def run(self):
with self.in_subtitles().open('r') as fp:
transcription = pyannote.core.json.load(fp)
annotation = Annotation()
label = 0
for start, end, edge in transcription.ordered_edges_iter(data=True):
if 'subtitle' not in edge:
continue
segment = Segment(start, end)
annotation[segment] = label
label += 1
annotation = annotation.anonymize_labels(generator='string')
with self.out_put().open('w') as fp:
pyannote.core.json.dump(annotation, fp)
def run(self):
# wav file duration
wav = self.in_wav().path
with contextlib.closing(wave.open(wav, 'r')) as f:
frames = f.getnframes()
rate = f.getframerate()
duration = frames / rate
extent = Segment(0., duration)
with self.in_speaker().open('r') as fp:
speaker = pyannote.core.json.load(fp)
timeline = Timeline()
for segment, _ in speaker.itertracks():
timeline.add(segment)
# fill gaps
for gap in timeline.gaps(extent):
if gap.duration < self.fill_gaps:
timeline.add(gap)
timeline = timeline.coverage()
# dump as annotation...
if self.to_annotation:
annotation = Annotation()
for s, segment in enumerate(timeline):
annotation[segment] = s
annotation = annotation.anonymize_labels(generator='string')
with self.out_put().open('w') as fp:
pyannote.core.json.dump(annotation, fp)
# ... or as timeline
else:
with self.out_put().open('w') as fp:
pyannote.core.json.dump(timeline, fp)
path = SHOTS.format(repository=REPOSITORY, uri=uri)
names = ['corpus_id', 'video_id', 'shot_id', 'start', 'end']
dtype = {'shot_id': str}
shots = pd.read_table(path, delim_whitespace=True, header=None, names=names, dtype=dtype)
pyannote_shots = Annotation(uri=uri)
for _, (_, _, shot_id, start, end) in shots.iterrows():
pyannote_shots[Segment(start, end), shot_id] = shot_id
# load speaker diarization as pyannote.Annotation
path = SPEAKERS.format(repository=REPOSITORY, uri=uri)
names = ['corpus_id', 'video_id', 'start', 'end', 'label', 'gender']
speakers = pd.read_table(path, delim_whitespace=True, header=None, names=names)
pyannote_speakers = Annotation(uri=uri)
for _, (_, _, start, end, label, _) in speakers.iterrows():
pyannote_speakers[Segment(start, end)] = label
pyannote_speakers = pyannote_speakers.anonymize_labels(generator='int')
# load names as pyannote.Annotation
path = OCR.format(repository=REPOSITORY, uri=uri)
names = ['start', 'end', 'start_frame', 'end_frame', 'name', 'confidence']
pyannote_ocr = Annotation(uri=uri)
try:
ocr = pd.read_table(path, delim_whitespace=True, header=None, names=names)
for _, (start, end, _, _, name, _) in ocr.iterrows():
pyannote_ocr[Segment(start, end)] = name
except pandas.parser.CParserError as e:
pass
# name each speaker by most co-occurring OCR name
if not pyannote_ocr:
named_speakers = Annotation(uri=uri)
