1 files changed, 0 insertions, 87 deletions
diff --git a/power_sequencer/operators/audiosync/find_offset.py b/power_sequencer/operators/audiosync/find_offset.py
deleted file mode 100644
index 02287839..00000000
--- a/power_sequencer/operators/audiosync/find_offset.py
+++ /dev/null
@@ -1,87 +0,0 @@
-#
-# Copyright (C) 2016-2020 by Nathan Lovato, Daniel Oakey, Razvan Radulescu, and contributors
-#
-# This file is part of Power Sequencer.
-#
-# Power Sequencer is free software: you can redistribute it and/or modify it under the terms of the
-# GNU General Public License as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# Power Sequencer is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
-# without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License along with Power Sequencer. If
-# not, see <https://www.gnu.org/licenses/>.
-#
-"""
-This code is an adaptation of 'audio-offset-finder' by BBC
-"""
-import os
-import numpy as np
-
-from .mfcc import mfcc
-from .convert_and_trim import convert_and_trim
-from .std_mfcc import std_mfcc
-from .cross_correlation import cross_correlation
-from .ensure_non_zero import ensure_non_zero
-
-
-def find_offset(file1, file2, freq=8000, trim=60 * 15, correl_nframes=1000):
-    """
-    Determine the offset (in seconds) between 2 audio files
-
-    Uses cross-correlation of standardised Mel-Frequency Cepstral
-    Coefficients
-    """
-    from scipy.io import wavfile
-
-    file1 = os.path.abspath(file1)
-    file2 = os.path.abspath(file2)
-
-    wav1_path = convert_and_trim(file1, freq, trim)
-    wav2_path = convert_and_trim(file2, freq, trim)
-
-    rate1, data1 = wavfile.read(wav1_path, mmap=True)
-    data1 = data1 / (2.0 ** 15)
-
-    rate2, data2 = wavfile.read(wav2_path, mmap=True)
-    data2 = data2 / (2.0 ** 15)
-
-    data1 = ensure_non_zero(data1)
-    data2 = ensure_non_zero(data2)
-
-    mfcc1 = mfcc(data1, nwin=256, nfft=512, fs=freq, nceps=13)[0]
-    mfcc2 = mfcc(data2, nwin=256, nfft=512, fs=freq, nceps=13)[0]
-
-    mfcc1 = std_mfcc(mfcc1)
-    mfcc2 = std_mfcc(mfcc2)
-
-    frames1 = mfcc1.shape[0]
-    frames2 = mfcc2.shape[0]
-
-    if frames1 > frames2:
-        flip = 1
-
-    else:
-        flip = -1
-        mfcc1, mfcc2 = mfcc2, mfcc1
-
-    c = cross_correlation(mfcc1, mfcc2, nframes=correl_nframes)
-    try:
-        c.any()
-    except AttributeError:
-        os.remove(wav1_path)
-        os.remove(wav2_path)
-
-        return 0, 0
-
-    max_k_index = np.argmax(c)
-
-    offset = max_k_index * 160.0 / float(freq)
-    score = (c[max_k_index] - np.mean(c)) / np.std(c)
-
-    os.remove(wav1_path)
-    os.remove(wav2_path)
-
-    return offset * flip, score