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Running
on
Zero
Delete dataloader/misc.py
Browse files- dataloader/misc.py +0 -109
dataloader/misc.py
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#!/usr/bin/env python -u
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# -*- coding: utf-8 -*-
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import torch
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import torch.nn as nn
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import numpy as np
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import os
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import sys
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import librosa
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import mimetypes
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def get_file_extension(file_path):
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"""
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Return an audio file extension
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"""
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_, ext = os.path.splitext(file_path)
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return ext
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def is_audio_file(file_path):
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"""
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Check if the given file_path is an audio file
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Return True if it is an audio file, otherwise, return False
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"""
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file_ext = ["wav", "aac", "ac3", "aiff", "flac", "m4a", "mp3", "ogg", "opus", "wma", "webm"]
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ext = get_file_extension(file_path)
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if ext.replace('.','') in file_ext:
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return True
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mime_type, _ = mimetypes.guess_type(file_path)
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if mime_type and mime_type.startswith('audio'):
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return True
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return False
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def read_and_config_file(args, input_path, decode=0):
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"""
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Reads and processes the input file or directory to extract audio file paths or configuration data.
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Parameters:
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args: The args
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input_path (str): Path to a file or directory containing audio data or file paths.
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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.
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If False (decode=0) for training, assume the input file contains lines with paths to audio files.
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Returns:
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processed_list (list): A list of processed file paths or a list of dictionaries containing input
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and optional condition audio paths.
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"""
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processed_list = [] # Initialize list to hold processed file paths or configurations
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#The supported audio types are listed below (tested), but not limited to.
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file_ext = ["wav", "aac", "ac3", "aiff", "flac", "m4a", "mp3", "ogg", "opus", "wma", "webm"]
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if decode:
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if args.task == 'target_speaker_extraction':
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if args.network_reference.cue== 'lip':
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# If decode is True, find video files in a directory or single file
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if os.path.isdir(input_path):
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# Find all .mp4 , mov .avi files in the input directory
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processed_list = librosa.util.find_files(input_path, ext="mp4")
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processed_list += librosa.util.find_files(input_path, ext="avi")
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processed_list += librosa.util.find_files(input_path, ext="mov")
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processed_list += librosa.util.find_files(input_path, ext="MOV")
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processed_list += librosa.util.find_files(input_path, ext="webm")
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else:
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# If it's a single file and it's a .wav or .flac, add to processed list
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if input_path.lower().endswith(".mp4") or input_path.lower().endswith(".avi") or input_path.lower().endswith(".mov") or input_path.lower().endswith(".webm"):
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processed_list.append(input_path)
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else:
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# Read file paths from the input text file (one path per line)
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with open(input_path) as fid:
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for line in fid:
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path_s = line.strip().split() # Split paths (space-separated)
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processed_list.append(path_s[0]) # Add the first path (input audio path)
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return processed_list
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# If decode is True, find audio files in a directory or single file
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if os.path.isdir(input_path):
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# Find all .wav files in the input directory
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processed_list = librosa.util.find_files(input_path, ext=file_ext)
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else:
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# If it's a single file and it's a .wav or .flac, add to processed list
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#if input_path.lower().endswith(".wav") or input_path.lower().endswith(".flac"):
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if is_audio_file(input_path):
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processed_list.append(input_path)
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else:
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# Read file paths from the input text file (one path per line)
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with open(input_path) as fid:
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for line in fid:
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path_s = line.strip().split() # Split paths (space-separated)
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processed_list.append(path_s[0]) # Add the first path (input audio path)
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return processed_list
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# If decode is False, treat the input file as a configuration file
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with open(input_path) as fid:
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for line in fid:
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tmp_paths = line.strip().split() # Split paths (space-separated)
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if len(tmp_paths) == 2:
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# If two paths per line, treat the second as 'condition_audio'
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sample = {'inputs': tmp_paths[0], 'condition_audio': tmp_paths[1]}
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elif len(tmp_paths) == 1:
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# If only one path per line, treat it as 'inputs'
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sample = {'inputs': tmp_paths[0]}
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processed_list.append(sample) # Append processed sample to list
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return processed_list
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