def calculateFeatures(filename):
y, sr = librosa.load(filename)
hop_length = 512
section_length = 30
permit_length = 0 #No overlap
n_paras = 4
tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)
n_beats = len(beat_frames)
y_harmonic, _ = librosa.effects.hpss(y)
beat_times = librosa.frames_to_time(beat_frames, sr=sr)
mfcc = librosa.feature.mfcc(y=y, sr=sr, hop_length=hop_length, n_mfcc=1)
mfcc_delta = librosa.feature.delta(mfcc)
beat_mfcc_delta = librosa.util.sync(np.vstack([mfcc, mfcc_delta]), beat_frames)
chromagram = librosa.feature.chroma_cqt(y=y_harmonic, sr=sr)
beat_chroma = librosa.util.sync(chromagram, beat_frames, aggregate=np.median)
delta_rms = np.square(beat_mfcc_delta[1])
prev_delta_sums = np.empty((n_beats-section_length+1))
total_sum = np.sum(delta_rms[:section_length])
prev_delta_sums[0] = total_sum
for pos in range(n_beats-section_length):
total_sum = total_sum - delta_rms[pos] + delta_rms[pos+section_length]
prev_delta_sums[pos+1] = total_sum
prev_delta_sums_delta = librosa.feature.delta(prev_delta_sums)
para_init_locs = []
for n_p in range(n_paras):
lowest = 50
lowest_loc = 0
for loc, each_sum_delta in enumerate(prev_delta_sums_delta):
#Check valid loc
valid_loc = True
for each_loc in para_init_locs:
if loc > each_loc - (section_length - permit_length) and loc < each_loc + (section_length - permit_length):
valid_loc = False
break
if each_sum_delta <= lowest and valid_loc:
lowest = each_sum_delta
lowest_loc = loc
para_init_locs.append(lowest_loc)
para_init_locs.sort()
#print(para_init_locs)
all_features = np.empty((n_paras*section_length, 2)) #0 - mfcc, 1 - chroma
for n_p in range(n_paras):
all_features[n_p*section_length:(n_p+1)*section_length, 0] = beat_mfcc_delta[0][para_init_locs[n_p]:para_init_locs[n_p]+section_length] / 250
all_features[n_p*section_length:(n_p+1)*section_length, 1] = np.argmax(beat_chroma[:, para_init_locs[n_p]:para_init_locs[n_p]+section_length], axis=0)/11
return all_features.reshape((n_paras*section_length*2))
评论列表
文章目录
