298 lines
8.6 KiB
Python
Executable File
298 lines
8.6 KiB
Python
Executable File
#!/usr/bin/env python3
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# ffmpeg wrapper
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import multiprocessing
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from os.path import isdir, isfile
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import ffmpy
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# argument parsing
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import argparse
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# multiprocessing stuff
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from multiprocessing import Pool
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from multiprocessing import cpu_count
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# executing some commands
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import subprocess
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# parsing json output of loudnorm
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import json
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# file/directory handling
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import os
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# most recent starttime for program
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import time
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from random import randint
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from typing import Any, Optional
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"""
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"""
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# FIXME
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# inputfile = (
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# '/home/marc/Downloads/FalKKonE - 01 Aria (From "Berserk: The Golden Age Arc").flac'
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# )
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# inputfile = "/home/marc/Downloads/test441.opus"
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# outputfile = "/home/marc/Downloads/test441_out.opus"
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# srcfolder = "/home/marc/Downloads/MusikRaw"
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# destfolder = "/home/marc/Downloads/Musik"
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musicfile_extensions = (".flac", ".wav", ".mp3", ".m4a", ".aac", ".opus")
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def get_format(inputfile) -> str:
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# get codec format
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# https://stackoverflow.com/a/29610897
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# this shows the codecs of all audio streams present in the file, which shouldn't matter unless you have more than one stream
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ff = ffmpy.FFprobe(
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inputs={inputfile: None},
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global_options=(
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"-v quiet",
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"-select_streams a",
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"-show_entries stream=codec_name",
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"-of default=noprint_wrappers=1:nokey=1",
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),
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)
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# print(ff.cmd)
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proc = subprocess.Popen(ff.cmd, shell=True, stdout=subprocess.PIPE)
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# NOTE read output from previous command
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# rstrip: remove trailing newline
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# decode: convert from binary string to normal string
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format: str = (
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proc.stdout.read() # pyright: ignore[reportOptionalMemberAccess]
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.rstrip()
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.decode("utf8")
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)
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# print(format)
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return format
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def remove_picture(inputfile):
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"""
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This function makes sure no image is attached to the audio stream.
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An image might cause problems for the later conversion to opus.
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Parameters:
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inputfile (str): Path to file
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"""
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tmpfile = os.path.splitext(inputfile)[0] + ".tmp" + os.path.splitext(inputfile)[1]
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ff = ffmpy.FFmpeg(
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inputs={inputfile: None},
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outputs={tmpfile: "-vn -c:a copy"},
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global_options=("-v error"),
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)
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ff.run()
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os.remove(inputfile)
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os.rename(tmpfile, inputfile)
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def loudness_info(inputfile) -> dict[str, str]:
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print("Measuring loudness of ", os.path.basename(inputfile))
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# get format from file
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# inputformat = get_format(inputfile)
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# NOTE format is actually unnecessary here
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ff = ffmpy.FFmpeg(
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inputs={inputfile: None},
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outputs={"/dev/null": "-pass 1 -filter:a loudnorm=print_format=json -f null"},
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global_options=("-y"),
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)
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# print(ff.cmd)
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proc = subprocess.Popen(
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ff.cmd, shell=True, stderr=subprocess.STDOUT, stdout=subprocess.PIPE
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)
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# NOTE get loudness info from subprocess
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# rstrip: remove trailing newline
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# decode: convert from binary string to utf8
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# splitlines: list of lines (only 12 last ones, length of the output json)
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# join: reassembles the list of lines and separates with "\n"
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loudness_json: str = "\n".join(
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proc.stdout.read().rstrip().decode("utf8").splitlines()[-12:]
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)
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# decode json to dict
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loudness: dict[str, str] = json.loads(loudness_json)
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# print(loudness_json)
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# print(ff.cmd)
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return loudness
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def convert(inputfile, outputfile, loudness) -> Optional[list[Any]]:
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print("Working on ", os.path.basename(inputfile))
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# coverpath = os.path.join(os.path.dirname(inputfile), "cover.jpg")
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# NOTE including covers into ogg/opus containers currently doesn't work
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# https://trac.ffmpeg.org/ticket/4448
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inputcmd = {inputfile: None}
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outputcmd = {
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outputfile: "-pass 2"
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" "
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"-filter:a"
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" "
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"loudnorm=I=-26.0:"
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"LRA=9.0:"
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"measured_I={input_i}:"
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"measured_LRA={input_lra}:"
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"measured_tp={input_tp}:measured_thresh={input_thresh}:"
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"print_format=json"
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" "
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"-c:a libopus"
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" "
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"-b:a 320k".format(
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input_i=loudness["input_i"],
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input_lra=loudness["input_lra"],
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input_tp=loudness["input_tp"],
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input_thresh=loudness["input_thresh"],
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)
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}
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ff = ffmpy.FFmpeg(
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inputs=inputcmd,
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outputs=outputcmd,
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# global_options=("-y", "-v error"),
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global_options=("-y"),
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)
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# ff.run()
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proc = subprocess.Popen(
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ff.cmd, shell=True, stderr=subprocess.STDOUT, stdout=subprocess.PIPE
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)
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# NOTE get loudness info from subprocess
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# rstrip: remove trailing newline
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# decode: convert from binary string to utf8
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# splitlines: list of lines (only 12 last ones, length of the output json)
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# join: reassembles the list of lines and separates with "\n"
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loudness_json: str = "\n".join(
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proc.stdout.read().rstrip().decode("utf8").splitlines()[-12:]
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)
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# decode json to dict
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loudness_new: dict[str, str] = json.loads(loudness_json)
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if loudness_new["normalization_type"] != "linear":
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nonlinear: list[Any] = [inputfile, loudness_new]
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return nonlinear
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def main(inputfile: str) -> Optional[list[Any]]:
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"""
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Main program loop
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Parameters:
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inputfile (str): Path to input file
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"""
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# set output folder to parent path + "normalized"
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outputfolder = os.path.join(os.path.dirname(inputfile), "normalized")
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# NOTE create output folder
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# because multiple parallel processes are at work here,
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# there might be conflicts with one trying to create the directory although it already exists
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# this while loop makes sure the directory does exist
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# the try/except block ensures the error is caught and (hopefully) doesn't happen again just after with random sleep
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# there's very likely a better way to do this, idk
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while not os.path.isdir(outputfolder):
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try:
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os.mkdir(outputfolder)
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except:
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time.sleep(randint(0, 4))
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# output file path
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noext_infile: str = os.path.splitext(os.path.basename(inputfile))[0]
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outputfile: str = os.path.join(outputfolder, noext_infile + ".opus")
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# print(inputfile)
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# print(os.path.dirname(inputfile))
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# print(os.path.basename(inputfile))
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# print(outputfile)
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# remove_picture(inputfile=inputfile)
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loudness = loudness_info(inputfile=inputfile)
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nonlinear: Optional[list[Any]] = convert(
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inputfile=inputfile,
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outputfile=outputfile,
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loudness=loudness,
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)
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return nonlinear
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if __name__ == "__main__":
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# start time of program
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starttime = time.time()
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parser = argparse.ArgumentParser(description="")
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# Input directory
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parser.add_argument(
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"-i", "--input-dir", required=True, type=str, help="Input source directory"
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)
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# number of cpus/threads to use, defaults to all available
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parser.add_argument(
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"-c",
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"--cpu-count",
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required=False,
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type=int,
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help="Number of cpu cores",
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default=multiprocessing.cpu_count(),
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)
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# in case you wanted to rerun the conversion for everything
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parser.add_argument(
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"-r",
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"--reset",
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required=False,
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action="store_true",
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help="Rerun conversion for all files",
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)
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args = parser.parse_args()
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srcfolder = args.input_dir
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cpu = args.cpu_count
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reset = args.reset
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# file where last run timestamp is stored
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timefile = os.path.join(srcfolder, "run.time")
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# list of non-linear normalizations
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nonlinear_all: Optional[list[Any]] = []
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# get time of previous run
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if reset:
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timeprev = 0
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elif os.path.isfile(timefile):
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with open(timefile, "r") as file:
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timeprev = file.read()
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else:
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timeprev = 0
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# print(timeprev)
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musicfiles: list[str] = []
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for root, dirs, files in os.walk(srcfolder):
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# ignore the "normalized" subfolder
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dirs[:] = [d for d in dirs if d not in ["normalized"]]
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for file in files:
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if file.endswith(musicfile_extensions):
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filepath = os.path.join(root, file)
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# only file newer than the last run are added
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if os.path.getmtime(filepath) >= float(timeprev):
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musicfiles.append(os.path.join(root, file))
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# print(musicfiles)
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with Pool(cpu) as p:
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nonlinear_all: Optional[list[Any]] = p.map(main, musicfiles)
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# write this run's time into file
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with open(timefile, "w") as file:
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file.write(str(starttime))
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print("Dynamically normalized music:")
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for i in nonlinear_all:
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# NOTE ignore empty and "None" values
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if i:
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print(i)
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