Add python scripts

.gitignore

@@ -6,6 +6,7 @@
 /resources/samples
 /build
 /cmake-build-*
+/venv
 
 .DS_Store
 *.pdf

requirements.txt

@@ -0,0 +1,5 @@
+librosa
+matplotlib
+
+autopep8
+pylint

src/Scripts/bpm_detect.py

@@ -0,0 +1,28 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+import librosa
+import librosa.display
+
+y, sr = librosa.load('/home/tobante/Music/Loops/Bass.wav', sr=None, mono=True)
+onset_env = librosa.onset.onset_strength(y=y, sr=sr, aggregate=np.median)
+tempo, beats = librosa.beat.beat_track(onset_envelope=onset_env, sr=sr)
+
+
+hop_length = 512
+fig, ax = plt.subplots(nrows=2, sharex=True)
+times = librosa.times_like(onset_env, sr=sr, hop_length=hop_length)
+
+M = librosa.feature.melspectrogram(y=y, sr=sr, hop_length=hop_length)
+librosa.display.specshow(librosa.power_to_db(M, ref=np.max), y_axis='mel',
+ x_axis='time', hop_length=hop_length, ax=ax[0])
+
+ax[0].label_outer()
+ax[0].set(title='Mel spectrogram')
+
+ax[1].plot(times, librosa.util.normalize(onset_env), label='Onset strength')
+ax[1].vlines(times[beats], 0, 2, alpha=0.5,
+ color='r', linestyle='--', label='Beats')
+ax[1].legend()
+
+plt.show()