first

.gitignore

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+.venv

Makefile

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+all: .venv/bin/activate
+	source .venv/bin/activate && pip install -r requirements.txt > /dev/null && ./skz-usbprep.py
+
+.venv/bin/activate:
+	python -m venv --prompt SKZ-USBPREP .venv
+
+clean:
+	rm -rf .venv

requirements.txt

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+essentia

skz-usbprep.py

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+#!/usr/bin/env python3
+import argparse, os, shutil, subprocess
+from multiprocessing import Pool, cpu_count
+
+#os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+#import tensorflow as tf
+#tf.get_logger().setLevel('FATAL')
+
+from essentia.standard import *
+essentia.log.infoActive = False
+
+DIRS = ['_new', '_new-dubstep']
+RATE = 44100 
+
+parser = argparse.ArgumentParser()
+parser.add_argument('dirs', nargs='*', default=DIRS, help='the list of directories')
+args = parser.parse_args()
+
+def calculate_key(audio_path):
+    import essentia.streaming as ess
+    import essentia
+
+    loader = ess.MonoLoader(filename=audio_path)
+    framecutter = ess.FrameCutter(frameSize=4096, hopSize=2048, silentFrames='noise')
+    windowing = ess.Windowing(type='blackmanharris62')
+    spectrum = ess.Spectrum()
+    spectralpeaks = ess.SpectralPeaks(orderBy='magnitude',
+                                      magnitudeThreshold=0.00001,
+                                      minFrequency=20,
+                                      maxFrequency=3500,
+                                      maxPeaks=60)
+    # Use default HPCP parameters for plots.
+    # However we will need higher resolution and custom parameters for better Key estimation.
+    hpcp = ess.HPCP()
+    hpcp_key = ess.HPCP(size=36, # We will need higher resolution for Key estimation.
+                        referenceFrequency=440, # Assume tuning frequency is 44100.
+                        bandPreset=False,
+                        minFrequency=20,
+                        maxFrequency=3500,
+                        weightType='cosine',
+                        nonLinear=False,
+                        windowSize=1.)
+    
+    key = ess.Key(profileType='edmm', # Use profile for electronic music.
+                  numHarmonics=4,
+                  pcpSize=36,
+                  slope=0.6,
+                  usePolyphony=True,
+                  useThreeChords=True)
+    
+    # Use pool to store data.
+    pool = essentia.Pool()
+    
+    # Connect streaming algorithms.
+    loader.audio >> framecutter.signal
+    framecutter.frame >> windowing.frame >> spectrum.frame
+    spectrum.spectrum >> spectralpeaks.spectrum
+    spectralpeaks.magnitudes >> hpcp.magnitudes
+    spectralpeaks.frequencies >> hpcp.frequencies
+    spectralpeaks.magnitudes >> hpcp_key.magnitudes
+    spectralpeaks.frequencies >> hpcp_key.frequencies
+    hpcp_key.hpcp >> key.pcp
+    hpcp.hpcp >> (pool, 'tonal.hpcp')
+    key.key >> (pool, 'tonal.key_key')
+    key.scale >> (pool, 'tonal.key_scale')
+    key.strength >> (pool, 'tonal.key_strength')
+    
+    # Run streaming network.
+    essentia.run(loader)
+    return pool['tonal.key_key'], pool['tonal.key_scale']
+
+def calculate_bpm(audio_path):
+    audio44100 = MonoLoader(filename=audio_path, sampleRate=44100, resampleQuality=4)()
+    start44100 = int(len(audio44100)*0.2)
+    end44100 = int(len(audio44100)*0.8)
+    
+    rhythm_extractor = RhythmExtractor2013(method="multifeature")
+    bpm, _, _, _, _ = rhythm_extractor(audio44100[start44100:end44100])
+    if bpm < 100:
+        bpm = bpm * 2
+    return bpm
+
+def reencode(audio_path):
+    if '.wav' in audio_path[-4:]:
+        subprocess.run("ffmpeg -hide_banner -loglevel error -y -i \"" + audio_path + "\" -map 0:a -c:a pcm_s16le -ar " + str(RATE) + " -write_xing 0 -id3v2_version 0 -map_metadata -1 -bitexact \"" + audio_path + ".reenc.wav\"", shell=True)
+        shutil.move(audio_path + ".reenc.wav", audio_path)
+        return audio_path
+    elif '.flac' in audio_path[-5:]:
+        subprocess.run("ffmpeg -hide_banner -loglevel error -y -i \"" + audio_path + "\" -map 0:a -c:a pcm_s16le -ar " + str(RATE) + " -write_xing 0 -id3v2_version 0 -map_metadata -1 -bitexact \"" + audio_path.replace('.flac', '.wav') + "\"", shell=True)
+        os.remove(audio_path)
+        return audio_path.replace('.flac', '.wav')
+    elif '.mp3' in audio_path[-4:]:
+        subprocess.run("ffmpeg -hide_banner -loglevel error -y -i \"" + audio_path + "\" -map 0:a -c:a copy -write_xing 0 -id3v2_version 0 -map_metadata -1 \"" + audio_path + ".reenc.mp3\"", shell=True)
+        shutil.move(audio_path + ".reenc.mp3", audio_path)
+        return(audio_path)
+    else:
+        print("Can't reencode", audio_path)
+        return None
+ 
+def rmtags(audio_path):
+    if '.wav' in audio_path[-4:]:
+        subprocess.run("id3v2 -D \"" + audio_path + "\" > /dev/null", shell=True)
+    elif '.mp3' in audio_path[-4:]:
+        subprocess.run("id3v2 -D \"" + audio_path + "\" > /dev/null", shell=True)
+        subprocess.run("apetag -m erase -i \"" + audio_path + "\" > /dev/null", shell=True)
+    else:
+        print("Can't rmtags'", audio_path)
+
+def process(audio_path):
+    #key, scale = calculate_key(audio_path)
+    audio_path = reencode(audio_path)
+    if audio_path is not None:
+        bpm = "{:.2f}".format(calculate_bpm(audio_path))
+        if bpm in audio_path:
+            name = audio_path
+        else:
+            rmtags(audio_path)
+            name = audio_path[:-4] + " - " + bpm + audio_path[-4:]
+            shutil.move(audio_path, name)
+        return name
+
+files = []
+
+for dir in args.dirs:
+    for file in os.listdir(dir):
+        files.append(dir + "/" + file)
+
+NICENESS=15
+
+with Pool(initializer=os.nice, initargs=(NICENESS,)) as pool:
+    for result in pool.imap_unordered(process, files):
+        print(result)
+
+print('done\n')