调整配置参数，进行集中管理

Ref_Audio_Selector/config/config_manager.py

@@ -44,4 +44,3 @@ def get_config():
 
 if __name__ == '__main__':
     print(_config.print())
-    print(_config.get_base('reference_audio_dir'))

Ref_Audio_Selector/config/config_params.py

@@ -0,0 +1,42 @@
+import Ref_Audio_Selector.config.config_manager as config_manager
+
+config = config_manager.get_config()
+
+# [Base]
+# 参考音频目录
+reference_audio_dir = config.get_base('reference_audio_dir')
+
+# [AudioSample]
+# list转换待选参考音频目录
+list_to_convert_reference_audio_dir = config.get_audio_sample('list_to_convert_reference_audio_dir')
+# 音频相似度目录
+audio_similarity_dir = config.get_audio_sample('audio_similarity_dir')
+
+# [Inference]
+# 默认测试文本位置
+default_test_text_path = config.get_inference('default_test_text_path')
+# 推理音频目录
+inference_audio_dir = config.get_inference('inference_audio_dir')
+# 推理音频文本聚合目录
+inference_audio_text_aggregation_dir = config.get_inference('inference_audio_text_aggregation_dir')
+# 推理音频情绪聚合目录
+inference_audio_emotion_aggregation_dir = config.get_inference('inference_audio_emotion_aggregation_dir')
+
+# [ResultCheck]
+# asr输出文件
+asr_filename = config.get_result_check('asr_filename')
+# 文本相似度输出目录
+text_similarity_output_dir = config.get_result_check('text_similarity_output_dir')
+# 文本情绪平均相似度报告文件名
+text_emotion_average_similarity_report_filename = config.get_result_check('text_emotion_average_similarity_report_filename')
+# 文本相似度按情绪聚合明细文件名
+text_similarity_by_emotion_detail_filename = config.get_result_check('text_similarity_by_emotion_detail_filename')
+# 文本相似度按文本聚合明细文件名
+text_similarity_by_text_detail_filename = config.get_result_check('text_similarity_by_text_detail_filename')
+
+# [AudioConfig]
+# 默认模板文件位置
+default_template_path = config.get_audio_config('default_template_path')
+# 参考音频配置文件名
+reference_audio_config_filename = config.get_audio_config('reference_audio_config_filename')
+

Ref_Audio_Selector/ref_audio_selector_webui.py

@@ -8,7 +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
+import Ref_Audio_Selector.config.config_params as params
 from tools.i18n.i18n import I18nAuto
 from config import python_exec, is_half
 from tools import my_utils
@@ -16,7 +16,6 @@ from tools.asr.config import asr_dict
 from subprocess import Popen
 
 i18n = I18nAuto()
-config = config_manager.get_config()
 
 p_similarity = None
 p_asr = None
@@ -32,7 +31,7 @@ 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,
-                                 config.get_audio_sample('list_to_convert_reference_audio_dir'))
+                                 params.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:
@@ -51,7 +50,7 @@ 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, config.get_audio_sample('audio_similarity_dir'))
+    similarity_dir = os.path.join(work_space_dir, params.audio_similarity_dir)
     os.makedirs(similarity_dir, exist_ok=True)
 
     base_voice_file_name = common.get_filename_without_extension(base_voice_path)
@@ -82,7 +81,7 @@ 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, config.get_base('reference_audio_dir'))
+    ref_audio_dir = os.path.join(text_work_space_dir, params.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)
@@ -117,9 +116,9 @@ 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, config.get_inference('inference_audio_dir'))
+    inference_dir = os.path.join(text_work_space_dir, params.inference_audio_dir)
-    text_asr_audio_dir = os.path.join(inference_dir, 
+    text_asr_audio_dir = os.path.join(inference_dir,
-                                      config.get_inference('inference_audio_text_aggregation_dir'))
+                                      params.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)
@@ -202,7 +201,7 @@ 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'{config.get_result_check("asr_filename")}.list')
+        output_file_path = os.path.join(output_dir_abs, f'{params.asr_filename}.list')
         return output_file_path
 
     else:
@@ -212,7 +211,7 @@ 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, config.get_result_check('text_similarity_output_dir'))
+    similarity_dir = os.path.join(text_work_space_dir, params.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)
@@ -289,7 +288,7 @@ 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, f'{config.get_audio_config("reference_audio_config_filename")}.json')
+    config_file = os.path.join(text_work_space_dir, f'{params.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)
@@ -359,7 +358,7 @@ 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 = config.get_inference('default_test_text_path')
+        default_test_content_path = params.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"))
@@ -427,7 +426,7 @@ 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 = config.get_audio_config('default_template_path')
+        default_template_path = params.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

@@ -3,10 +3,9 @@
 import argparse
 import os
 import traceback
-import Ref_Audio_Selector.config.config_manager as config_manager
+import Ref_Audio_Selector.config.config_params as params
 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'
@@ -85,7 +84,7 @@ 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'{config.get_result_check("asr_filename")}.list')
+    output_file_path = os.path.join(output_dir_abs, f'{params.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

@@ -1,11 +1,9 @@
 import os
 import requests
 import itertools
-import Ref_Audio_Selector.config.config_manager as config_manager
+import Ref_Audio_Selector.config.config_params as params
 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):
@@ -80,9 +78,9 @@ 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, config.get_inference('inference_audio_text_aggregation_dir'))
+    text_subdir = os.path.join(output_dir, params.inference_audio_text_aggregation_dir)
     os.makedirs(text_subdir, exist_ok=True)
-    emotion_subdir = os.path.join(output_dir, config.get_inference('inference_audio_emotion_aggregation_dir'))
+    emotion_subdir = os.path.join(output_dir, params.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

@@ -1,9 +1,8 @@
 import os
 import shutil
 import Ref_Audio_Selector.common.common as common
-import Ref_Audio_Selector.config.config_manager as config_manager
+import Ref_Audio_Selector.config.config_params as params
 
-config = config_manager.get_config()
 
 def remove_matching_audio_files_in_text_dir(text_dir, emotions_list):
     count = 0
@@ -53,8 +52,8 @@ 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, config.get_inference('inference_audio_text_aggregation_dir'))
+    text_dir = os.path.join(inference_audio_dir, params.inference_audio_text_aggregation_dir)
-    emotion_dir = os.path.join(inference_audio_dir, config.get_inference('inference_audio_emotion_aggregation_dir'))
+    emotion_dir = os.path.join(inference_audio_dir, params.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/text_comparison/asr_text_process.py

@@ -3,11 +3,9 @@ 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.config.config_params as params
 import Ref_Audio_Selector.common.common as common
 
-config = config_manager.get_config()
-
 
 def parse_asr_file(file_path):
     output = []
@@ -100,19 +98,19 @@ def process(asr_file_path, output_dir, similarity_enlarge_boundary):
     average_similarity_list = calculate_average_similarity_by_emotion(records)
 
     average_similarity_file = os.path.join(output_dir,
-                                           f'{config.get_result_check("text_emotion_average_similarity_report_filename")}.txt')
+                                           f'{params.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, f'{config.get_result_check("emotion_group_detail")}.txt')
+    emotion_detail_file = os.path.join(output_dir, f'{params.text_similarity_by_emotion_detail_filename}.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, f'{config.get_result_check("text_group_detail")}.txt')
+    original_text_detail_file = os.path.join(output_dir, f'{params.text_similarity_by_text_detail_filename}.txt')
     format_list_to_text(original_text_detail_list, original_text_detail_file)
 
     print('文本相似度分析完成。')