def tracktorDeserialize(path, titles=None):
"""
get a track from the xml format from tracktor (1?)
"""
tree = ET.parse(path)
root = tree.getroot()
tracks = {}
for entry in root.find("COLLECTION").iter("ENTRY"):
track = Track()
track.name = entry.attrib["TITLE"]
track.path = entry.find(
"LOCATION").attrib["FILE"][:-4] #Removing .mp3
cues = [
cue for cue in entry.iter("CUE_V2")
if cue.attrib["NAME"] != "AutoGrid"
]
track.features["Cues"] = Signal(
[cue.attrib["NAME"][:7] for cue in cues],
times=[float(cue.attrib["START"]) / 1000 for cue in cues],
sparse=True)
tracks[track.path] = track
if titles:
return [tracks[t] if t in tracks else None for t in titles]
return tracks.values()
# bla = TraktorSerializer.tracktorDeserialize(
# "/home/mickael/Documents/programming/dj-tracks-switch-points/evaluation/mixed in key/collection.nml")
# print(bla)
def deserializeTrack(path, agreement=0.51, distanceAgreement=0.5, minimalAnnotator=0, minimalConfidence=0):
"""instantiate a Track from the jams encoding. https://github.com/marl/jams/
Args:
----
path (list[str]): path to the .JAMS file
agreement (float, optional): minimal ratio of annotators agreeing to keep the point. Defaults to 0.51.
distanceAgreement (float, optional): distance between annotations to cluster them to the same point. Defaults to 0.5.
minimalAnnotator (int, optional): minimal number of annotators to keep the annotation. Defaults to 0.
minimalConfidence (int, optional): minimal confidence to keep the annotation. Defaults to 0.
Returns:
-------
Track: a track with annotations in it's features
"""
reference = None
track = Track()
with open(path) as file:
reference = json.load(file)
# meta
track.path = path
track.features["duration"] = reference["file_metadata"]["duration"]
track.name = reference["file_metadata"]["title"]
switchsIn = []
switchsOut = []
for annotation in reference["annotations"]:
# meta
annotator = annotation["annotation_metadata"]["annotator"]["name"]
# if annotator == "Marco":
# continue
# old format segment_open
if annotation["namespace"] == "segment_open":
segments = annotation["data"]
track.features["boundaries"] = Signal(1, times=[segment["time"] for segment in segments], sparse=True)
track.features["labels"] = [segment["value"] for segment in segments]
# tempo
elif annotation["namespace"] == "tempo":
track.features["tempo"] = annotation["data"][0]["value"]
# Current format with confidence, segment, and multiple annotators
elif annotation["namespace"] == "cue_point":
segments = annotation["data"]
switchsIn.append([segment for segment in segments if segment["value"]["label"] == "IN"])
switchsOut.append([segment for segment in segments if segment["value"]["label"] == "OUT"])
track.features["switchIn-" + annotator] = Signal(
1, times=[segment["time"] for segment in segments if segment["value"]["label"] == "IN"], sparse=True)
track.features["switchIn"] = JamsSerializer.aggregateAnnotations(switchsIn,
agreementThreshold=agreement,
distanceAgreement=distanceAgreement,
minimalAnnotator=minimalAnnotator)
# track.features["switchOut"] = JamsSerializer.aggregateAnnotations(switchsOut,
# agreementThreshold=agreement,
# distanceAgreement=distanceAgreement,
# minimalAnnotator=minimalAnnotator)
return track