def test_start_seconds(start_seconds):
    parser_zero = GenericSubtitleParser(start_seconds=0)
    parser_zero.fit(BytesIO(fake_srt))
    parser = GenericSubtitleParser(start_seconds=start_seconds)
    parser.fit(BytesIO(fake_srt))
    expected = [sub for sub in parser_zero.subs_ if sub.start >= timedelta(seconds=start_seconds)]
    assert all(esub == psub for esub, psub in zip(expected, parser.subs_))
Beispiel #2
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def timestamps_roughly_match(f1, f2):
    parser = GenericSubtitleParser()
    extractor = SubtitleSpeechTransformer(sample_rate=ffsubsync.DEFAULT_FRAME_RATE)
    pipe = make_pipeline(parser, extractor)
    f1_bitstring = pipe.fit_transform(f1).astype(bool)
    f2_bitstring = pipe.fit_transform(f2).astype(bool)
    return np.alltrue(f1_bitstring == f2_bitstring)
def test_same_encoding(encoding):
    parser = GenericSubtitleParser(encoding=encoding)
    offseter = SubtitleShifter(1)
    pipe = make_pipeline(parser, offseter)
    pipe.fit(BytesIO(fake_srt))
    assert parser.subs_._encoding == encoding
    assert offseter.subs_._encoding == parser.subs_._encoding
    assert offseter.subs_.set_encoding('same')._encoding == encoding
    assert offseter.subs_.set_encoding('utf-8')._encoding == 'utf-8'
def test_offset(offset):
    parser = GenericSubtitleParser()
    offseter = SubtitleShifter(offset)
    pipe = make_pipeline(parser, offseter)
    pipe.fit(BytesIO(fake_srt))
    for sub_orig, sub_offset in zip(parser.subs_, offseter.subs_):
        assert abs(sub_offset.start.total_seconds() -
                   sub_orig.start.total_seconds() - offset) < 1e-6
        assert abs(sub_offset.end.total_seconds() -
                   sub_orig.end.total_seconds() - offset) < 1e-6
def test_speech_extraction(sample_rate, start_seconds):
    parser = GenericSubtitleParser(start_seconds=start_seconds)
    extractor = SubtitleSpeechTransformer(sample_rate=sample_rate, start_seconds=start_seconds)
    pipe = make_pipeline(parser, extractor)
    bitstring = pipe.fit_transform(BytesIO(fake_srt)).astype(bool)
    bitstring_shifted_left = np.append(bitstring[1:], [False])
    bitstring_shifted_right = np.append([False], bitstring[:-1])
    bitstring_cumsum = np.cumsum(bitstring)
    consec_ones_end_pos = np.nonzero(bitstring_cumsum *
                                     (bitstring ^ bitstring_shifted_left) *
                                     (bitstring_cumsum != np.cumsum(bitstring_shifted_right)))[0]
    prev = 0
    for pos, sub in zip(consec_ones_end_pos, parser.subs_):
        start = int(round(sub.start.total_seconds() * sample_rate))
        duration = sub.end.total_seconds() - sub.start.total_seconds()
        stop = start + int(round(duration * sample_rate))
        assert bitstring_cumsum[pos] - prev == stop - start
        prev = bitstring_cumsum[pos]
def test_max_time_found():
    parser = GenericSubtitleParser()
    extractor = SubtitleSpeechTransformer(sample_rate=100)
    pipe = make_pipeline(parser, extractor)
    pipe.fit(BytesIO(fake_srt))
    assert extractor.max_time_ == 6.062
def test_max_seconds(max_seconds):
    parser = GenericSubtitleParser(max_subtitle_seconds=max_seconds)
    parser.fit(BytesIO(fake_srt))
    assert max(sub.end - sub.start for sub in parser.subs_) <= timedelta(seconds=max_seconds)
Beispiel #8
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def detected_encoding(fname):
    parser = GenericSubtitleParser()
    parser.fit(fname)
    return parser.detected_encoding_
def detected_encoding(fname):
    parser = GenericSubtitleParser(skip_ssa_info=True)
    parser.fit(fname)
    return parser.detected_encoding_