Created
March 19, 2015 16:17
-
-
Save jiaaro/faa96fabd252b8552066 to your computer and use it in GitHub Desktop.
Super simple BPM detection with pydub
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from pydub import AudioSegment | |
from pydub.silence import detect_nonsilent | |
seg = AudioSegment.from_file("./ghosts_and_stuff.m4a") | |
# reduce loudness of sounds over 120Hz (focus on bass drum, etc) | |
seg = seg.low_pass_filter(120.0) | |
# we'll call a beat: anything above average loudness | |
beat_loudness = seg.dBFS | |
# the fastest tempo we'll allow is 240 bpm (60000ms / 240beats) | |
minimum_silence = int(60000 / 240.0) | |
nonsilent_times = detect_nonsilent(seg, minimum_silence, beat_loudness) | |
spaces_between_beats = [] | |
last_t = nonsilent_times[0][0] | |
for peak_start, _ in nonsilent_times[1:]: | |
spaces_between_beats.append(peak_start - last_t) | |
last_t = peak_start | |
# We'll base our guess on the median space between beats | |
spaces_between_beats = sorted(spaces_between_beats) | |
space = spaces_between_beats[len(spaces_between_beats) / 2] | |
bpm = 60000 / space |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment