添加配置文件管理

Ref_Audio_Selector/config.ini

@@ -0,0 +1,45 @@
+# config.ini
+
+[Base]
+# 工作目录
+work_dir =
+# 角色
+role =
+# 参考音频目录
+reference_audio_dir = refer_audio
+
+[AudioSample]
+# list转换待选参考音频目录
+list_to_convert_reference_audio_dir = refer_audio_all
+# 音频相似度目录
+audio_similarity_dir = similarity
+
+[Inference]
+# 默认测试文本位置
+default_test_text_path = Ref_Audio_Selector/file/test_content/test_content.txt
+# 推理音频目录
+inference_audio_dir = inference_audio
+# 推理音频文本聚合目录
+inference_audio_text_aggregation_dir = text
+# 推理音频情绪聚合目录
+inference_audio_emotion_aggregation_dir = emotion
+
+[ResultCheck]
+# asr输出文件
+asr_filename = asr
+# 文本相似度输出目录
+text_similarity_output_dir = text_similarity
+# 文本情绪平均相似度报告文件名
+text_emotion_average_similarity_report_filename = average_similarity
+# 文本相似度按情绪聚合明细文件名
+text_similarity_by_emotion_detail_filename = emotion_group_detail
+# 文本相似度按文本聚合明细文件名
+text_similarity_by_text_detail_filename = text_group_detail
+
+[AudioConfig]
+# 默认模板文件位置
+default_template_path = Ref_Audio_Selector/file/config_template/ref_audio_template.txt
+# 参考音频配置文件名
+reference_audio_config_filename = refer_audio
+
+[Other]

Ref_Audio_Selector/config/config_manager.py

@@ -0,0 +1,67 @@
+import configparser
+import re
+
+
+class ConfigManager:
+    def __init__(self):
+        self.config_path = 'Ref_Audio_Selector/config.ini'
+        self.comments = []
+        self.config = None
+        self.read_with_comments()
+
+    def read_with_comments(self):
+        with open(self.config_path, 'r', encoding='utf-8') as f:
+            lines = f.readlines()
+
+            self.comments = []
+            for i, line in enumerate(lines):
+                if line.startswith(';') or line.startswith('#'):
+                    self.comments.append((i, line))
+
+            self.config = configparser.ConfigParser()
+            self.config.read_string(''.join(lines))
+
+    def write_with_comments(self):
+        output_lines = []
+
+        # 先写入配置项
+        config_str = self.config.write()
+        output_lines.extend(config_str.splitlines(True))  # 保持换行
+
+        # 然后插入原有注释
+        for index, comment in sorted(self.comments, reverse=True):  # 从后往前插入，避免行号错乱
+            while len(output_lines) < index + 1:
+                output_lines.append('\n')  # 补充空行
+            output_lines.insert(index, comment)
+
+        with open(self.config_path, 'w', encoding='utf-8') as f:
+            f.writelines(output_lines)
+
+    def get_base(self, key):
+        return self.config.get('Base', key)
+
+    def set_base(self, key, value):
+        self.config.set('Base', key, value)
+        self.write_with_comments()
+
+    def get_audio_sample(self, key):
+        return self.config.get('AudioSample', key)
+
+    def get_inference(self, key):
+        return self.config.get('Inference', key)
+
+    def get_result_check(self, key):
+        return self.config.get('ResultCheck', key)
+
+    def get_audio_config(self, key):
+        return self.config.get('AudioConfig', key)
+
+    def get_other(self, key):
+        return self.config.get('Other', key)
+
+
+_config = ConfigManager()
+
+
+def get_config():
+    return _config

Ref_Audio_Selector/ref_audio_selector_webui.py

@@ -8,6 +8,7 @@ import Ref_Audio_Selector.tool.audio_inference as audio_inference
 import Ref_Audio_Selector.tool.audio_config as audio_config
 import Ref_Audio_Selector.tool.delete_inference_with_ref as delete_inference_with_ref
 import Ref_Audio_Selector.common.common as common
+import Ref_Audio_Selector.config.config_manager as config_manager
 from tools.i18n.i18n import I18nAuto
 from config import python_exec, is_half
 from tools import my_utils
@@ -15,6 +16,7 @@ from tools.asr.config import asr_dict
 from subprocess import Popen
 
 i18n = I18nAuto()
+config = config_manager.get_config()
 
 p_similarity = None
 p_asr = None
@@ -29,7 +31,8 @@ def check_base_info(text_work_space_dir):
 
 # 从list文件，提取参考音频
 def convert_from_list(text_work_space_dir, text_list_input):
-    ref_audio_all = os.path.join(text_work_space_dir, 'refer_audio_all')
+    ref_audio_all = os.path.join(text_work_space_dir,
+                                 config.get_audio_sample('list_to_convert_reference_audio_dir'))
     text_convert_from_list_info = f"转换成功：生成目录{ref_audio_all}"
     text_sample_dir = ref_audio_all
     try:
@@ -48,7 +51,7 @@ def start_similarity_analysis(work_space_dir, sample_dir, base_voice_path, need_
     similarity_list = None
     similarity_file_dir = None
 
-    similarity_dir = os.path.join(work_space_dir, 'similarity')
+    similarity_dir = os.path.join(work_space_dir, config.get_audio_sample('audio_similarity_dir'))
     os.makedirs(similarity_dir, exist_ok=True)
 
     base_voice_file_name = common.get_filename_without_extension(base_voice_path)
@@ -79,7 +82,7 @@ def start_similarity_analysis(work_space_dir, sample_dir, base_voice_path, need_
 # 基于一个基准音频，从参考音频目录中进行分段抽样
 def sample(text_work_space_dir, text_sample_dir, text_base_voice_path,
            text_subsection_num, text_sample_num, checkbox_similarity_output):
-    ref_audio_dir = os.path.join(text_work_space_dir, 'refer_audio')
+    ref_audio_dir = os.path.join(text_work_space_dir, config.get_base('reference_audio_dir'))
     text_sample_info = f"抽样成功：生成目录{ref_audio_dir}"
     try:
         check_base_info(text_work_space_dir)
@@ -114,8 +117,9 @@ def sample(text_work_space_dir, text_sample_dir, text_base_voice_path,
 def model_inference(text_work_space_dir, text_model_inference_voice_dir, text_url,
                     text_text, text_ref_path, text_ref_text, text_emotion,
                     text_test_content):
-    inference_dir = os.path.join(text_work_space_dir, 'inference_audio')
+    inference_dir = os.path.join(text_work_space_dir, config.get_inference('inference_audio_dir'))
-    text_asr_audio_dir = os.path.join(inference_dir, 'text')
+    text_asr_audio_dir = os.path.join(inference_dir, 
+                                      config.get_inference('inference_audio_text_aggregation_dir'))
     text_model_inference_info = f"推理成功：生成目录{inference_dir}"
     try:
         check_base_info(text_work_space_dir)
@@ -164,7 +168,7 @@ def asr(text_work_space_dir, text_asr_audio_dir, dropdown_asr_model,
         if dropdown_asr_lang is None or dropdown_asr_lang == '':
             raise Exception("asr语言不能为空")
         asr_file = open_asr(text_asr_audio_dir, text_work_space_dir, dropdown_asr_model, dropdown_asr_size,
-                                      dropdown_asr_lang)
+                            dropdown_asr_lang)
         text_text_similarity_analysis_path = asr_file
         text_asr_info = f"asr成功：生成文件{asr_file}"
     except Exception as e:
@@ -198,7 +202,7 @@ def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
         output_dir_abs = os.path.abspath(asr_opt_dir)
         output_file_name = os.path.basename(asr_inp_dir)
         # 构造输出文件路径
-        output_file_path = os.path.join(output_dir_abs, f'{output_file_name}_asr.list')
+        output_file_path = os.path.join(output_dir_abs, f'{config.get_result_check("asr_filename")}.list')
         return output_file_path
 
     else:
@@ -208,7 +212,7 @@ def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
 # 对asr生成的文件，与原本的文本内容，进行相似度分析
 def text_similarity_analysis(text_work_space_dir,
                              text_text_similarity_analysis_path):
-    similarity_dir = os.path.join(text_work_space_dir, 'text_similarity')
+    similarity_dir = os.path.join(text_work_space_dir, config.get_result_check('text_similarity_output_dir'))
     text_text_similarity_analysis_info = f"相似度分析成功：生成目录{similarity_dir}"
     try:
         check_base_info(text_work_space_dir)
@@ -243,7 +247,7 @@ def open_text_similarity_analysis(asr_file_path, output_dir, similarity_enlarge_
 # 根据一个参考音频，对指定目录下的音频进行相似度分析，并输出到另一个目录
 def similarity_audio_output(text_work_space_dir, text_base_audio_path,
                             text_compare_audio_dir):
-    text_similarity_audio_output_info = "相似度分析成功：生成目录XXX"
+    text_similarity_audio_output_info = None
     try:
         check_base_info(text_work_space_dir)
         if text_base_audio_path is None or text_base_audio_path == '':
@@ -274,7 +278,8 @@ def sync_ref_audio(text_work_space_dir, text_sync_ref_audio_dir,
             raise Exception("参考音频目录不能为空")
         if text_sync_inference_audio_dir is None or text_sync_inference_audio_dir == '':
             raise Exception("推理生成的音频目录不能为空")
-        delete_text_wav_num, delete_emotion_dir_num = delete_inference_with_ref.sync_ref_audio(text_sync_ref_audio_dir, text_sync_inference_audio_dir)
+        delete_text_wav_num, delete_emotion_dir_num = delete_inference_with_ref.sync_ref_audio(text_sync_ref_audio_dir,
+                                                                                               text_sync_inference_audio_dir)
         text_sync_ref_audio_info = f"推理音频目录{text_sync_inference_audio_dir}下，text目录删除了{delete_text_wav_num}个参考音频，emotion目录下，删除了{delete_emotion_dir_num}个目录"
     except Exception as e:
         traceback.print_exc()
@@ -284,7 +289,7 @@ def sync_ref_audio(text_work_space_dir, text_sync_ref_audio_dir,
 
 # 根据模板和参考音频目录，生成参考音频配置内容
 def create_config(text_work_space_dir, text_template, text_sync_ref_audio_dir2):
-    config_file = os.path.join(text_work_space_dir, 'refer_audio.json')
+    config_file = os.path.join(text_work_space_dir, f'{config.get_audio_config("reference_audio_config_filename")}.json')
     text_create_config_info = f"配置生成成功：生成文件{config_file}"
     try:
         check_base_info(text_work_space_dir)
@@ -293,7 +298,8 @@ def create_config(text_work_space_dir, text_template, text_sync_ref_audio_dir2):
         if text_sync_ref_audio_dir2 is None or text_sync_ref_audio_dir2 == '':
             raise Exception("参考音频目录不能为空")
         ref_audio_manager = common.RefAudioListManager(text_sync_ref_audio_dir2)
-        audio_config.generate_audio_config(text_work_space_dir, text_template, ref_audio_manager.get_ref_audio_list(), config_file)
+        audio_config.generate_audio_config(text_work_space_dir, text_template, ref_audio_manager.get_ref_audio_list(),
+                                           config_file)
     except Exception as e:
         traceback.print_exc()
         text_create_config_info = f"发生异常：{e}"
@@ -353,7 +359,7 @@ with gr.Blocks() as app:
         text_emotion.input(whole_url, [text_url, text_text, text_ref_path, text_ref_text, text_emotion],
                            [text_whole_url])
         gr.Markdown(value=i18n("2.2：配置待推理文本，一句一行，不要太多，10条即可"))
-        default_test_content_path = 'Ref_Audio_Selector/tool/test_content/test_content.txt'
+        default_test_content_path = config.get_inference('default_test_text_path')
         text_test_content = gr.Text(label=i18n("请输入待推理文本路径"), value=default_test_content_path)
         gr.Markdown(value=i18n("2.3：启动推理服务，如果还没启动的话"))
         gr.Markdown(value=i18n("2.4：开始批量推理，这个过程比较耗时，可以去干点别的"))
@@ -421,7 +427,7 @@ with gr.Blocks() as app:
                                                          text_sync_inference_audio_dir], [text_sync_ref_info])
     with gr.Accordion("第四步：生成参考音频配置文本", open=False):
         gr.Markdown(value=i18n("4.1：编辑模板"))
-        default_template_path = 'Ref_Audio_Selector/tool/config_template/ref_audio_template.txt'
+        default_template_path = config.get_audio_config('default_template_path')
         default_template_content = common.read_file(default_template_path)
         text_template_path = gr.Text(label=i18n("模板文件路径"), value=default_template_path, interactive=False)
         text_template = gr.Text(label=i18n("模板内容"), value=default_template_content, lines=10)

Ref_Audio_Selector/tool/asr/funasr_asr_multi_level_dir.py

@@ -3,9 +3,10 @@
 import argparse
 import os
 import traceback
+import Ref_Audio_Selector.config.config_manager as config_manager
 from tqdm import tqdm
-
 from funasr import AutoModel
+config = config_manager.get_config()
 
 path_asr = 'tools/asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'
 path_vad = 'tools/asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch'
@@ -84,7 +85,7 @@ def execute_asr_multi_level_dir(input_folder, output_folder, model_size, languag
     os.makedirs(output_dir_abs, exist_ok=True)
 
     # 构造输出文件路径
-    output_file_path = os.path.join(output_dir_abs, f'{output_file_name}_asr.list')
+    output_file_path = os.path.join(output_dir_abs, f'{config.get_result_check("asr_filename")}.list')
 
     # 将输出写入文件
     with open(output_file_path, "w", encoding="utf-8") as f:

Ref_Audio_Selector/tool/audio_inference.py

@@ -1,8 +1,11 @@
 import os
 import requests
 import itertools
+import Ref_Audio_Selector.config.config_manager as config_manager
 from urllib.parse import urlparse, parse_qs, urlencode, urlunparse, quote
 
+config = config_manager.get_config()
+
 
 class URLComposer:
     def __init__(self, base_url, emotion_param_name, text_param_name, ref_path_param_name, ref_text_param_name):
@@ -78,9 +81,9 @@ def generate_audio_files(url_composer, text_list, emotion_list, output_dir_path)
     os.makedirs(output_dir, exist_ok=True)
 
     # Create subdirectories for text and emotion categories
-    text_subdir = os.path.join(output_dir, 'text')
+    text_subdir = os.path.join(output_dir, config.get_inference('inference_audio_text_aggregation_dir'))
     os.makedirs(text_subdir, exist_ok=True)
-    emotion_subdir = os.path.join(output_dir, 'emotion')
+    emotion_subdir = os.path.join(output_dir, config.get_inference('inference_audio_emotion_aggregation_dir'))
     os.makedirs(emotion_subdir, exist_ok=True)
 
     # 计算笛卡尔积

Ref_Audio_Selector/tool/delete_inference_with_ref.py

@@ -1,7 +1,9 @@
 import os
 import shutil
 import Ref_Audio_Selector.common.common as common
+import Ref_Audio_Selector.config.config_manager as config_manager
 
+config = config_manager.get_config()
 
 def remove_matching_audio_files_in_text_dir(text_dir, emotions_list):
     count = 0
@@ -51,8 +53,8 @@ def delete_emotion_subdirectories(emotion_dir, emotions_list):
 def sync_ref_audio(ref_audio_dir, inference_audio_dir):
     ref_audio_manager = common.RefAudioListManager(ref_audio_dir)
     ref_list = ref_audio_manager.get_ref_audio_list()
-    text_dir = os.path.join(inference_audio_dir, 'text')
+    text_dir = os.path.join(inference_audio_dir, config.get_inference('inference_audio_text_aggregation_dir'))
-    emotion_dir = os.path.join(inference_audio_dir, 'emotion')
+    emotion_dir = os.path.join(inference_audio_dir, config.get_inference('inference_audio_emotion_aggregation_dir'))
     delete_text_wav_num = remove_matching_audio_files_in_text_dir(text_dir, ref_list)
     delete_emotion_dir_num = delete_emotion_subdirectories(emotion_dir, ref_list)
     return delete_text_wav_num, delete_emotion_dir_num

Ref_Audio_Selector/tool/speaker_verification/voice_similarity.py

@@ -2,6 +2,7 @@ import argparse
 import os
 
 from modelscope.pipelines import pipeline
+
 sv_pipeline = pipeline(
     task='speaker-verification',
     model='Ref_Audio_Selector/tool/speaker_verification/models/speech_campplus_sv_zh-cn_16k-common',
@@ -11,7 +12,8 @@ sv_pipeline = pipeline(
 
 def compare_audio_and_generate_report(reference_audio_path, comparison_dir_path, output_file_path):
     # Step 1: 获取比较音频目录下所有音频文件的路径
-    comparison_audio_paths = [os.path.join(comparison_dir_path, f) for f in os.listdir(comparison_dir_path) if f.endswith('.wav')]
+    comparison_audio_paths = [os.path.join(comparison_dir_path, f) for f in os.listdir(comparison_dir_path) if
+                              f.endswith('.wav')]
 
     # Step 2: 用参考音频依次比较音频目录下的每个音频，获取相似度分数及对应路径
     similarity_scores = []
@@ -31,10 +33,10 @@ def compare_audio_and_generate_report(reference_audio_path, comparison_dir_path,
         open(output_file_path, 'w').close()  # Create an empty file
 
     # Step 5: 将排序后的结果写入输出结果文件（支持中文）
-    formatted_scores  = [f'{item["score"]}|{item["path"]}' for item in similarity_scores]
+    formatted_scores = [f'{item["score"]}|{item["path"]}' for item in similarity_scores]
     with open(output_file_path, 'w', encoding='utf-8') as f:
         # 使用'\n'将每个字符串分开，使其写入不同行
-        content = '\n'.join(formatted_scores )
+        content = '\n'.join(formatted_scores)
         f.write(content)
 
 
@@ -60,7 +62,7 @@ if __name__ == '__main__':
     cmd = parse_arguments()
     print(cmd)
     compare_audio_and_generate_report(
-        reference_audio_path  = cmd.reference_audio,
+        reference_audio_path=cmd.reference_audio,
-        comparison_dir_path = cmd.comparison_dir,
+        comparison_dir_path=cmd.comparison_dir,
-        output_file_path    = cmd.output_file,
+        output_file_path=cmd.output_file,
-    )
+    )

Ref_Audio_Selector/tool/text_comparison/asr_text_process.py

@@ -3,8 +3,11 @@ import argparse
 from collections import defaultdict
 from operator import itemgetter
 import Ref_Audio_Selector.tool.text_comparison.text_comparison as text_comparison
+import Ref_Audio_Selector.config.config_manager as config_manager
 import Ref_Audio_Selector.common.common as common
 
+config = config_manager.get_config()
+
 
 def parse_asr_file(file_path):
     output = []
@@ -96,19 +99,20 @@ def process(asr_file_path, output_dir, similarity_enlarge_boundary):
     calculate_similarity_and_append_to_list(records, similarity_enlarge_boundary)
     average_similarity_list = calculate_average_similarity_by_emotion(records)
 
-    average_similarity_file = os.path.join(output_dir, 'average_similarity.txt')
+    average_similarity_file = os.path.join(output_dir,
+                                           f'{config.get_result_check("text_emotion_average_similarity_report_filename")}.txt')
     average_similarity_content = \
         '\n'.join([f"{item['average_similarity_score']}|{item['emotion']}" for item in average_similarity_list])
     common.write_text_to_file(average_similarity_content, average_similarity_file)
 
     emotion_detail_list = group_and_sort_by_field(records, 'emotion')
 
-    emotion_detail_file = os.path.join(output_dir, 'emotion_group_detail.txt')
+    emotion_detail_file = os.path.join(output_dir, f'{config.get_result_check("emotion_group_detail")}.txt')
     format_list_to_text(emotion_detail_list, emotion_detail_file)
 
     original_text_detail_list = group_and_sort_by_field(records, 'original_text')
 
-    original_text_detail_file = os.path.join(output_dir, 'text_group_detail.txt')
+    original_text_detail_file = os.path.join(output_dir, f'{config.get_result_check("text_group_detail")}.txt')
     format_list_to_text(original_text_detail_list, original_text_detail_file)
 
     print('文本相似度分析完成。')