3.0]])
labels = ["Siren", "Laughter", "Engine"]
confidence = np.array([1.0, 0.0, 1.0])
events = annotations.Events(intervals, "seconds", labels, "open",
confidence)
assert np.allclose(events.intervals, intervals)
assert events.labels == labels
assert np.allclose(events.confidence, confidence)
# test bad data
bad_intervals = np.array([[1.0, 0.0], [1.5, 3.0], [2.0, 3.0]])
pytest.raises(
ValueError,
annotations.Events,
bad_intervals,
"seconds",
labels,
"open",
confidence,
)
bad_labels = ["Siren", "Laughter", 5]
pytest.raises(
TypeError,
annotations.Events,
intervals,
"seconds",
bad_labels,
"open",
confidence,
)
bad_confidence = np.array([1, 0.5, -0.2])
pytest.raises(
ValueError,
annotations.Events,
intervals,
"seconds",
labels,
"open",
bad_confidence,
)
# test units
with pytest.raises(ValueError):
annotations.Events(intervals, "seconds", labels, "bad_unit",
confidence)
with pytest.raises(ValueError):
annotations.Events(intervals, "bad_unit", labels, "open", confidence)
with pytest.raises(TypeError):
annotations.Events(intervals, labels, confidence)
with pytest.raises(TypeError):
annotations.Events(intervals, labels, "open", confidence)
with pytest.raises(TypeError):
annotations.Events(intervals, "seconds", labels, confidence)