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bug修复

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Downupanddownup 2024-04-26 22:55:09 +08:00
parent d1e92edc7c
commit 2a23f95f61
4 changed files with 44 additions and 52 deletions
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5
Ref_Audio_Selector/common/common.py
View File

@ -1,5 +1,4 @@
from tools import my_utils
import Ref_Audio_Selector.config_param.log_config as log_config
import os
@ -102,9 +101,9 @@ def write_text_to_file(text, output_file_path):
with open(output_file_path, 'w', encoding='utf-8') as file:
file.write(text)
except IOError as e:
log_config.logger.info(f"Error occurred while writing to the file: {e}")
print(f"Error occurred while writing to the file: {e}")
else:
log_config.logger.info(f"Text successfully written to file: {output_file_path}")
print(f"Text successfully written to file: {output_file_path}")
def check_path_existence_and_return(path):

27
Ref_Audio_Selector/ref_audio_selector_webui.py
View File

@ -90,8 +90,9 @@ def start_similarity_analysis(work_space_dir, sample_dir, base_voice_path, need_
p_similarity = Popen(cmd, shell=True)
p_similarity.wait()
similarity_list = audio_similarity.parse_similarity_file(similarity_file)
if need_similarity_output:
similarity_list = audio_similarity.parse_similarity_file(similarity_file)
similarity_file_dir = os.path.join(similarity_dir, base_voice_file_name)
audio_similarity.copy_and_move(similarity_file_dir, similarity_list)
@ -122,11 +123,9 @@ def sample(text_work_space_dir, text_role, text_sample_dir, text_base_voice_path
ref_audio_dir = os.path.join(base_role_dir, params.reference_audio_dir)
time_consuming, similarity_list, _, _ = (
time_util.time_monitor(start_similarity_analysis)(base_role_dir,
text_sample_dir,
text_base_voice_path,
checkbox_similarity_output))
time_consuming, (similarity_list, _, _) \
= time_util.time_monitor(start_similarity_analysis)(base_role_dir, text_sample_dir, text_base_voice_path,
checkbox_similarity_output)
text_sample_info = f"耗时：{time_consuming:0.1f}秒；抽样成功：生成目录{ref_audio_dir}"
@ -197,7 +196,7 @@ def model_inference(text_work_space_dir, text_role, text_model_inference_voice_d
logger.error("发生异常: \n%s", traceback.format_exc())
text_model_inference_info = f"发生异常：{e}"
text_asr_audio_dir = ''
return i18n(text_model_inference_info), text_asr_audio_dir, text_asr_audio_dir
return i18n(text_model_inference_info), text_asr_audio_dir, inference_dir
# 对推理生成音频执行asr
@ -325,7 +324,7 @@ def similarity_audio_output(text_work_space_dir, text_role, text_base_audio_path
if text_compare_audio_dir is None or text_compare_audio_dir == '':
raise Exception("待分析的音频所在目录不能为空")
time_consuming, similarity_list, similarity_file, similarity_file_dir \
time_consuming, (similarity_list, similarity_file, similarity_file_dir) \
= time_util.time_monitor(start_similarity_analysis)(base_role_dir,
text_compare_audio_dir, text_base_audio_path, True)
@ -356,13 +355,13 @@ def sync_ref_audio(text_work_space_dir, text_role, 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")
time_consuming, delete_text_wav_num, delete_emotion_dir_num \
time_consuming, (delete_text_wav_num, delete_emotion_dir_num) \
= time_util.time_monitor(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"耗时：{time_consuming:0.1f}秒；推理音频目录{text_sync_inference_audio_dir}下，"
f"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")
f"text目录删除了{delete_text_wav_num}个推理音频，emotion目录下，删除了{delete_emotion_dir_num}个目录")
except Exception as e:
logger.error("发生异常: \n%s", traceback.format_exc())
text_sync_ref_audio_info = f"发生异常：{e}"
@ -462,7 +461,7 @@ with gr.Blocks() as app:
text_role = gr.Text(label=i18n("角色名称"), value=default_role)
text_work_space_dir.input(save_work_dir, [text_work_space_dir, text_role], [text_role])
text_role.input(save_role, [text_role], [])
with gr.Accordion(label=i18n("第一步：基于训练素材，生成待选参考音频列表"), open=False):
with gr.Tab(label=i18n("第一步：基于训练素材，生成待选参考音频列表"), open=False):
gr.Markdown(value=i18n("1.1：选择list文件，并提取3-10秒的素材作为参考候选"))
text_list_input = gr.Text(label=i18n("请输入list文件路径"), value="")
with gr.Row():
@ -482,7 +481,7 @@ with gr.Blocks() as app:
with gr.Row():
button_sample = gr.Button(i18n("开始分段随机抽样"), variant="primary")
text_sample_info = gr.Text(label=i18n("分段随机抽样结果"), value="", interactive=False)
with gr.Accordion(label=i18n("第二步：基于参考音频和测试文本，执行批量推理"), open=False):
with gr.Tab(label=i18n("第二步：基于参考音频和测试文本，执行批量推理"), open=False):
gr.Markdown(value=i18n("2.1：配置推理服务参数信息，参考音频路径/文本和角色情绪二选一，如果是角色情绪，需要先执行第四步，"
"将参考音频打包配置到推理服务下，在推理前，请确认完整请求地址是否与正常使用时的一致，包括角色名称，尤其是文本分隔符是否正确"))
default_model_inference_voice_dir = common.check_path_existence_and_return(
@ -521,7 +520,7 @@ with gr.Blocks() as app:
with gr.Row():
button_model_inference = gr.Button(i18n("开启批量推理"), variant="primary")
text_model_inference_info = gr.Text(label=i18n("批量推理结果"), value="", interactive=False)
with gr.Accordion(label=i18n("第三步：进行参考音频效果校验与筛选"), open=False):
with gr.Tab(label=i18n("第三步：进行参考音频效果校验与筛选"), open=False):
gr.Markdown(value=i18n("3.1：启动asr，获取推理音频文本"))
default_asr_audio_dir = common.check_path_existence_and_return(
os.path.join(default_base_dir, params.inference_audio_dir, params.inference_audio_text_aggregation_dir))
@ -587,7 +586,7 @@ with gr.Blocks() as app:
text_sync_ref_info = gr.Text(label=i18n("同步结果"), value="", interactive=False)
button_sync_ref_audio.click(sync_ref_audio, [text_work_space_dir, text_role, text_sync_ref_audio_dir,
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):
with gr.Tab("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 = params.default_template_path
default_template_content = common.read_file(default_template_path)

60
Ref_Audio_Selector/tool/delete_inference_with_ref.py
View File

@ -7,46 +7,40 @@ from Ref_Audio_Selector.config_param.log_config import logger
def remove_matching_audio_files_in_text_dir(text_dir, emotions_list):
count = 0
emotions = [item['emotion'] for item in emotions_list]
for root, dirs, files in os.walk(text_dir):
for emotion_dict in emotions_list:
emotion_tag = emotion_dict['emotion']
wav_file_name = f"{emotion_tag}.wav"
file_path = os.path.join(root, wav_file_name)
if not os.path.exists(file_path):
logger.info(f"Deleting file: {file_path}")
try:
os.remove(file_path)
count += 1
except Exception as e:
logger.error(f"Error deleting file {file_path}: {e}")
for file in files:
if file.endswith(".wav"):
emotion_tag = os.path.basename(file)[:-4]
if emotion_tag not in emotions:
file_path = os.path.join(root, file)
logger.info(f"Deleting file: {file_path}")
try:
os.remove(file_path)
count += 1
except Exception as e:
logger.error(f"Error deleting file {file_path}: {e}")
return count
def delete_emotion_subdirectories(emotion_dir, emotions_list):
"""
根据给定的情绪数组，删除emotion目录下对应情绪标签的子目录。
参数:
emotions_list (List[Dict]): 每个字典包含'emotion'字段。
base_dir (str): 子目录所在的基础目录，默认为'emotion')。
返回:
None
"""
count = 0
for emotion_dict in emotions_list:
emotion_folder = emotion_dict['emotion']
folder_path = os.path.join(emotion_dir, emotion_folder)
# 检查emotion子目录是否存在
if not os.path.isdir(folder_path):
logger.info(f"Deleting directory: {folder_path}")
try:
# 使用shutil.rmtree删除整个子目录及其内容
shutil.rmtree(folder_path)
count += 1
except Exception as e:
logger.error(f"Error deleting directory {folder_path}: {e}")
emotions = [item['emotion'] for item in emotions_list]
for entry in os.listdir(emotion_dir):
entry_path = os.path.join(emotion_dir, entry)
if os.path.isdir(entry_path):
if entry not in emotions:
logger.info(f"Deleting directory: {entry_path}")
try:
# 使用shutil.rmtree删除整个子目录及其内容
shutil.rmtree(entry_path)
count += 1
except Exception as e:
logger.error(f"Error deleting directory {entry_path}: {e}")
return count

4
Ref_Audio_Selector/tool/speaker_verification/voice_similarity.py
View File

@ -4,8 +4,8 @@ import torchaudio
import torchaudio.transforms as T
import platform
import Ref_Audio_Selector.config_param.config_params as params
import Ref_Audio_Selector.config_param.log_config as log_config
from Ref_Audio_Selector.common.time_util import timeit_decorator
from Ref_Audio_Selector.config_param.log_config import logger
from modelscope.pipelines import pipeline
@ -46,7 +46,7 @@ def compare_audio_and_generate_report(reference_audio_path, comparison_dir_path,
'path': audio_path
})
has_processed_count += 1
logger.info(f'进度：{has_processed_count}/{all_count}')
log_config.logger.info(f'进度：{has_processed_count}/{all_count}')
# Step 3: 根据相似度分数降序排列
similarity_scores.sort(key=lambda x: x['score'], reverse=True)