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File size: 2,508 Bytes
fe7e262 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | """
CPJKU's beat_this
- reference: https://github.com/CPJKU/beat_this
"""
import sys
from pathlib import Path
import torch
from .utils import load_audio
if not sys.version_info < (3, 10):
from beat_this.inference import Audio2Beats
class BeatThis:
def __init__(self, cuda=None, dbn=True):
if cuda is None:
cuda = torch.cuda.is_available()
self.audio2beats = Audio2Beats(
device="cuda" if cuda else "cpu",
dbn=dbn,
)
self.use_dbn = dbn
@torch.no_grad()
def __call__(
self,
file_or_array,
sr=None,
beats_per_bar=[3, 4],
min_bpm=55.0,
max_bpm=215.0,
fps=50,
transition_lambda=100,
):
"""
Function for extracting beat and downbeat positions (in seconds) from a file or a data array.
Args:
file_or_array (str or Path or ndarray): Path to the audio file or numpy array containing the audio data.
sr (int, optional): Sample rate of the audio file. Required if `file_or_array` is a numpy array. Defaults to None.
if dbn is True:
beats_per_bar (list, optional): List of possible beats per bar. Defaults to [3, 4].
min_bpm (float, optional): Minimum tempo in BPM. Defaults to 55.0.
max_bpm (float, optional): Maximum tempo in BPM. Defaults to 215.0.
fps (int, optional): Frames per second. Defaults to 50.
Returns:
beats (ndarray): Array of beat positions in seconds.
downbeats (ndarray): Array of downbeat positions in seconds.
"""
if sys.version_info < (3, 10):
raise ImportError("Python 3.10 or higher is required to use this function.")
if isinstance(file_or_array, (str, Path)):
audio, sr = load_audio(file_or_array, dtype="float64")
else:
audio = file_or_array
if self.use_dbn:
from madmom.features.downbeats import DBNDownBeatTrackingProcessor
# WARN: This is a hacky way to set the DBN parameters
dbn = DBNDownBeatTrackingProcessor(
beats_per_bar=beats_per_bar,
min_bpm=min_bpm,
max_bpm=max_bpm,
fps=fps,
transition_lambda=transition_lambda,
)
self.audio2beats.frames2beats.dbn = dbn
beats, downbeats = self.audio2beats(audio, sr)
return beats, downbeats
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