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changed back to [0,1] normal

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k 2025-10-15 02:19:33 -04:00
parent 1a66f31048
commit 78ece6996f
2 changed files with 13 additions and 13 deletions
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22
data.py
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@ -6,13 +6,15 @@ import mlflow
SAMPLE_RATE = 22050 SAMPLE_RATE = 22050
@mlflow.trace #@mlflow.trace
def process_file(file_path): def process_file(file_path):
""" """
Load 10 second chunks single song. Load 10 second chunks single song.
""" """
y, sr = librosa.load(file_path, mono=True, sr=SAMPLE_RATE) y, sr = librosa.load(file_path, mono=True, sr=SAMPLE_RATE)
size = int(SAMPLE_RATE * 5) if(not sr == SAMPLE_RATE):
return []
size = int(SAMPLE_RATE * 10)
sample_len = len(y) sample_len = len(y)
file_chunks = [] file_chunks = []
@ -20,18 +22,19 @@ def process_file(file_path):
end = start_pos + size end = start_pos + size
if end <= sample_len: if end <= sample_len:
chunk = y[start_pos:end] chunk = y[start_pos:end]
chunk = librosa.feature.melspectrogram(y=chunk,sr=SAMPLE_RATE) #chunk = librosa.feature.melspectrogram(y=chunk,sr=SAMPLE_RATE)
chunk = ((librosa.amplitude_to_db(chunk,ref=np.max)+40)/40) #chunk = ((librosa.amplitude_to_db(chunk,ref=np.max)+40)/40)
file_chunks.append(chunk) file_chunks.append(chunk)
return file_chunks return file_chunks
@mlflow.trace #@mlflow.trace
def load(): def load():
""" """
Load 10 second chunks of songs. Load 10 second chunks of songs.
""" """
audio = [] audio = []
files = list(Path("./data/").glob("*.mp3")) files = list(Path("./data/").glob("*.mp3"))
#files = files[:12]
with Pool(cpu_count()) as pool: with Pool(cpu_count()) as pool:
chunk_list = pool.map(process_file, files) chunk_list = pool.map(process_file, files)
for l in chunk_list: for l in chunk_list:
@ -52,15 +55,12 @@ def audio_split(audio):
x = librosa.feature.melspectrogram(y=x, sr=SAMPLE_RATE) x = librosa.feature.melspectrogram(y=x, sr=SAMPLE_RATE)
y = librosa.feature.melspectrogram(y=y, sr=SAMPLE_RATE) y = librosa.feature.melspectrogram(y=y, sr=SAMPLE_RATE)
ma,mi = x.max(), x.min() x = ((librosa.amplitude_to_db(x,ref=np.max)+80)/80)
x = (x - mi) / (ma - mi) y = ((librosa.amplitude_to_db(y,ref=np.max)+80)/80)
ma,mi = y.max(), y.min()
y = (y - mi) / (ma - mi)
return x,y return x,y
def detaset(chunks): def dataset(chunks):
""" """
convert 10 second chunks to dataset convert 10 second chunks to dataset
""" """

4
show.py
View File

@ -6,7 +6,7 @@ import mlflow
SAMPLE_RATE = 22050 SAMPLE_RATE = 22050
def logSpec(spec,e): def logSpec(spec,e):
#spec = ((spec*40)-40) spec = ((spec*80)-80)
#spec = librosa.db_to_amplitude(spec) #spec = librosa.db_to_amplitude(spec)
plt.figure(figsize=(10, 4)) plt.figure(figsize=(10, 4))
librosa.display.specshow(spec, sr=SAMPLE_RATE, librosa.display.specshow(spec, sr=SAMPLE_RATE,
@ -15,7 +15,7 @@ def logSpec(spec,e):
plt.colorbar(format='%+2.0f dB') plt.colorbar(format='%+2.0f dB')
plt.title('Mel spectrogram') plt.title('Mel spectrogram')
mlflow.log_figure(plt.gcf(), f"output_{e}.png") mlflow.log_figure(plt.gcf(), f"output_{e}.png")
#plt.close() plt.close()
def playSpec(spec): def playSpec(spec):
S = librosa.feature.inverse.mel_to_stft(spec, sr=SAMPLE_RATE) S = librosa.feature.inverse.mel_to_stft(spec, sr=SAMPLE_RATE)