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https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-04-05 19:41:56 +08:00
1073 lines
66 KiB
Python
1073 lines
66 KiB
Python
import os.path
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import os
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import traceback
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import gradio as gr
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from Ref_Audio_Selector.config_param.log_config import logger
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import Ref_Audio_Selector.common.model_manager as model_manager
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import Ref_Audio_Selector.tool.audio_sample as audio_sample
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import Ref_Audio_Selector.tool.audio_inference as audio_inference
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import Ref_Audio_Selector.tool.audio_config as audio_config
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import Ref_Audio_Selector.tool.audio_check as audio_check
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import Ref_Audio_Selector.tool.text_check as text_check
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import Ref_Audio_Selector.common.common as common
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import Ref_Audio_Selector.config_param.config_params as params
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import Ref_Audio_Selector.common.time_util as time_util
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import Ref_Audio_Selector.ui_init.init_ui_param as init
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from tools.i18n.i18n import I18nAuto
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from config import python_exec, is_half
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from tools import my_utils
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from tools.asr.config import asr_dict
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from subprocess import Popen
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i18n = I18nAuto()
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rw_param = params.config_manager.get_rw_param()
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p_similarity = None
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p_asr = None
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p_text_similarity = None
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# 校验基础信息
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def check_base_info(text_work_space_dir, text_role):
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if text_work_space_dir is None or text_work_space_dir == '':
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raise Exception("工作目录不能为空")
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if text_role is None or text_role == '':
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raise Exception("角色不能为空")
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base_role_dir = os.path.join(text_work_space_dir, text_role)
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# 判断目录是否存在
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if not os.path.exists(base_role_dir):
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# 如果不存在，则创建目录
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os.makedirs(base_role_dir, exist_ok=True)
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return base_role_dir
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# 从list文件，提取参考音频
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def convert_from_list(text_work_space_dir, text_role, text_list_input):
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text_work_space_dir, text_list_input = common.batch_clean_paths([text_work_space_dir, text_list_input])
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text_convert_from_list_info = None
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text_sample_dir = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_list_input is None or text_list_input == '':
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raise Exception("list文件路径不能为空")
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ref_audio_all = os.path.join(base_role_dir,
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params.list_to_convert_reference_audio_dir)
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time_consuming, _ = time_util.time_monitor(audio_sample.convert_from_list)(text_list_input, ref_audio_all)
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text_convert_from_list_info = f"耗时：{time_consuming:0.1f}秒；转换成功：生成目录{ref_audio_all}"
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text_sample_dir = ref_audio_all
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_convert_from_list_info = f"发生异常：{e}"
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text_sample_dir = ''
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return i18n(text_convert_from_list_info), text_sample_dir
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def start_similarity_analysis(work_space_dir, sample_dir, speaker_verification, base_voice_path, need_similarity_output):
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similarity_list = None
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similarity_file_dir = None
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similarity_dir = os.path.join(work_space_dir, params.audio_similarity_dir)
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os.makedirs(similarity_dir, exist_ok=True)
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base_voice_file_name = common.get_filename_without_extension(base_voice_path)
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similarity_file = os.path.join(similarity_dir, f'{base_voice_file_name}.txt')
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global p_similarity
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if p_similarity is None:
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cmd = f'"{python_exec}" Ref_Audio_Selector/tool/speaker_verification/voice_similarity.py '
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cmd += f' -r "{base_voice_path}"'
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cmd += f' -c "{sample_dir}"'
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cmd += f' -o {similarity_file}'
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cmd += f' -m {speaker_verification}'
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logger.info(cmd)
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p_similarity = Popen(cmd, shell=True)
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p_similarity.wait()
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similarity_list = audio_sample.parse_similarity_file(similarity_file)
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if need_similarity_output:
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similarity_file_dir = os.path.join(similarity_dir, base_voice_file_name)
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audio_sample.copy_and_move(similarity_file_dir, similarity_list)
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p_similarity = None
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return similarity_list, similarity_file, similarity_file_dir
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else:
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return similarity_list, None, None
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# 基于一个基准音频，从参考音频目录中进行分段抽样
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def sample(text_work_space_dir, text_role, text_sample_dir, dropdown_speaker_verification, text_base_voice_path,
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slider_subsection_num, slider_sample_num, checkbox_similarity_output):
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text_work_space_dir, text_sample_dir, text_base_voice_path \
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= common.batch_clean_paths([text_work_space_dir, text_sample_dir, text_base_voice_path])
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ref_audio_dir = None
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text_sample_info = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_sample_dir is None or text_sample_dir == '':
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raise Exception("参考音频抽样目录不能为空，请先完成上一步操作")
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if text_base_voice_path is None or text_base_voice_path == '':
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raise Exception("基准音频路径不能为空")
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if slider_subsection_num is None or slider_subsection_num == '':
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raise Exception("分段数不能为空")
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if slider_sample_num is None or slider_sample_num == '':
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raise Exception("每段随机抽样个数不能为空")
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if dropdown_speaker_verification is None or dropdown_speaker_verification == '':
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raise Exception("说话人确认算法不能为空")
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ref_audio_dir = os.path.join(base_role_dir, params.reference_audio_dir)
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time_consuming, (similarity_list, _, _) \
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= time_util.time_monitor(start_similarity_analysis)(base_role_dir, text_sample_dir, dropdown_speaker_verification, text_base_voice_path,
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checkbox_similarity_output)
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text_sample_info = f"耗时：{time_consuming:0.1f}秒；抽样成功：生成目录{ref_audio_dir}"
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if similarity_list is None:
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raise Exception("相似度分析失败")
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audio_sample.sample(ref_audio_dir, similarity_list, slider_subsection_num, slider_sample_num)
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_sample_info = f"发生异常：{e}"
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ref_audio_dir = ''
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text_refer_audio_file_dir = ref_audio_dir
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return i18n(text_sample_info), text_refer_audio_file_dir
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# 根据参考音频和测试文本，执行批量推理
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def model_inference(text_work_space_dir, text_role, slider_request_concurrency_num, text_refer_audio_file_dir,
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text_url, dropdown_refer_type_param,
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text_text, text_ref_path, text_ref_text, text_emotion,
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text_test_content_dir):
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text_work_space_dir, text_refer_audio_file_dir, text_test_content_dir \
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= common.batch_clean_paths([text_work_space_dir, text_refer_audio_file_dir, text_test_content_dir])
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inference_dir = None
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text_asr_audio_dir = None
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text_model_inference_info = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_refer_audio_file_dir is None or text_refer_audio_file_dir == '':
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raise Exception("待推理的参考音频所在目录不能为空，请先完成上一步操作")
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if text_url is None or text_url == '':
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raise Exception("推理服务请求地址不能为空")
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if text_text is None or text_text == '':
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raise Exception("文本参数名不能为空")
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if text_test_content_dir is None or text_test_content_dir == '':
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raise Exception("待推理文本路径不能为空")
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if (text_ref_path is None or text_ref_path == '') and (text_ref_text is None or text_ref_text == '') and (
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text_emotion is None or text_emotion == ''):
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raise Exception("参考音频路径/文本和角色情绪二选一填写，不能全部为空")
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inference_dir = os.path.join(base_role_dir, params.inference_audio_dir)
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text_asr_audio_dir = os.path.join(inference_dir,
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params.inference_audio_text_aggregation_dir)
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url_composer = audio_inference.TTSURLComposer(text_url, dropdown_refer_type_param, text_emotion, text_text,
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text_ref_path, text_ref_text)
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url_composer.is_valid()
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text_list = common.read_text_file_to_list(text_test_content_dir)
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if text_list is None or len(text_list) == 0:
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raise Exception("待推理文本内容不能为空")
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ref_audio_manager = common.RefAudioListManager(text_refer_audio_file_dir)
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if len(ref_audio_manager.get_audio_list()) == 0:
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raise Exception("待推理的参考音频不能为空")
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time_consuming, _ = time_util.time_monitor(audio_inference.generate_audio_files_parallel)(url_composer,
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text_list,
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ref_audio_manager.get_ref_audio_list(),
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inference_dir,
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slider_request_concurrency_num)
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text_model_inference_info = f"耗时：{time_consuming:0.1f}秒；推理成功：生成目录{inference_dir}"
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_model_inference_info = f"发生异常：{e}"
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text_asr_audio_dir = ''
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return i18n(text_model_inference_info), text_asr_audio_dir, inference_dir
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# 对推理生成音频执行asr
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def asr(text_work_space_dir, text_role, text_asr_audio_dir, dropdown_asr_model,
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dropdown_asr_size, dropdown_asr_lang):
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text_work_space_dir, text_asr_audio_dir \
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= common.batch_clean_paths([text_work_space_dir, text_asr_audio_dir])
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asr_file = None
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text_text_similarity_analysis_path = None
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text_asr_info = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_asr_audio_dir is None or text_asr_audio_dir == '':
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raise Exception("待asr的音频所在目录不能为空，请先完成上一步操作")
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if dropdown_asr_model is None or dropdown_asr_model == '':
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raise Exception("asr模型不能为空")
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if dropdown_asr_size is None or dropdown_asr_size == '':
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raise Exception("asr模型大小不能为空")
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if dropdown_asr_lang is None or dropdown_asr_lang == '':
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raise Exception("asr语言不能为空")
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time_consuming, asr_file = time_util.time_monitor(open_asr)(text_asr_audio_dir, base_role_dir,
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dropdown_asr_model, dropdown_asr_size,
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dropdown_asr_lang)
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text_text_similarity_analysis_path = asr_file
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text_asr_info = f"耗时：{time_consuming:0.1f}秒；asr成功：生成文件{asr_file}"
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_asr_info = f"发生异常：{e}"
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text_text_similarity_analysis_path = ''
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return i18n(text_asr_info), text_text_similarity_analysis_path
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def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
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global p_asr
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if p_asr is None:
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asr_inp_dir = my_utils.clean_path(asr_inp_dir)
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asr_py_path = asr_dict[asr_model]["path"]
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if asr_py_path == 'funasr_asr.py':
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asr_py_path = 'funasr_asr_multi_level_dir.py'
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if asr_py_path == 'fasterwhisper.py':
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asr_py_path = 'fasterwhisper_asr_multi_level_dir.py'
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cmd = f'"{python_exec}" Ref_Audio_Selector/tool/asr/{asr_py_path} '
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cmd += f' -i "{asr_inp_dir}"'
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cmd += f' -o "{asr_opt_dir}"'
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cmd += f' -s {asr_model_size}'
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cmd += f' -l {asr_lang}'
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cmd += " -p %s" % ("float16" if is_half == True else "float32")
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logger.info(cmd)
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p_asr = Popen(cmd, shell=True)
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p_asr.wait()
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p_asr = None
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output_dir_abs = os.path.abspath(asr_opt_dir)
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output_file_name = os.path.basename(asr_inp_dir)
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# 构造输出文件路径
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output_file_path = os.path.join(output_dir_abs, f'{params.asr_filename}.list')
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return output_file_path
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else:
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return None
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# 对asr生成的文件，与原本的文本内容，进行相似度分析
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def text_similarity_analysis(text_work_space_dir, text_role, slider_text_similarity_amplification_boundary,
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text_text_similarity_analysis_path):
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text_work_space_dir, text_text_similarity_analysis_path \
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= common.batch_clean_paths([text_work_space_dir, text_text_similarity_analysis_path])
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similarity_dir = None
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text_text_similarity_analysis_info = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_text_similarity_analysis_path is None or text_text_similarity_analysis_path == '':
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raise Exception("asr生成的文件路径不能为空，请先完成上一步操作")
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similarity_dir = os.path.join(base_role_dir, params.text_similarity_output_dir)
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time_consuming, _ = time_util.time_monitor(open_text_similarity_analysis)(text_text_similarity_analysis_path,
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similarity_dir,
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slider_text_similarity_amplification_boundary)
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average_similarity_file = os.path.join(similarity_dir,
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f'{params.text_emotion_average_similarity_report_filename}.txt')
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text_text_similarity_analysis_info = f"耗时：{time_consuming:0.1f}秒；相似度分析成功：生成目录{similarity_dir}"
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_text_similarity_analysis_info = f"发生异常：{e}"
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return i18n(text_text_similarity_analysis_info), average_similarity_file
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def open_text_similarity_analysis(asr_file_path, output_dir, similarity_enlarge_boundary=0.9):
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global p_text_similarity
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if p_text_similarity is None:
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cmd = f'"{python_exec}" Ref_Audio_Selector/tool/text_comparison/asr_text_process.py '
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cmd += f' -a "{asr_file_path}"'
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cmd += f' -o "{output_dir}"'
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cmd += f' -b {similarity_enlarge_boundary}'
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logger.info(cmd)
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p_text_similarity = Popen(cmd, shell=True)
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p_text_similarity.wait()
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p_text_similarity = None
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return output_dir
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else:
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return None
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hide_voice_similarity_dir = ''
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# 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
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def similarity_audio_output(text_work_space_dir, text_role, text_base_audio_path,
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text_compare_audio_dir, dropdown_speaker_verification):
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global hide_voice_similarity_dir
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text_work_space_dir, text_base_audio_path, text_compare_audio_dir \
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= common.batch_clean_paths([text_work_space_dir, text_base_audio_path, text_compare_audio_dir])
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text_similarity_audio_output_info = None
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try:
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base_role_dir = check_base_info(text_work_space_dir, text_role)
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if text_base_audio_path is None or text_base_audio_path == '':
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raise Exception("基准音频路径不能为空")
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if text_compare_audio_dir is None or text_compare_audio_dir == '':
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raise Exception("待分析的音频所在目录不能为空")
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if dropdown_speaker_verification is None or dropdown_speaker_verification == '':
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raise Exception("说话人验证模型不能为空")
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time_consuming, (similarity_list, similarity_file, similarity_file_dir) \
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= time_util.time_monitor(start_similarity_analysis)(base_role_dir,text_compare_audio_dir,
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dropdown_speaker_verification, text_base_audio_path, True)
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if similarity_list is None:
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raise Exception("相似度分析失败")
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text_similarity_audio_output_info = f'耗时：{time_consuming:0.1f}秒；相似度分析成功：生成目录{similarity_file_dir}，文件{similarity_file}'
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hide_voice_similarity_dir = os.path.join(text_work_space_dir, params.audio_similarity_dir)
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except Exception as e:
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logger.error("发生异常: \n%s", traceback.format_exc())
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text_similarity_audio_output_info = f"发生异常：{e}"
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return i18n(text_similarity_audio_output_info)
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# 根据参考音频目录的删除情况，将其同步到推理生成的音频目录中，即参考音频目录下，删除了几个参考音频，就在推理目录下，将这些参考音频生成的音频文件移除
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def sync_ref_audio(text_work_space_dir, text_role, text_refer_audio_file_dir,
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text_inference_audio_file_dir):
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text_work_space_dir, text_refer_audio_file_dir, text_inference_audio_file_dir \
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= common.batch_clean_paths([text_work_space_dir, text_refer_audio_file_dir, text_inference_audio_file_dir])
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text_sync_ref_audio_info = None
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try:
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check_base_info(text_work_space_dir, text_role)
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if text_refer_audio_file_dir is None or text_refer_audio_file_dir == '':
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raise Exception("参考音频目录不能为空")
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if text_inference_audio_file_dir is None or text_inference_audio_file_dir == '':
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raise Exception("推理生成的音频目录不能为空")
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time_consuming, (delete_text_wav_num, delete_emotion_dir_num) \
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= time_util.time_monitor(audio_check.sync_ref_audio)(text_refer_audio_file_dir,
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text_inference_audio_file_dir)
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|
||
text_sync_ref_audio_info = (f"耗时：{time_consuming:0.1f}秒；推理音频目录{text_inference_audio_file_dir}下，"
|
||
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}"
|
||
return i18n(text_sync_ref_audio_info)
|
||
|
||
|
||
hide_config_file = ''
|
||
|
||
|
||
# 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_role, text_template, text_refer_audio_file_dir):
|
||
text_work_space_dir, text_refer_audio_file_dir \
|
||
= common.batch_clean_paths([text_work_space_dir, text_refer_audio_file_dir])
|
||
|
||
config_file = None
|
||
text_create_config_info = None
|
||
try:
|
||
base_role_dir = check_base_info(text_work_space_dir, text_role)
|
||
if text_template is None or text_template == '':
|
||
raise Exception("参考音频抽样目录不能为空")
|
||
if text_refer_audio_file_dir is None or text_refer_audio_file_dir == '':
|
||
raise Exception("参考音频目录不能为空")
|
||
config_file = os.path.join(base_role_dir, f'{params.reference_audio_config_filename}.json')
|
||
ref_audio_manager = common.RefAudioListManager(text_refer_audio_file_dir)
|
||
|
||
time_consuming, _ = time_util.time_monitor(audio_config.generate_audio_config)(base_role_dir, text_template,
|
||
ref_audio_manager.get_ref_audio_list(),
|
||
config_file)
|
||
|
||
text_create_config_info = f"耗时：{time_consuming:0.1f}秒；配置生成成功：生成文件{config_file}"
|
||
|
||
hide_config_file = config_file
|
||
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_create_config_info = f"发生异常：{e}"
|
||
return i18n(text_create_config_info)
|
||
|
||
|
||
# 基于请求路径和参数，合成完整的请求路径
|
||
def whole_url(text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text, text_emotion):
|
||
url_composer = audio_inference.TTSURLComposer(text_url, dropdown_refer_type_param, text_emotion, text_text,
|
||
text_ref_path, text_ref_text)
|
||
if url_composer.is_emotion():
|
||
text_whole_url = url_composer.build_url_with_emotion('测试内容', '情绪类型', False)
|
||
else:
|
||
text_whole_url = url_composer.build_url_with_ref('测试内容', '参考路径', '参考文本', False)
|
||
return text_whole_url
|
||
|
||
|
||
def start_api():
|
||
text_start_api_info = None
|
||
try:
|
||
proc = common.start_new_service('api.py')
|
||
text_start_api_info = "启动完成"
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_start_api_info = f"发生异常：{e}"
|
||
return text_start_api_info
|
||
|
||
|
||
def refresh_api_model():
|
||
return ({"choices": model_manager.get_gpt_model_names(), "__type__": "update"},
|
||
{"choices": model_manager.get_sovits_model_names(), "__type__": "update"})
|
||
|
||
|
||
def api_set_model_whole_url(text_api_set_model_base_url, dropdown_api_gpt_models, dropdown_api_sovits_models,
|
||
text_api_gpt_param, text_api_sovits_param):
|
||
url = audio_inference.SetModelURLComposer("all", text_api_set_model_base_url, text_api_gpt_param,
|
||
text_api_sovits_param)
|
||
return url.build_get_url([dropdown_api_gpt_models, dropdown_api_sovits_models], False)
|
||
|
||
|
||
def start_api_set_model(text_api_set_model_base_url, dropdown_api_gpt_models, dropdown_api_sovits_models,
|
||
text_api_gpt_param, text_api_sovits_param):
|
||
text_api_start_set_model_request_info = None
|
||
try:
|
||
if dropdown_api_gpt_models is None or dropdown_api_gpt_models == '':
|
||
raise Exception("GPT模型不能为空")
|
||
if dropdown_api_sovits_models is None or dropdown_api_sovits_models == '':
|
||
raise Exception("Sovits模型不能为空")
|
||
url = audio_inference.SetModelURLComposer("all", text_api_set_model_base_url, text_api_gpt_param,
|
||
text_api_sovits_param)
|
||
url.is_valid()
|
||
time_consuming, result = time_util.time_monitor(audio_inference.start_api_set_model)(url,
|
||
dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models)
|
||
text_api_start_set_model_request_info = f"耗时：{time_consuming:0.1f}秒；请求结果：{result}"
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_api_start_set_model_request_info = f"发生异常：{e}"
|
||
return text_api_start_set_model_request_info
|
||
|
||
|
||
def refresh_api_v2_gpt_model():
|
||
return {"choices": model_manager.get_gpt_model_names(), "__type__": "update"}
|
||
|
||
|
||
def api_v2_set_gpt_whole_url(text_api_v2_set_gpt_model_base_url, text_api_v2_gpt_model_param,
|
||
dropdown_api_v2_gpt_models):
|
||
url = audio_inference.SetModelURLComposer("gpt", text_api_v2_set_gpt_model_base_url, text_api_v2_gpt_model_param,
|
||
None)
|
||
return url.build_get_url([dropdown_api_v2_gpt_models], False)
|
||
|
||
|
||
def start_api_v2_set_gpt_model(text_api_v2_set_gpt_model_base_url, text_api_v2_gpt_model_param,
|
||
dropdown_api_v2_gpt_models):
|
||
text_api_v2_start_set_gpt_model_request_info = None
|
||
try:
|
||
if dropdown_api_v2_gpt_models is None or dropdown_api_v2_gpt_models == '':
|
||
raise Exception("GPT模型不能为空")
|
||
url = audio_inference.SetModelURLComposer("gpt", text_api_v2_set_gpt_model_base_url,
|
||
text_api_v2_gpt_model_param, None)
|
||
url.is_valid()
|
||
time_consuming, result = time_util.time_monitor(audio_inference.start_api_v2_set_gpt_model)(url,
|
||
dropdown_api_v2_gpt_models)
|
||
text_api_v2_start_set_gpt_model_request_info = f"耗时：{time_consuming:0.1f}秒；请求结果：{result}"
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_api_v2_start_set_gpt_model_request_info = f"发生异常：{e}"
|
||
return text_api_v2_start_set_gpt_model_request_info
|
||
|
||
|
||
def refresh_api_v2_sovits_model():
|
||
return {"choices": model_manager.get_sovits_model_names(), "__type__": "update"}
|
||
|
||
|
||
def api_v2_set_sovits_whole_url(text_api_v2_set_sovits_model_base_url, text_api_v2_sovits_model_param,
|
||
dropdown_api_v2_sovits_models):
|
||
url = audio_inference.SetModelURLComposer("sovits", text_api_v2_set_sovits_model_base_url, None,
|
||
text_api_v2_sovits_model_param)
|
||
return url.build_get_url([dropdown_api_v2_sovits_models], False)
|
||
|
||
|
||
def start_api_v2_set_sovits_model(text_api_v2_set_sovits_model_base_url, text_api_v2_sovits_model_param,
|
||
dropdown_api_v2_sovits_models):
|
||
text_api_v2_start_set_sovits_model_request_info = None
|
||
try:
|
||
if dropdown_api_v2_sovits_models is None or dropdown_api_v2_sovits_models == '':
|
||
raise Exception("Sovits模型不能为空")
|
||
url = audio_inference.SetModelURLComposer("sovits", text_api_v2_set_sovits_model_base_url, None,
|
||
text_api_v2_sovits_model_param)
|
||
url.is_valid()
|
||
time_consuming, result = time_util.time_monitor(audio_inference.start_api_v2_set_sovits_model)(url,
|
||
dropdown_api_v2_sovits_models)
|
||
text_api_v2_start_set_sovits_model_request_info = f"耗时：{time_consuming:0.1f}秒；请求结果：{result}"
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_api_v2_start_set_sovits_model_request_info = f"发生异常：{e}"
|
||
return text_api_v2_start_set_sovits_model_request_info
|
||
|
||
|
||
def open_file(file_path):
|
||
common.open_file(my_utils.clean_path(file_path))
|
||
|
||
|
||
def delete_ref_audio_below_boundary(ref_audio_path, text_text_similarity_result_path, text_inference_audio_file_dir,
|
||
slider_audio_text_similarity_boundary):
|
||
text_delete_ref_audio_below_boundary_info = None
|
||
ref_audio_path, text_text_similarity_result_path, text_inference_audio_file_dir = common.batch_clean_paths(
|
||
[ref_audio_path, text_text_similarity_result_path, text_inference_audio_file_dir])
|
||
try:
|
||
if ref_audio_path is None or ref_audio_path == '':
|
||
raise Exception("参考音频路径不能为空")
|
||
if text_text_similarity_result_path is None or text_text_similarity_result_path == '':
|
||
raise Exception("文本相似度结果路径不能为空")
|
||
time_consuming, count = time_util.time_monitor(text_check.delete_ref_audio_below_boundary)(ref_audio_path,
|
||
text_text_similarity_result_path,
|
||
text_inference_audio_file_dir,
|
||
slider_audio_text_similarity_boundary)
|
||
text_delete_ref_audio_below_boundary_info = f"耗时：{time_consuming:0.1f}秒；删除参考音频数量：{count}"
|
||
except Exception as e:
|
||
logger.error("发生异常: \n%s", traceback.format_exc())
|
||
text_delete_ref_audio_below_boundary_info = f"发生异常：{e}"
|
||
return text_delete_ref_audio_below_boundary_info
|
||
|
||
|
||
def change_lang_choices(key): # 根据选择的模型修改可选的语言
|
||
# return gr.Dropdown(choices=asr_dict[key]['lang'])
|
||
return {"__type__": "update", "choices": asr_dict[key]['lang'], "value": asr_dict[key]['lang'][0]}
|
||
|
||
|
||
def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸
|
||
# return gr.Dropdown(choices=asr_dict[key]['size'])
|
||
return {"__type__": "update", "choices": asr_dict[key]['size']}
|
||
|
||
|
||
def save_generate_audio_url(text_url):
|
||
rw_param.write(rw_param.text_url, text_url)
|
||
|
||
|
||
def save_text_param(text_text):
|
||
rw_param.write(rw_param.text_param, text_text)
|
||
|
||
|
||
def save_ref_path_param(text_ref_path):
|
||
rw_param.write(rw_param.ref_path_param, text_ref_path)
|
||
|
||
|
||
def save_ref_text_param(text_ref_text):
|
||
rw_param.write(rw_param.ref_text_param, text_ref_text)
|
||
|
||
|
||
def save_emotion_param(text_emotion):
|
||
rw_param.write(rw_param.emotion_param, text_emotion)
|
||
|
||
|
||
def save_work_dir(text_work_space_dir, text_role):
|
||
text_work_space_dir = my_utils.clean_path(text_work_space_dir)
|
||
rw_param.write(rw_param.work_dir, text_work_space_dir)
|
||
if text_role is not None and text_role != '':
|
||
return text_role
|
||
else:
|
||
role_dir = ''
|
||
for i in range(1, 101):
|
||
role_dir = f"role_{i}"
|
||
dir_name = os.path.join(text_work_space_dir, role_dir)
|
||
if not os.path.isdir(dir_name):
|
||
break
|
||
rw_param.write(rw_param.role, role_dir)
|
||
return role_dir
|
||
|
||
|
||
def chang_refer_type_param(selected_value):
|
||
rw_param.write(rw_param.refer_type_param, selected_value)
|
||
if selected_value == "参考音频":
|
||
return {"visible": True, "__type__": "update"}, {"visible": True, "__type__": "update"}, {"visible": False,
|
||
"__type__": "update"}
|
||
else:
|
||
return {"visible": False, "__type__": "update"}, {"visible": False, "__type__": "update"}, {"visible": True,
|
||
"__type__": "update"}
|
||
|
||
|
||
def switch_role_and_refresh():
|
||
global hide_voice_similarity_dir, hide_config_file
|
||
init.init_all()
|
||
reset_list = []
|
||
# 基础
|
||
reset_list.extend([
|
||
init.text_refer_audio_file_dir_default,
|
||
init.text_inference_audio_file_dir_default
|
||
])
|
||
# 第一步
|
||
reset_list.extend([
|
||
init.text_sample_dir_default,
|
||
'', # text_list_input
|
||
'', # text_base_voice_path
|
||
])
|
||
# 第二步
|
||
# 第三步
|
||
reset_list.extend([
|
||
init.text_asr_audio_dir_default,
|
||
init.text_text_similarity_analysis_path_default
|
||
])
|
||
# 第四步
|
||
reset_list.extend([
|
||
'', # text_base_audio_path
|
||
'', # text_compare_audio_dir
|
||
])
|
||
hide_voice_similarity_dir = ''
|
||
hide_config_file = ''
|
||
# 第五步
|
||
return reset_list
|
||
|
||
|
||
def init_ui():
|
||
init.init_all()
|
||
|
||
with gr.Blocks() as app:
|
||
gr.Markdown(value=i18n("基本介绍：这是一个从训练素材中，批量提取参考音频，并进行效果评估与配置生成的工具"))
|
||
with gr.Accordion(label=i18n("基本信息")):
|
||
with gr.Row():
|
||
text_work_space_dir = gr.Text(label=i18n("工作目录，后续操作所生成文件都会保存在此目录下"),
|
||
value=init.text_work_space_dir_default, scale=4)
|
||
text_role = gr.Text(label=i18n("角色名称"), value=init.text_role_default, scale=4)
|
||
button_switch_role_and_refresh = gr.Button(i18n("切换并刷新"), variant="primary", scale=1)
|
||
text_work_space_dir.blur(save_work_dir, [text_work_space_dir, text_role], [text_role])
|
||
text_role.blur(lambda value: rw_param.write(rw_param.role, value), [text_role], [])
|
||
gr.Markdown(value=i18n("下方为公共参数，会随着进度自动填充，无需填写"))
|
||
with gr.Row():
|
||
text_refer_audio_file_dir = gr.Text(label=i18n("参考音频所在目录"),
|
||
value=init.text_refer_audio_file_dir_default)
|
||
text_inference_audio_file_dir = gr.Text(label=i18n("推理音频所在目录"),
|
||
value=init.text_inference_audio_file_dir_default)
|
||
with gr.Tab(label=i18n("第一步：基于训练素材，生成待选参考音频列表")):
|
||
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():
|
||
button_convert_from_list = gr.Button(i18n("开始生成待参考列表"), variant="primary", scale=4)
|
||
text_convert_from_list_info = gr.Text(label=i18n("参考列表生成结果"), value="", interactive=False,
|
||
scale=4)
|
||
button_convert_from_list_result_dir = gr.Button(i18n("打开目录"), variant="primary", scale=1)
|
||
gr.Markdown(value=i18n("1.2：选择基准音频，执行相似度匹配，并分段随机抽样"))
|
||
with gr.Row():
|
||
text_sample_dir = gr.Text(label=i18n("参考音频抽样目录"), value=init.text_sample_dir_default,
|
||
interactive=True)
|
||
dropdown_speaker_verification_1 = gr.Dropdown(label=i18n("说话人确认算法"),
|
||
choices=list(
|
||
model_manager.speaker_verification_models.keys()),
|
||
value='speech_campplus_sv_zh-cn_16k-common',
|
||
interactive=True)
|
||
button_convert_from_list_result_dir.click(open_file, [text_sample_dir], [])
|
||
button_convert_from_list.click(convert_from_list, [text_work_space_dir, text_role, text_list_input],
|
||
[text_convert_from_list_info, text_sample_dir])
|
||
with gr.Row():
|
||
text_base_voice_path = gr.Text(label=i18n("请输入基准音频路径"), value="")
|
||
slider_subsection_num = gr.Slider(minimum=1, maximum=10, step=1, label=i18n("请输入分段数"),
|
||
value=init.slider_subsection_num_default,
|
||
interactive=True)
|
||
slider_sample_num = gr.Slider(minimum=1, maximum=10, step=1, label=i18n("请输入每段随机抽样个数"),
|
||
value=init.slider_sample_num_default, interactive=True)
|
||
checkbox_similarity_output = gr.Checkbox(label=i18n("是否将相似度匹配结果输出到临时目录？"),
|
||
show_label=True)
|
||
slider_subsection_num.change(lambda value: rw_param.write(rw_param.subsection_num, value),
|
||
[slider_subsection_num], [])
|
||
slider_sample_num.change(lambda value: rw_param.write(rw_param.sample_num, value), [slider_sample_num],
|
||
[])
|
||
with gr.Row():
|
||
button_sample = gr.Button(i18n("开始分段随机抽样"), variant="primary", scale=4)
|
||
text_sample_info = gr.Text(label=i18n("分段随机抽样结果"), value="", interactive=False, scale=4)
|
||
button_sample_result_open = gr.Button(i18n("打开目录"), variant="primary", scale=1)
|
||
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")):
|
||
gr.Markdown(value=i18n("2.1：启动推理服务，并配置模型参数"))
|
||
with gr.Accordion(label=i18n("详情")):
|
||
with gr.Tab(label=i18n("主项目下api.py服务")):
|
||
gr.Markdown(value=i18n("2.1.1：启动服务"))
|
||
with gr.Row():
|
||
button_start_api = gr.Button(i18n("启动api"), variant="primary")
|
||
text_start_api_info = gr.Text(label=i18n("api启动信息"), value="", interactive=False)
|
||
button_start_api.click(start_api, [], [text_start_api_info])
|
||
gr.Markdown(value=i18n("2.1.2：设置模型参数"))
|
||
text_api_set_model_base_url = gr.Text(label=i18n("请输入api服务模型切换接口地址"),
|
||
value=init.text_api_set_model_base_url_default,
|
||
interactive=True)
|
||
text_api_set_model_base_url.blur(
|
||
lambda value: rw_param.write(rw_param.api_set_model_base_url, value),
|
||
[text_api_set_model_base_url], [])
|
||
with gr.Row():
|
||
dropdown_api_gpt_models = gr.Dropdown(label=i18n("GPT模型列表"),
|
||
choices=model_manager.get_gpt_model_names(), value="",
|
||
interactive=True, scale=4)
|
||
dropdown_api_sovits_models = gr.Dropdown(label=i18n("SoVITS模型列表"),
|
||
choices=model_manager.get_sovits_model_names(),
|
||
value="", interactive=True, scale=4)
|
||
button_refresh_api_model = gr.Button(i18n("刷新模型路径"), variant="primary", scale=1)
|
||
button_refresh_api_model.click(refresh_api_model, [],
|
||
[dropdown_api_gpt_models, dropdown_api_sovits_models])
|
||
with gr.Row():
|
||
text_api_gpt_param = gr.Text(label=i18n("GPT模型参数名"), value=init.text_api_gpt_param_default,
|
||
interactive=True)
|
||
text_api_sovits_param = gr.Text(label=i18n("SoVITS模型参数名"),
|
||
value=init.text_api_sovits_param_default, interactive=True)
|
||
text_api_gpt_param.blur(lambda value: rw_param.write(rw_param.api_gpt_param, value),
|
||
[text_api_gpt_param], [])
|
||
text_api_sovits_param.blur(lambda value: rw_param.write(rw_param.api_sovits_param, value),
|
||
[text_api_sovits_param], [])
|
||
gr.Markdown(value=i18n("2.1.3：发起设置请求"))
|
||
text_api_set_model_whole_url = gr.Text(label=i18n("完整的模型参数设置请求地址"), value="",
|
||
interactive=False)
|
||
dropdown_api_gpt_models.change(api_set_model_whole_url,
|
||
[text_api_set_model_base_url, dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models, text_api_gpt_param,
|
||
text_api_sovits_param], [text_api_set_model_whole_url])
|
||
dropdown_api_sovits_models.change(api_set_model_whole_url,
|
||
[text_api_set_model_base_url, dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models, text_api_gpt_param,
|
||
text_api_sovits_param], [text_api_set_model_whole_url])
|
||
text_api_gpt_param.input(api_set_model_whole_url,
|
||
[text_api_set_model_base_url, dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models, text_api_gpt_param, text_api_sovits_param],
|
||
[text_api_set_model_whole_url])
|
||
text_api_sovits_param.input(api_set_model_whole_url,
|
||
[text_api_set_model_base_url, dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models, text_api_gpt_param, text_api_sovits_param],
|
||
[text_api_set_model_whole_url])
|
||
with gr.Row():
|
||
button_api_start_set_model_request = gr.Button(i18n("发起模型设置请求"), variant="primary")
|
||
text_api_start_set_model_request_info = gr.Text(label=i18n("设置请求结果"), value="",
|
||
interactive=False)
|
||
button_api_start_set_model_request.click(start_api_set_model,
|
||
[text_api_set_model_base_url, dropdown_api_gpt_models,
|
||
dropdown_api_sovits_models, text_api_gpt_param,
|
||
text_api_sovits_param],
|
||
[text_api_start_set_model_request_info])
|
||
with gr.Tab(label=i18n("fast项目下api_v2.py服务")):
|
||
gr.Markdown(value=i18n("2.1.1：请到你的项目下，启动服务"))
|
||
gr.Markdown(value=i18n("2.1.2：设置GPT模型参数"))
|
||
text_api_v2_set_gpt_model_base_url = gr.Text(label=i18n("请输入api服务GPT模型切换接口地址"),
|
||
value=init.text_api_v2_set_gpt_model_base_url_default,
|
||
interactive=True)
|
||
text_api_v2_set_gpt_model_base_url.blur(
|
||
lambda value: rw_param.write(rw_param.api_v2_set_gpt_model_base_url, value),
|
||
[text_api_v2_set_gpt_model_base_url], [])
|
||
with gr.Row():
|
||
text_api_v2_gpt_model_param = gr.Text(label=i18n("GPT模型参数名"),
|
||
value=init.text_api_v2_gpt_model_param_default,
|
||
interactive=True, scale=4)
|
||
dropdown_api_v2_gpt_models = gr.Dropdown(label=i18n("GPT模型列表"),
|
||
choices=model_manager.get_gpt_model_names(), value="",
|
||
interactive=True, scale=4)
|
||
text_api_v2_gpt_model_param.blur(
|
||
lambda value: rw_param.write(rw_param.api_v2_gpt_model_param, value),
|
||
[text_api_v2_gpt_model_param], [])
|
||
button_api_v2_refresh_gpt = gr.Button(i18n("刷新模型路径"), variant="primary", scale=1)
|
||
button_api_v2_refresh_gpt.click(refresh_api_v2_gpt_model, [], [dropdown_api_v2_gpt_models])
|
||
text_api_v2_set_gpt_model_whole_url = gr.Text(label=i18n("完整的GPT模型参数设置请求地址"), value="",
|
||
interactive=False)
|
||
text_api_v2_gpt_model_param.input(api_v2_set_gpt_whole_url,
|
||
[text_api_v2_set_gpt_model_base_url, text_api_v2_gpt_model_param,
|
||
dropdown_api_v2_gpt_models],
|
||
[text_api_v2_set_gpt_model_whole_url])
|
||
dropdown_api_v2_gpt_models.change(api_v2_set_gpt_whole_url,
|
||
[text_api_v2_set_gpt_model_base_url, text_api_v2_gpt_model_param,
|
||
dropdown_api_v2_gpt_models],
|
||
[text_api_v2_set_gpt_model_whole_url])
|
||
with gr.Row():
|
||
button_api_v2_start_set_gpt_model_request = gr.Button(i18n("发起GPT模型设置请求"),
|
||
variant="primary")
|
||
text_api_v2_start_set_gpt_model_request_info = gr.Text(label=i18n("设置请求结果"), value="",
|
||
interactive=False)
|
||
button_api_v2_start_set_gpt_model_request.click(start_api_v2_set_gpt_model,
|
||
[text_api_v2_set_gpt_model_base_url,
|
||
text_api_v2_gpt_model_param,
|
||
dropdown_api_v2_gpt_models],
|
||
[text_api_v2_start_set_gpt_model_request_info])
|
||
gr.Markdown(value=i18n("2.1.3：设置SoVITS模型参数"))
|
||
text_api_v2_set_sovits_model_base_url = gr.Text(label=i18n("请输入api服务SoVITS模型切换接口地址"),
|
||
value=init.text_api_v2_set_sovits_model_base_url_default,
|
||
interactive=True)
|
||
text_api_v2_set_sovits_model_base_url.blur(
|
||
lambda value: rw_param.write(rw_param.api_v2_set_sovits_model_base_url, value),
|
||
[text_api_v2_set_sovits_model_base_url], [])
|
||
with gr.Row():
|
||
text_api_v2_sovits_model_param = gr.Text(label=i18n("SoVITS模型参数名"),
|
||
value=init.text_api_v2_sovits_model_param_default,
|
||
interactive=True, scale=4)
|
||
dropdown_api_v2_sovits_models = gr.Dropdown(label=i18n("SoVITS模型列表"),
|
||
choices=model_manager.get_sovits_model_names(),
|
||
value="", interactive=True, scale=4)
|
||
button_api_v2_refresh_sovits = gr.Button(i18n("刷新模型路径"), variant="primary", scale=1)
|
||
text_api_v2_sovits_model_param.blur(
|
||
lambda value: rw_param.write(rw_param.api_v2_sovits_model_param, value),
|
||
[text_api_v2_sovits_model_param], [])
|
||
button_api_v2_refresh_sovits.click(refresh_api_v2_sovits_model, [],
|
||
[dropdown_api_v2_sovits_models])
|
||
text_api_v2_set_sovits_model_whole_url = gr.Text(label=i18n("完整的SoVITS模型参数设置请求地址"),
|
||
value="", interactive=False)
|
||
text_api_v2_sovits_model_param.input(api_v2_set_sovits_whole_url,
|
||
[text_api_v2_set_sovits_model_base_url,
|
||
text_api_v2_sovits_model_param,
|
||
dropdown_api_v2_sovits_models],
|
||
[text_api_v2_set_sovits_model_whole_url])
|
||
dropdown_api_v2_sovits_models.change(api_v2_set_sovits_whole_url,
|
||
[text_api_v2_set_sovits_model_base_url,
|
||
text_api_v2_sovits_model_param,
|
||
dropdown_api_v2_sovits_models],
|
||
[text_api_v2_set_sovits_model_whole_url])
|
||
with gr.Row():
|
||
button_api_v2_start_set_sovits_model_request = gr.Button(i18n("发起SoVITS模型设置请求"),
|
||
variant="primary")
|
||
text_api_v2_start_set_sovits_model_request_info = gr.Text(label=i18n("设置请求结果"), value="",
|
||
interactive=False)
|
||
button_api_v2_start_set_sovits_model_request.click(start_api_v2_set_sovits_model,
|
||
[text_api_v2_set_sovits_model_base_url,
|
||
text_api_v2_sovits_model_param,
|
||
dropdown_api_v2_sovits_models], [
|
||
text_api_v2_start_set_sovits_model_request_info])
|
||
with gr.Tab(label=i18n("第三方推理服务")):
|
||
gr.Markdown(value=i18n("启动第三方推理服务，并完成参考音频打包，模型参数设置等操作"))
|
||
gr.Markdown(value=i18n("2.2：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"))
|
||
text_url = gr.Text(label=i18n("请输入推理服务请求地址与参数"),
|
||
value=init.text_url_default)
|
||
with gr.Row():
|
||
text_text = gr.Text(label=i18n("请输入文本参数名"), value=init.text_text_default)
|
||
dropdown_refer_type_param = gr.Dropdown(label=i18n("类型"), choices=["参考音频", "角色情绪"],
|
||
value=init.dropdown_refer_type_param_default, interactive=True)
|
||
text_ref_path = gr.Text(label=i18n("请输入参考音频路径参数名"),
|
||
value=init.text_ref_path_default, visible=True)
|
||
text_ref_text = gr.Text(label=i18n("请输入参考音频文本参数名"),
|
||
value=init.text_ref_text_default, visible=True)
|
||
text_emotion = gr.Text(label=i18n("请输入角色情绪参数名"), value=init.text_emotion_default,
|
||
visible=False)
|
||
dropdown_refer_type_param.change(chang_refer_type_param, [dropdown_refer_type_param],
|
||
[text_ref_path, text_ref_text, text_emotion])
|
||
text_whole_url = gr.Text(label=i18n("完整地址"), value="", interactive=False)
|
||
|
||
text_text.blur(lambda value: rw_param.write(rw_param.text_param, value), [text_text], [])
|
||
text_ref_path.blur(lambda value: rw_param.write(rw_param.ref_path_param, value), [text_ref_path], [])
|
||
text_ref_text.blur(lambda value: rw_param.write(rw_param.ref_text_param, value), [text_ref_text], [])
|
||
text_emotion.blur(lambda value: rw_param.write(rw_param.emotion_param, value), [text_emotion], [])
|
||
|
||
text_url.input(whole_url,
|
||
[text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text, text_emotion],
|
||
[text_whole_url])
|
||
text_url.blur(save_generate_audio_url, [text_url], [])
|
||
text_text.input(whole_url, [text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text,
|
||
text_emotion],
|
||
[text_whole_url])
|
||
text_text.blur(save_text_param, [text_text], [])
|
||
text_ref_path.input(whole_url,
|
||
[text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text,
|
||
text_emotion],
|
||
[text_whole_url])
|
||
text_ref_path.blur(save_ref_path_param, [text_ref_path], [])
|
||
text_ref_text.input(whole_url,
|
||
[text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text,
|
||
text_emotion],
|
||
[text_whole_url])
|
||
text_ref_text.blur(save_ref_text_param, [text_ref_text], [])
|
||
text_emotion.input(whole_url, [text_url, dropdown_refer_type_param, text_text, text_ref_path, text_ref_text,
|
||
text_emotion],
|
||
[text_whole_url])
|
||
text_emotion.blur(save_emotion_param, [text_emotion], [])
|
||
gr.Markdown(value=i18n("2.3：配置待推理文本，一句一行，尽量保证文本多样性，不同情绪、不同类型的都来一点"))
|
||
with gr.Row():
|
||
text_test_content = gr.Text(label=i18n("请输入待推理文本路径"), value=init.text_test_content_default,
|
||
scale=8)
|
||
button_open_test_content_file = gr.Button(i18n("打开推理文本"), variant="primary", scale=1)
|
||
button_open_test_content_file.click(open_file, [text_test_content], [])
|
||
text_test_content.blur(lambda value: rw_param.write(rw_param.test_content_path, value),
|
||
[text_test_content], [])
|
||
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"))
|
||
slider_request_concurrency_num = gr.Slider(minimum=1, maximum=init.slider_request_concurrency_max_num,
|
||
step=1, label=i18n(
|
||
"请输入请求并发数，会根据此数创建对应数量的子进程并行发起推理请求"),
|
||
value=init.slider_request_concurrency_num_default,
|
||
interactive=True)
|
||
slider_request_concurrency_num.change(lambda value: rw_param.write(rw_param.request_concurrency_num, value),
|
||
[slider_request_concurrency_num], [])
|
||
with gr.Row():
|
||
button_model_inference = gr.Button(i18n("开启批量推理"), variant="primary", scale=4)
|
||
text_model_inference_info = gr.Text(label=i18n("批量推理结果"), value="", interactive=False, scale=4)
|
||
button_model_inference_result_open = gr.Button(i18n("打开目录"), variant="primary", scale=1)
|
||
with gr.Tab(label=i18n("第三步：进行参考音频效果校验与筛选")):
|
||
gr.Markdown(value=i18n("3.1：启动asr，获取推理音频文本"))
|
||
text_asr_audio_dir = gr.Text(label=i18n("待asr的音频所在目录"), value=init.text_asr_audio_dir_default,
|
||
interactive=True)
|
||
with gr.Row():
|
||
dropdown_asr_model = gr.Dropdown(
|
||
label=i18n("ASR 模型"),
|
||
choices=list(asr_dict.keys()),
|
||
interactive=True,
|
||
value="达摩 ASR (中文)"
|
||
)
|
||
dropdown_asr_size = gr.Dropdown(
|
||
label=i18n("ASR 模型尺寸"),
|
||
choices=["large"],
|
||
interactive=True,
|
||
value="large"
|
||
)
|
||
dropdown_asr_lang = gr.Dropdown(
|
||
label=i18n("ASR 语言设置"),
|
||
choices=["zh"],
|
||
interactive=True,
|
||
value="zh"
|
||
)
|
||
dropdown_asr_model.change(change_lang_choices, [dropdown_asr_model], [dropdown_asr_lang])
|
||
dropdown_asr_model.change(change_size_choices, [dropdown_asr_model], [dropdown_asr_size])
|
||
with gr.Row():
|
||
button_asr = gr.Button(i18n("启动asr"), variant="primary", scale=4)
|
||
text_asr_info = gr.Text(label=i18n("asr结果"), value="", interactive=False, scale=4)
|
||
button_asr_result_open = gr.Button(i18n("打开文件"), variant="primary", scale=1)
|
||
gr.Markdown(value=i18n("3.2：启动文本相似度分析"))
|
||
with gr.Row():
|
||
text_text_similarity_analysis_path = gr.Text(label=i18n("待分析的文件路径"),
|
||
value=init.text_text_similarity_analysis_path_default,
|
||
interactive=True)
|
||
slider_text_similarity_amplification_boundary = gr.Slider(minimum=0, maximum=1, step=0.01,
|
||
label=i18n("文本相似度放大边界"),
|
||
value=init.slider_text_similarity_amplification_boundary_default,
|
||
interactive=True)
|
||
slider_text_similarity_amplification_boundary.change(
|
||
lambda value: rw_param.write(rw_param.text_similarity_amplification_boundary, value),
|
||
[slider_text_similarity_amplification_boundary], [])
|
||
button_asr.click(asr, [text_work_space_dir, text_role, text_asr_audio_dir, dropdown_asr_model,
|
||
dropdown_asr_size, dropdown_asr_lang],
|
||
[text_asr_info, text_text_similarity_analysis_path])
|
||
button_asr_result_open.click(open_file, [text_text_similarity_analysis_path], [])
|
||
with gr.Row():
|
||
button_text_similarity_analysis = gr.Button(i18n("启动文本相似度分析"), variant="primary")
|
||
text_text_similarity_analysis_info = gr.Text(label=i18n("文本相似度分析结果"), value="",
|
||
interactive=False)
|
||
gr.Markdown(value=i18n("3.3：根据相似度分析结果，重点检查最后几条是否存在复读等问题"))
|
||
with gr.Row():
|
||
text_text_similarity_result_path = gr.Text(label=i18n("文本相似度分析结果文件所在路径"),
|
||
value=init.text_text_similarity_result_path_default,
|
||
interactive=True, scale=7)
|
||
button_open_text_similarity_result = gr.Button(i18n("打开结果文件"), variant="primary", scale=1)
|
||
button_open_inference_dir = gr.Button(i18n("打开推理目录"), variant="primary", scale=1)
|
||
|
||
button_text_similarity_analysis.click(text_similarity_analysis, [text_work_space_dir, text_role,
|
||
slider_text_similarity_amplification_boundary,
|
||
text_text_similarity_analysis_path],
|
||
[text_text_similarity_analysis_info,
|
||
text_text_similarity_result_path])
|
||
|
||
button_open_text_similarity_result.click(open_file, [text_text_similarity_result_path], [])
|
||
button_open_inference_dir.click(open_file, [text_inference_audio_file_dir], [])
|
||
slider_audio_text_similarity_boundary = gr.Slider(minimum=0, maximum=1, step=0.001,
|
||
label=i18n("音频文本相似度边界值"), value=0.800,
|
||
interactive=True)
|
||
with gr.Row():
|
||
button_delete_ref_audio_below_boundary = gr.Button(i18n("删除音频文本相似度边界值以下的参考音频"),
|
||
variant="primary")
|
||
text_delete_ref_audio_below_boundary_info = gr.Text(label=i18n("删除结果"), value="", interactive=True)
|
||
button_delete_ref_audio_below_boundary.click(delete_ref_audio_below_boundary,
|
||
[text_refer_audio_file_dir,
|
||
text_text_similarity_result_path,
|
||
text_inference_audio_file_dir,
|
||
slider_audio_text_similarity_boundary],
|
||
[text_delete_ref_audio_below_boundary_info])
|
||
with gr.Tab(label=i18n("第四步：校验参考音频音质")):
|
||
gr.Markdown(value=i18n("4.1：对结果按音频相似度排序，或许有用吧，主要还是耳朵听"))
|
||
with gr.Row():
|
||
text_base_audio_path = gr.Text(label=i18n("请输入基准音频"), value="")
|
||
text_compare_audio_dir = gr.Text(label=i18n("请输入待比较的音频文件目录"), value="")
|
||
dropdown_speaker_verification_2 = gr.Dropdown(label=i18n("说话人确认算法"),
|
||
choices=list(
|
||
model_manager.speaker_verification_models.keys()),
|
||
value='speech_campplus_sv_zh-cn_16k-common',
|
||
interactive=True)
|
||
with gr.Row():
|
||
button_similarity_audio_output = gr.Button(i18n("输出相似度-参考音频到临时目录"), variant="primary",
|
||
scale=4)
|
||
text_similarity_audio_output_info = gr.Text(label=i18n("输出结果"), value="", interactive=False,
|
||
scale=4)
|
||
button_similarity_audio_output_result_open = gr.Button(i18n("打开目录"), variant="primary", scale=1)
|
||
button_similarity_audio_output.click(similarity_audio_output,
|
||
[text_work_space_dir, text_role, text_base_audio_path,
|
||
text_compare_audio_dir, dropdown_speaker_verification_2], [text_similarity_audio_output_info])
|
||
button_similarity_audio_output_result_open.click(lambda: open_file(hide_voice_similarity_dir), [], [])
|
||
gr.Markdown(value=i18n("4.2：如果发现存在低音质的推理音频，那么就去参考音频目录下，把原参考音频删了"))
|
||
gr.Markdown(value=i18n("4.3：删除参考音频之后，按下面的操作，会将推理音频目录下对应的音频也删掉"))
|
||
with gr.Row():
|
||
button_sync_ref_audio = gr.Button(i18n("将参考音频的删除情况，同步到推理音频目录"), variant="primary")
|
||
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_refer_audio_file_dir,
|
||
text_inference_audio_file_dir], [text_sync_ref_info])
|
||
with gr.Tab("第五步：生成参考音频配置文本"):
|
||
gr.Markdown(value=i18n("5.1：编辑模板"))
|
||
text_template = gr.Text(label=i18n("模板内容"), value=init.text_template_default, lines=10)
|
||
text_template.blur(lambda value: rw_param.write(rw_param.text_template, value), [text_template], [])
|
||
gr.Markdown(value=i18n("5.2：生成配置"))
|
||
with gr.Row():
|
||
button_create_config = gr.Button(i18n("生成配置"), variant="primary", scale=4)
|
||
text_create_config_info = gr.Text(label=i18n("生成结果"), value="", interactive=False, scale=4)
|
||
button_create_config_result_open = gr.Button(i18n("打开文件"), variant="primary", scale=1)
|
||
button_create_config.click(create_config,
|
||
[text_work_space_dir, text_role, text_template, text_refer_audio_file_dir],
|
||
[text_create_config_info])
|
||
button_create_config_result_open.click(lambda: open_file(hide_config_file), [], [])
|
||
button_sample.click(sample, [text_work_space_dir, text_role, text_sample_dir, dropdown_speaker_verification_1, text_base_voice_path,
|
||
slider_subsection_num, slider_sample_num, checkbox_similarity_output],
|
||
[text_sample_info, text_refer_audio_file_dir])
|
||
button_sample_result_open.click(open_file, [text_refer_audio_file_dir], [])
|
||
button_model_inference.click(model_inference,
|
||
[text_work_space_dir, text_role, slider_request_concurrency_num,
|
||
text_refer_audio_file_dir, text_url, dropdown_refer_type_param,
|
||
text_text, text_ref_path, text_ref_text, text_emotion,
|
||
text_test_content],
|
||
[text_model_inference_info, text_asr_audio_dir, text_inference_audio_file_dir])
|
||
button_model_inference_result_open.click(open_file, [text_inference_audio_file_dir], [])
|
||
|
||
# 设置重置刷新事件
|
||
refresh_list = []
|
||
# 基础
|
||
refresh_list.extend([
|
||
text_refer_audio_file_dir,
|
||
text_inference_audio_file_dir
|
||
])
|
||
# 第一步
|
||
refresh_list.extend([
|
||
text_sample_dir,
|
||
text_list_input,
|
||
text_base_voice_path
|
||
])
|
||
# 第二步
|
||
# 第三步
|
||
refresh_list.extend([
|
||
text_asr_audio_dir,
|
||
text_text_similarity_analysis_path
|
||
])
|
||
# 第四步
|
||
refresh_list.extend([
|
||
text_base_audio_path,
|
||
text_compare_audio_dir
|
||
])
|
||
# 第五步
|
||
|
||
button_switch_role_and_refresh.click(switch_role_and_refresh, [], refresh_list)
|
||
|
||
app.launch(
|
||
server_port=params.server_port,
|
||
inbrowser=True,
|
||
quiet=True,
|
||
)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
init_ui()
|