def find_chorus(chroma, sr, song_length_sec, clip_length):
"""
Find the most repeated chorus
Args:
chroma: 12 x n frequency chromogram
sr: sample rate of the song, usually 22050
song_length_sec: length in seconds of the song (lost in processing chroma)
clip_length: minimum length in seconds we want our chorus to be (at least 10-15s)
Returns: Time in seconds of the start of the best chorus
"""
num_samples = chroma.shape[1]
time_time_similarity = TimeTimeSimilarityMatrix(chroma, sr)
time_lag_similarity = TimeLagSimilarityMatrix(chroma, sr)
# Denoise the time lag matrix
chroma_sr = num_samples / song_length_sec
smoothing_size_samples = int(SMOOTHING_SIZE_SEC * chroma_sr)
time_lag_similarity.denoise(time_time_similarity.matrix,
smoothing_size_samples)
# Detect lines in the image
clip_length_samples = clip_length * chroma_sr
candidate_rows = local_maxima_rows(time_lag_similarity.matrix)
lines = detect_lines(time_lag_similarity.matrix, candidate_rows,
clip_length_samples)
if len(lines) == 0:
print(
f"No choruses were detected. Trying with a smaller search duration."
)
return None
line_scores = count_overlapping_lines(
lines, OVERLAP_PERCENT_MARGIN * clip_length_samples,
clip_length_samples)
best_chorus = best_segment(line_scores)
return best_chorus.start / chroma_sr
from pychorus import create_chroma
from pychorus.similarity_matrix import TimeTimeSimilarityMatrix, TimeLagSimilarityMatrix
chroma, _, sr, _ = create_chroma("daft.wav")
time_time_similarity = TimeTimeSimilarityMatrix(chroma, sr)
time_lag_similarity = TimeLagSimilarityMatrix(chroma, sr)
# Visualize the results
# time_time_similarity.display()
# time_lag_similarity.display()