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Zero
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#!/usr/bin/env python -u
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import torch.nn as nn
import numpy as np
import os
import sys
import librosa
import mimetypes
def get_file_extension(file_path):
"""
Return an audio file extension
"""
_, ext = os.path.splitext(file_path)
return ext
def is_audio_file(file_path):
"""
Check if the given file_path is an audio file
Return True if it is an audio file, otherwise, return False
"""
file_ext = ["wav", "aac", "ac3", "aiff", "flac", "m4a", "mp3", "ogg", "opus", "wma", "webm"]
ext = get_file_extension(file_path)
if ext.replace('.','') in file_ext:
return True
mime_type, _ = mimetypes.guess_type(file_path)
if mime_type and mime_type.startswith('audio'):
return True
return False
def read_and_config_file(args, input_path, decode=0):
"""
Reads and processes the input file or directory to extract audio file paths or configuration data.
Parameters:
args: The args
input_path (str): Path to a file or directory containing audio data or file paths.
decode (bool): If True (decode=1) for decoding, process the input as audio files directly (find .wav or .flac files) or from a .scp file.
If False (decode=0) for training, assume the input file contains lines with paths to audio files.
Returns:
processed_list (list): A list of processed file paths or a list of dictionaries containing input
and optional condition audio paths.
"""
processed_list = [] # Initialize list to hold processed file paths or configurations
#The supported audio types are listed below (tested), but not limited to.
file_ext = ["wav", "aac", "ac3", "aiff", "flac", "m4a", "mp3", "ogg", "opus", "wma", "webm"]
if decode:
if args.task == 'target_speaker_extraction':
if args.network_reference.cue== 'lip':
# If decode is True, find video files in a directory or single file
if os.path.isdir(input_path):
# Find all .mp4 , mov .avi files in the input directory
processed_list = librosa.util.find_files(input_path, ext="mp4")
processed_list += librosa.util.find_files(input_path, ext="avi")
processed_list += librosa.util.find_files(input_path, ext="mov")
processed_list += librosa.util.find_files(input_path, ext="MOV")
processed_list += librosa.util.find_files(input_path, ext="webm")
else:
# If it's a single file and it's a .wav or .flac, add to processed list
if input_path.lower().endswith(".mp4") or input_path.lower().endswith(".avi") or input_path.lower().endswith(".mov") or input_path.lower().endswith(".webm"):
processed_list.append(input_path)
else:
# Read file paths from the input text file (one path per line)
with open(input_path) as fid:
for line in fid:
path_s = line.strip().split() # Split paths (space-separated)
processed_list.append(path_s[0]) # Add the first path (input audio path)
return processed_list
# If decode is True, find audio files in a directory or single file
if os.path.isdir(input_path):
# Find all .wav files in the input directory
processed_list = librosa.util.find_files(input_path, ext=file_ext)
else:
# If it's a single file and it's a .wav or .flac, add to processed list
#if input_path.lower().endswith(".wav") or input_path.lower().endswith(".flac"):
if is_audio_file(input_path):
processed_list.append(input_path)
else:
# Read file paths from the input text file (one path per line)
with open(input_path) as fid:
for line in fid:
path_s = line.strip().split() # Split paths (space-separated)
processed_list.append(path_s[0]) # Add the first path (input audio path)
return processed_list
# If decode is False, treat the input file as a configuration file
with open(input_path) as fid:
for line in fid:
tmp_paths = line.strip().split() # Split paths (space-separated)
if len(tmp_paths) == 2:
# If two paths per line, treat the second as 'condition_audio'
sample = {'inputs': tmp_paths[0], 'condition_audio': tmp_paths[1]}
elif len(tmp_paths) == 1:
# If only one path per line, treat it as 'inputs'
sample = {'inputs': tmp_paths[0]}
processed_list.append(sample) # Append processed sample to list
return processed_list
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