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batch_processing.py
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batch_processing.py
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# -*- coding: utf-8 -*-
import os
from glob import glob
import multiprocessing
import soundfile as sf
import numpy as np
import tqdm
import yaml
from autoeq.constants import DEFAULT_MAX_GAIN, DEFAULT_TREBLE_F_LOWER, DEFAULT_TREBLE_F_UPPER, \
DEFAULT_TREBLE_GAIN_K, DEFAULT_FS, DEFAULT_BIT_DEPTH, DEFAULT_PHASE, DEFAULT_F_RES, DEFAULT_BASS_BOOST_GAIN, \
DEFAULT_BASS_BOOST_FC, DEFAULT_BASS_BOOST_Q, DEFAULT_SMOOTHING_WINDOW_SIZE, \
DEFAULT_TREBLE_SMOOTHING_WINDOW_SIZE, PEQ_CONFIGS
from autoeq.frequency_response import FrequencyResponse
def batch_processing(input_dir=None, output_dir=None, new_only=False, standardize_input=False, compensation=None,
parametric_eq=False, fixed_band_eq=False, rockbox=False,
ten_band_eq=False, parametric_eq_config=None, fixed_band_eq_config=None, convolution_eq=False,
fs=DEFAULT_FS, bit_depth=DEFAULT_BIT_DEPTH, phase=DEFAULT_PHASE, f_res=DEFAULT_F_RES,
bass_boost_gain=DEFAULT_BASS_BOOST_GAIN, bass_boost_fc=DEFAULT_BASS_BOOST_FC,
bass_boost_q=DEFAULT_BASS_BOOST_Q, tilt=None, sound_signature=None, max_gain=DEFAULT_MAX_GAIN,
window_size=DEFAULT_SMOOTHING_WINDOW_SIZE, treble_window_size=DEFAULT_TREBLE_SMOOTHING_WINDOW_SIZE,
treble_f_lower=DEFAULT_TREBLE_F_LOWER, treble_f_upper=DEFAULT_TREBLE_F_UPPER,
treble_gain_k=DEFAULT_TREBLE_GAIN_K, thread_count=1):
"""Parses files in input directory and produces equalization results in output directory."""
if not compensation and (parametric_eq or fixed_band_eq or rockbox or ten_band_eq or convolution_eq):
raise ValueError('Compensation must be specified when equalizing.')
# Dir paths to absolute
input_dir = os.path.abspath(input_dir)
glob_files = glob(os.path.join(input_dir, '**', '*.csv'), recursive=True)
if len(glob_files) == 0:
raise FileNotFoundError(f'No CSV files found in "{input_dir}"')
if compensation:
# Creates FrequencyResponse for compensation data
compensation_path = os.path.abspath(compensation)
compensation = FrequencyResponse.read_from_csv(compensation_path)
compensation.interpolate()
compensation.center()
if bit_depth == 16:
bit_depth = "PCM_16"
elif bit_depth == 24:
bit_depth = "PCM_24"
elif bit_depth == 32:
bit_depth = "PCM_32"
else:
raise ValueError('Invalid bit depth. Accepted values are 16, 24 and 32.')
if sound_signature is not None:
sound_signature = FrequencyResponse.read_from_csv(sound_signature)
if len(sound_signature.error) > 0:
# Error data present, replace raw data with it
sound_signature.raw = sound_signature.error
sound_signature.interpolate()
sound_signature.center()
if parametric_eq_config is not None:
if type(parametric_eq_config) is str and os.path.isfile(parametric_eq_config):
# Parametric EQ config is a file path
with open(parametric_eq_config) as fh:
parametric_eq_config = yaml.safe_load(fh)
else:
if type(parametric_eq_config) is str:
parametric_eq_config = [parametric_eq_config]
parametric_eq_config = [
PEQ_CONFIGS[config] if type(config) is str else config for config in parametric_eq_config]
if fixed_band_eq_config is not None:
if os.path.isfile(fixed_band_eq_config):
# Parametric EQ config is a file path
with open(fixed_band_eq_config) as fh:
fixed_band_eq_config = yaml.safe_load(fh)
else:
if fixed_band_eq_config not in PEQ_CONFIGS:
raise ValueError(
f'Unrecognized fixed band eq config "{fixed_band_eq_config}".'
f'If this was meant to be a file, the file does not exist.')
fixed_band_eq_config = PEQ_CONFIGS[fixed_band_eq_config]
# Prepare list of arguments for all the function calls to generate results.
n_total = 0
file_paths = []
args_list = []
for input_file_path in glob_files:
relative_path = os.path.relpath(input_file_path, input_dir)
output_file_path = os.path.join(output_dir, relative_path) if output_dir else None
output_file_dir = os.path.split(output_file_path)[0]
if not new_only or not os.path.isdir(output_file_dir) or not len(os.listdir(output_file_dir)):
# Not looking for only new ones or the output directory doesn't exist or it's empty
file_paths.append((input_file_path, output_file_path))
n_total += 1
args = (input_file_path, output_file_path, bass_boost_fc, bass_boost_gain, bass_boost_q, bit_depth,
compensation, convolution_eq, f_res, fixed_band_eq, fs, parametric_eq_config,
fixed_band_eq_config, max_gain, window_size, treble_window_size,
parametric_eq, phase, rockbox, sound_signature, standardize_input,
ten_band_eq, tilt, treble_f_lower, treble_f_upper, treble_gain_k)
args_list.append(args)
if not thread_count:
thread_count = multiprocessing.cpu_count()
with multiprocessing.Pool(thread_count) as pool:
results = []
for result in tqdm.tqdm(
pool.imap_unordered(process_file_wrapper, args_list, chunksize=1), total=len(args_list)):
results.append(result)
return results
def process_file_wrapper(params):
return process_file(*params)
def process_file(input_file_path, output_file_path, bass_boost_fc, bass_boost_gain, bass_boost_q, bit_depth,
compensation, convolution_eq, f_res, fixed_band_eq, fs, parametric_eq_config,
fixed_band_eq_config, max_gain, window_size, treble_window_size, parametric_eq, phase, rockbox,
sound_signature, standardize_input, ten_band_eq, tilt, treble_f_lower, treble_f_upper,
treble_gain_k):
# Read data from input file
fr = FrequencyResponse.read_from_csv(input_file_path)
# Copy relative path to output directory
output_dir_path, _ = os.path.split(output_file_path)
os.makedirs(output_dir_path, exist_ok=True)
if standardize_input:
# Overwrite input data in standard sampling and zero bias
fr.interpolate()
fr.center()
fr.write_to_csv(input_file_path)
if ten_band_eq:
# Ten band eq is a shortcut for setting Fc and Q values to standard 10-band equalizer filters parameters
fixed_band_eq = True
fixed_band_eq_config = PEQ_CONFIGS['10_BAND_GRAPHIC_EQ']
if rockbox and not ten_band_eq:
raise ValueError('Rockbox configuration requires ten-band eq')
# Process and equalize
fr.process(
compensation=compensation,
min_mean_error=True,
bass_boost_gain=bass_boost_gain,
bass_boost_fc=bass_boost_fc,
bass_boost_q=bass_boost_q,
tilt=tilt,
sound_signature=sound_signature,
max_gain=max_gain,
window_size=window_size,
treble_window_size=treble_window_size,
treble_f_lower=treble_f_lower,
treble_f_upper=treble_f_upper,
treble_gain_k=treble_gain_k,)
fr.write_eqapo_graphic_eq(output_file_path.replace('.csv', ' GraphicEQ.txt'), normalize=True)
if parametric_eq:
parametric_peqs = fr.optimize_parametric_eq(parametric_eq_config, fs[0]) if parametric_eq else None
fr.write_eqapo_parametric_eq(output_file_path.replace('.csv', ' ParametricEQ.txt'), parametric_peqs)
else:
parametric_peqs = None
if fixed_band_eq:
fixed_band_peq = fr.optimize_fixed_band_eq(fixed_band_eq_config, fs[0])[0] if fixed_band_eq else None
fr.write_eqapo_parametric_eq(output_file_path.replace('.csv', ' FixedBandEQ.txt'), [fixed_band_peq])
if rockbox:
# Write 10 band eq to Rockbox .cfg file
fr.write_rockbox_10_band_fixed_eq(output_file_path.replace('.csv', ' RockboxEQ.cfg'), fixed_band_peq)
else:
fixed_band_peq = None
if convolution_eq:
for _fs in fs:
if phase in ['minimum', 'both']: # Write minimum phase impulse response
minimum_phase_fir = fr.minimum_phase_impulse_response(fs=_fs, f_res=f_res, normalize=True)
minimum_phase_ir = np.tile(minimum_phase_fir, (2, 1)).T
sf.write(
output_file_path.replace('.csv', f' minimum phase {_fs}Hz.wav'), minimum_phase_ir, _fs, bit_depth)
if phase in ['linear', 'both']: # Write linear phase impulse response
linear_phase_fir = fr.linear_phase_impulse_response(fs=_fs, f_res=f_res, normalize=True)
linear_phase_ir = np.tile(linear_phase_fir, (2, 1)).T
sf.write(
output_file_path.replace('.csv', f' linear phase {_fs}Hz.wav'), linear_phase_ir, _fs, bit_depth)
fr.write_to_csv(output_file_path)
fr.plot_graph(
show=False,
close=True,
file_path=output_file_path.replace('.csv', '.png'),
)
fr.write_readme(
os.path.join(output_dir_path, 'README.md'),
parametric_peqs=parametric_peqs,
fixed_band_peq=fixed_band_peq)
return fr