220 lines
8.6 KiB
Python
220 lines
8.6 KiB
Python
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# coding=utf-8
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# Copyright (C) 2020 ATHENA AUTHORS; Yiping Peng; Ne Luo
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# All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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# Only support eager mode and TF>=2.0.0
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# pylint: disable=no-member, invalid-name, relative-beyond-top-level
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# pylint: disable=too-many-locals, too-many-statements, too-many-arguments, too-many-instance-attributes
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""" voxceleb 1 & 2 """
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import hashlib
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import os
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import subprocess
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import sys
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import zipfile
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import pandas
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import soundfile as sf
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from absl import logging
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SUBSETS = {
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"vox1_dev_wav": [
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad",
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],
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"vox1_test_wav": ["https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip"],
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"vox2_dev_aac": [
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partaa",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partab",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partac",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partad",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partae",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partaf",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partag",
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"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partah",
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],
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"vox2_test_aac": ["https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_test_aac.zip"],
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}
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MD5SUM = {
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"vox1_dev_wav": "ae63e55b951748cc486645f532ba230b",
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"vox2_dev_aac": "bbc063c46078a602ca71605645c2a402",
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"vox1_test_wav": "185fdc63c3c739954633d50379a3d102",
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"vox2_test_aac": "0d2b3ea430a821c33263b5ea37ede312",
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}
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USER = {"user": "", "password": ""}
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speaker_id_dict = {}
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def download_and_extract(directory, subset, urls):
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"""Download and extract the given split of dataset.
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Args:
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directory: the directory where to put the downloaded data.
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subset: subset name of the corpus.
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urls: the list of urls to download the data file.
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"""
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os.makedirs(directory, exist_ok=True)
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try:
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for url in urls:
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zip_filepath = os.path.join(directory, url.split("/")[-1])
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if os.path.exists(zip_filepath):
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continue
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logging.info("Downloading %s to %s" % (url, zip_filepath))
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subprocess.call(
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"wget %s --user %s --password %s -O %s" % (url, USER["user"], USER["password"], zip_filepath),
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shell=True,
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)
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statinfo = os.stat(zip_filepath)
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logging.info("Successfully downloaded %s, size(bytes): %d" % (url, statinfo.st_size))
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# concatenate all parts into zip files
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if ".zip" not in zip_filepath:
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zip_filepath = "_".join(zip_filepath.split("_")[:-1])
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subprocess.call("cat %s* > %s.zip" % (zip_filepath, zip_filepath), shell=True)
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zip_filepath += ".zip"
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extract_path = zip_filepath.strip(".zip")
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# check zip file md5sum
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with open(zip_filepath, "rb") as f_zip:
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md5 = hashlib.md5(f_zip.read()).hexdigest()
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if md5 != MD5SUM[subset]:
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raise ValueError("md5sum of %s mismatch" % zip_filepath)
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with zipfile.ZipFile(zip_filepath, "r") as zfile:
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zfile.extractall(directory)
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extract_path_ori = os.path.join(directory, zfile.infolist()[0].filename)
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subprocess.call("mv %s %s" % (extract_path_ori, extract_path), shell=True)
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finally:
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# os.remove(zip_filepath)
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pass
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def exec_cmd(cmd):
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"""Run a command in a subprocess.
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Args:
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cmd: command line to be executed.
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Return:
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int, the return code.
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"""
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try:
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retcode = subprocess.call(cmd, shell=True)
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if retcode < 0:
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logging.info(f"Child was terminated by signal {retcode}")
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except OSError as e:
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logging.info(f"Execution failed: {e}")
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retcode = -999
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return retcode
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def decode_aac_with_ffmpeg(aac_file, wav_file):
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"""Decode a given AAC file into WAV using ffmpeg.
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Args:
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aac_file: file path to input AAC file.
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wav_file: file path to output WAV file.
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Return:
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bool, True if success.
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"""
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cmd = f"ffmpeg -i {aac_file} {wav_file}"
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logging.info(f"Decoding aac file using command line: {cmd}")
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ret = exec_cmd(cmd)
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if ret != 0:
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logging.error(f"Failed to decode aac file with retcode {ret}")
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logging.error("Please check your ffmpeg installation.")
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return False
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return True
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def convert_audio_and_make_label(input_dir, subset, output_dir, output_file):
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"""Optionally convert AAC to WAV and make speaker labels.
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Args:
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input_dir: the directory which holds the input dataset.
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subset: the name of the specified subset. e.g. vox1_dev_wav
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output_dir: the directory to place the newly generated csv files.
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output_file: the name of the newly generated csv file. e.g. vox1_dev_wav.csv
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"""
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logging.info("Preprocessing audio and label for subset %s" % subset)
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source_dir = os.path.join(input_dir, subset)
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files = []
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# Convert all AAC file into WAV format. At the same time, generate the csv
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for root, _, filenames in os.walk(source_dir):
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for filename in filenames:
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name, ext = os.path.splitext(filename)
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if ext.lower() == ".wav":
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_, ext2 = os.path.splitext(name)
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if ext2:
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continue
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wav_file = os.path.join(root, filename)
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elif ext.lower() == ".m4a":
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# Convert AAC to WAV.
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aac_file = os.path.join(root, filename)
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wav_file = aac_file + ".wav"
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if not os.path.exists(wav_file):
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if not decode_aac_with_ffmpeg(aac_file, wav_file):
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raise RuntimeError("Audio decoding failed.")
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else:
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continue
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speaker_name = root.split(os.path.sep)[-2]
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if speaker_name not in speaker_id_dict:
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num = len(speaker_id_dict)
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speaker_id_dict[speaker_name] = num
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# wav_filesize = os.path.getsize(wav_file)
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wav_length = len(sf.read(wav_file)[0])
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files.append((os.path.abspath(wav_file), wav_length, speaker_id_dict[speaker_name], speaker_name))
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# Write to CSV file which contains four columns:
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# "wav_filename", "wav_length_ms", "speaker_id", "speaker_name".
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csv_file_path = os.path.join(output_dir, output_file)
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df = pandas.DataFrame(data=files, columns=["wav_filename", "wav_length_ms", "speaker_id", "speaker_name"])
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df.to_csv(csv_file_path, index=False, sep="\t")
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logging.info("Successfully generated csv file {}".format(csv_file_path))
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def processor(directory, subset, force_process):
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"""download and process"""
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urls = SUBSETS
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if subset not in urls:
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raise ValueError(subset, "is not in voxceleb")
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subset_csv = os.path.join(directory, subset + ".csv")
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if not force_process and os.path.exists(subset_csv):
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return subset_csv
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logging.info("Downloading and process the voxceleb in %s", directory)
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logging.info("Preparing subset %s", subset)
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download_and_extract(directory, subset, urls[subset])
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convert_audio_and_make_label(directory, subset, directory, subset + ".csv")
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logging.info("Finished downloading and processing")
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return subset_csv
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if __name__ == "__main__":
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logging.set_verbosity(logging.INFO)
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if len(sys.argv) != 4:
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print("Usage: python prepare_data.py save_directory user password")
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sys.exit()
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DIR, USER["user"], USER["password"] = sys.argv[1], sys.argv[2], sys.argv[3]
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for SUBSET in SUBSETS:
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processor(DIR, SUBSET, False)
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