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| import os | |
| import random | |
| import gradio as gr | |
| import time | |
| import torch | |
| import gc | |
| import warnings | |
| warnings.filterwarnings('ignore') | |
| from zhconv import convert | |
| from LLM import LLM | |
| from TTS import EdgeTTS | |
| from src.cost_time import calculate_time | |
| from configs import * | |
| os.environ["GRADIO_TEMP_DIR"]= './temp' | |
| os.environ["WEBUI"] = "true" | |
| def get_title(title = 'Linly 智能对话系统 (Linly-Talker)'): | |
| description = f""" | |
| <p style="text-align: center; font-weight: bold;"> | |
| <span style="font-size: 28px;">{title}</span> | |
| <br> | |
| <span style="font-size: 18px;" id="paper-info"> | |
| [<a href="https://zhuanlan.zhihu.com/p/671006998" target="_blank">知乎</a>] | |
| [<a href="https://www.bilibili.com/video/BV1rN4y1a76x/" target="_blank">bilibili</a>] | |
| [<a href="https://github.com/Kedreamix/Linly-Talker" target="_blank">GitHub</a>] | |
| [<a herf="https://kedreamix.github.io/" target="_blank">个人主页</a>] | |
| </span> | |
| <br> | |
| <span>Linly-Talker是一款创新的数字人对话系统，它融合了最新的人工智能技术，包括大型语言模型（LLM）🤖、自动语音识别（ASR）🎙️、文本到语音转换（TTS）🗣️和语音克隆技术🎤。</span> | |
| </p> | |
| """ | |
| return description | |
| # 设置默认system | |
| default_system = '你是一个很有帮助的助手' | |
| # 设置默认的prompt | |
| prefix_prompt = '''请用少于25个字回答以下问题\n\n''' | |
| edgetts = EdgeTTS() | |
| # 设定默认参数值，可修改 | |
| blink_every = True | |
| size_of_image = 256 | |
| preprocess_type = 'crop' | |
| facerender = 'facevid2vid' | |
| enhancer = False | |
| is_still_mode = False | |
| exp_weight = 1 | |
| use_ref_video = False | |
| ref_video = None | |
| ref_info = 'pose' | |
| use_idle_mode = False | |
| length_of_audio = 5 | |
| def Asr(audio): | |
| try: | |
| question = asr.transcribe(audio) | |
| question = convert(question, 'zh-cn') | |
| except Exception as e: | |
| print("ASR Error: ", e) | |
| question = 'Gradio存在一些bug，麦克风模式有时候可能音频还未传入，请重新点击一下语音识别即可' | |
| gr.Warning(question) | |
| return question | |
| def clear_memory(): | |
| """ | |
| 清理PyTorch的显存和系统内存缓存。 | |
| """ | |
| # 1. 清理缓存的变量 | |
| gc.collect() # 触发Python垃圾回收 | |
| torch.cuda.empty_cache() # 清理PyTorch的显存缓存 | |
| torch.cuda.ipc_collect() # 清理PyTorch的跨进程通信缓存 | |
| # 2. 打印显存使用情况（可选） | |
| print(f"Memory allocated: {torch.cuda.memory_allocated() / (1024 ** 2):.2f} MB") | |
| print(f"Max memory allocated: {torch.cuda.max_memory_allocated() / (1024 ** 2):.2f} MB") | |
| print(f"Cached memory: {torch.cuda.memory_reserved() / (1024 ** 2):.2f} MB") | |
| print(f"Max cached memory: {torch.cuda.max_memory_reserved() / (1024 ** 2):.2f} MB") | |
| def TTS_response(text, | |
| voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, | |
| question_audio, question, use_mic_voice, | |
| tts_method = 'PaddleTTS', save_path = 'answer.wav'): | |
| # print(text, voice, rate, volume, pitch, am, voc, lang, male, tts_method, save_path) | |
| if tts_method == 'Edge-TTS': | |
| if not edgetts.network: | |
| gr.Warning("请检查网络或者使用其他模型，例如PaddleTTS") | |
| return None, None | |
| try: | |
| edgetts.predict(text, voice, rate, volume, pitch , 'answer.wav', 'answer.vtt') | |
| except: | |
| os.system(f'edge-tts --text "{text}" --voice {voice} --write-media answer.wav --write-subtitles answer.vtt') | |
| return 'answer.wav', 'answer.vtt' | |
| elif tts_method == 'PaddleTTS': | |
| tts.predict(text, am, voc, lang = lang, male=male, save_path = save_path) | |
| return save_path, None | |
| elif tts_method == 'GPT-SoVITS克隆声音': | |
| if use_mic_voice: | |
| try: | |
| vits.predict(ref_wav_path = question_audio, | |
| prompt_text = question, | |
| prompt_language = "中文", | |
| text = text, # 回答 | |
| text_language = "中文", | |
| how_to_cut = "凑四句一切", | |
| save_path = 'answer.wav') | |
| return 'answer.wav', None | |
| except Exception as e: | |
| gr.Warning("无克隆环境或者无克隆模型权重，无法克隆声音", e) | |
| return None, None | |
| else: | |
| try: | |
| vits.predict(ref_wav_path = inp_ref, | |
| prompt_text = prompt_text, | |
| prompt_language = prompt_language, | |
| text = text, # 回答 | |
| text_language = text_language, | |
| how_to_cut = how_to_cut, | |
| save_path = 'answer.wav') | |
| return 'answer.wav', None | |
| except Exception as e: | |
| gr.Warning("无克隆环境或者无克隆模型权重，无法克隆声音", e) | |
| return None, None | |
| return None, None | |
| def LLM_response(question_audio, question, | |
| voice = 'zh-CN-XiaoxiaoNeural', rate = 0, volume = 0, pitch = 0, | |
| am='fastspeech2', voc='pwgan',lang='zh', male=False, | |
| inp_ref = None, prompt_text = "", prompt_language = "", text_language = "", how_to_cut = "", use_mic_voice = False, | |
| tts_method = 'Edge-TTS'): | |
| if len(question) == 0: | |
| gr.Warning("请输入问题") | |
| return None, None, None | |
| answer = llm.generate(question, default_system) | |
| print(answer) | |
| driven_audio, driven_vtt = TTS_response(answer, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, question_audio, question, use_mic_voice, | |
| tts_method) | |
| return driven_audio, driven_vtt, answer | |
| def Talker_response(question_audio = None, method = 'SadTalker', text = '', | |
| voice = 'zh-CN-XiaoxiaoNeural', rate = 0, volume = 100, pitch = 0, | |
| am = 'fastspeech2', voc = 'pwgan', lang = 'zh', male = False, | |
| inp_ref = None, prompt_text = "", prompt_language = "", text_language = "", how_to_cut = "", use_mic_voice = False, | |
| tts_method = 'Edge-TTS',batch_size = 2, character = '女性角色', | |
| progress=gr.Progress(track_tqdm=True)): | |
| default_voice = None | |
| if character == '女性角色': | |
| # 女性角色 | |
| source_image, pic_path = r'inputs/girl.png', r'inputs/girl.png' | |
| crop_pic_path = "./inputs/first_frame_dir_girl/girl.png" | |
| first_coeff_path = "./inputs/first_frame_dir_girl/girl.mat" | |
| crop_info = ((403, 403), (19, 30, 502, 513), [40.05956541381802, 40.17324339233366, 443.7892505041507, 443.9029284826663]) | |
| default_voice = 'zh-CN-XiaoxiaoNeural' | |
| elif character == '男性角色': | |
| # 男性角色 | |
| source_image = r'./inputs/boy.png' | |
| pic_path = "./inputs/boy.png" | |
| crop_pic_path = "./inputs/first_frame_dir_boy/boy.png" | |
| first_coeff_path = "./inputs/first_frame_dir_boy/boy.mat" | |
| crop_info = ((876, 747), (0, 0, 886, 838), [10.382158280494476, 0, 886, 747.7078990925525]) | |
| default_voice = 'zh-CN-YunyangNeural' | |
| else: | |
| gr.Warning('未知角色') | |
| return None | |
| voice = default_voice if not voice else voice | |
| if not voice: | |
| gr.Warning('请选择声音') | |
| driven_audio, driven_vtt, _ = LLM_response(question_audio, text, | |
| voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method) | |
| if driven_audio is None: | |
| gr.Warning("音频没有正常生成，请检查TTS是否正确") | |
| return None | |
| if method == 'SadTalker': | |
| pose_style = random.randint(0, 45) | |
| video = talker.test(pic_path, | |
| crop_pic_path, | |
| first_coeff_path, | |
| crop_info, | |
| source_image, | |
| driven_audio, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| use_ref_video, | |
| ref_video, | |
| ref_info, | |
| use_idle_mode, | |
| length_of_audio, | |
| blink_every, | |
| fps=20) | |
| elif method == 'Wav2Lip': | |
| video = talker.predict(crop_pic_path, driven_audio, batch_size, enhancer) | |
| elif method == 'NeRFTalk': | |
| video = talker.predict(driven_audio) | |
| else: | |
| gr.Warning("不支持的方法：" + method) | |
| return None | |
| if driven_vtt: | |
| return video, driven_vtt | |
| else: | |
| return video | |
| def Talker_response_img(question_audio, method, text, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref , prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, | |
| source_image, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| blink_every, | |
| fps, progress=gr.Progress(track_tqdm=True) | |
| ): | |
| if enhancer: | |
| gr.Warning("记得请先安装GFPGAN库，pip install gfpgan, 已安装可忽略") | |
| if not voice: | |
| gr.Warning("请先选择声音") | |
| driven_audio, driven_vtt, _ = LLM_response(question_audio, text, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method = tts_method) | |
| if driven_audio is None: | |
| gr.Warning("音频没有正常生成，请检查TTS是否正确") | |
| return None | |
| if method == 'SadTalker': | |
| video = talker.test2(source_image, | |
| driven_audio, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| use_ref_video, | |
| ref_video, | |
| ref_info, | |
| use_idle_mode, | |
| length_of_audio, | |
| blink_every, | |
| fps=fps) | |
| elif method == 'Wav2Lip': | |
| video = talker.predict(source_image, driven_audio, batch_size) | |
| elif method == 'NeRFTalk': | |
| video = talker.predict(driven_audio) | |
| else: | |
| return None | |
| if driven_vtt: | |
| return video, driven_vtt | |
| else: | |
| return video | |
| def Talker_Say(preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| blink_every, | |
| fps,source_image = None, source_video = None, question_audio = None, method = 'SadTalker', text = '', | |
| voice = 'zh-CN-XiaoxiaoNeural', rate = 0, volume = 100, pitch = 0, | |
| am = 'fastspeech2', voc = 'pwgan', lang = 'zh', male = False, | |
| inp_ref = None, prompt_text = "", prompt_language = "", text_language = "", how_to_cut = "", use_mic_voice = False, | |
| tts_method = 'Edge-TTS', character = '女性角色', | |
| progress=gr.Progress(track_tqdm=True)): | |
| if source_video: | |
| source_image = source_video | |
| default_voice = None | |
| voice = default_voice if not voice else voice | |
| if not voice: | |
| gr.Warning('请选择声音') | |
| driven_audio, driven_vtt = TTS_response(text, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, question_audio, text, use_mic_voice, | |
| tts_method) | |
| if driven_audio is None: | |
| gr.Warning("音频没有正常生成，请检查TTS是否正确") | |
| return None | |
| if method == 'SadTalker': | |
| pose_style = random.randint(0, 45) | |
| video = talker.test2(source_image, | |
| driven_audio, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| use_ref_video, | |
| ref_video, | |
| ref_info, | |
| use_idle_mode, | |
| length_of_audio, | |
| blink_every, | |
| fps=fps) | |
| elif method == 'Wav2Lip': | |
| video = talker.predict(source_image, driven_audio, batch_size, enhancer) | |
| elif method == 'NeRFTalk': | |
| video = talker.predict(driven_audio) | |
| else: | |
| gr.Warning("不支持的方法：" + method) | |
| return None | |
| if driven_vtt: | |
| return video, driven_vtt | |
| else: | |
| return video | |
| def chat_response(system, message, history): | |
| # response = llm.generate(message) | |
| response, history = llm.chat(system, message, history) | |
| print(history) | |
| # 流式输出 | |
| for i in range(len(response)): | |
| time.sleep(0.01) | |
| yield "", history[:-1] + [(message, response[:i+1])] | |
| return "", history | |
| def modify_system_session(system: str) -> str: | |
| if system is None or len(system) == 0: | |
| system = default_system | |
| llm.clear_history() | |
| return system, system, [] | |
| def clear_session(): | |
| # clear history | |
| llm.clear_history() | |
| return '', [] | |
| def human_response(source_image, history, question_audio, talker_method, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, character, | |
| preprocess_type, is_still_mode, enhancer, batch_size, size_of_image, | |
| pose_style, facerender, exp_weight, blink_every, fps = 20, progress=gr.Progress(track_tqdm=True)): | |
| response = history[-1][1] | |
| qusetion = history[-1][0] | |
| # driven_audio, video_vtt = 'answer.wav', 'answer.vtt' | |
| if character == '女性角色': | |
| # 女性角色 | |
| source_image, pic_path = r'./inputs/girl.png', r"./inputs/girl.png" | |
| crop_pic_path = "./inputs/first_frame_dir_girl/girl.png" | |
| first_coeff_path = "./inputs/first_frame_dir_girl/girl.mat" | |
| crop_info = ((403, 403), (19, 30, 502, 513), [40.05956541381802, 40.17324339233366, 443.7892505041507, 443.9029284826663]) | |
| default_voice = 'zh-CN-XiaoxiaoNeural' | |
| elif character == '男性角色': | |
| # 男性角色 | |
| source_image = r'./inputs/boy.png' | |
| pic_path = "./inputs/boy.png" | |
| crop_pic_path = "./inputs/first_frame_dir_boy/boy.png" | |
| first_coeff_path = "./inputs/first_frame_dir_boy/boy.mat" | |
| crop_info = ((876, 747), (0, 0, 886, 838), [10.382158280494476, 0, 886, 747.7078990925525]) | |
| default_voice = 'zh-CN-YunyangNeural' | |
| elif character == '自定义角色': | |
| if source_image is None: | |
| gr.Error("自定义角色需要上传正确的图片") | |
| return None | |
| default_voice = 'zh-CN-XiaoxiaoNeural' | |
| voice = default_voice if not voice else voice | |
| # tts.predict(response, voice, rate, volume, pitch, driven_audio, video_vtt) | |
| driven_audio, driven_vtt = TTS_response(response, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, question_audio, qusetion, use_mic_voice, | |
| tts_method) | |
| if driven_audio is None: | |
| gr.Warning("音频没有正常生成，请检查TTS是否正确") | |
| return None | |
| if talker_method == 'SadTalker': | |
| pose_style = random.randint(0, 45) | |
| video = talker.test(pic_path, | |
| crop_pic_path, | |
| first_coeff_path, | |
| crop_info, | |
| source_image, | |
| driven_audio, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| use_ref_video, | |
| ref_video, | |
| ref_info, | |
| use_idle_mode, | |
| length_of_audio, | |
| blink_every, | |
| fps=fps) | |
| elif talker_method == 'Wav2Lip': | |
| video = talker.predict(crop_pic_path, driven_audio, batch_size, enhancer) | |
| elif talker_method == 'NeRFTalk': | |
| video = talker.predict(driven_audio) | |
| else: | |
| gr.Warning("不支持的方法：" + talker_method) | |
| return None | |
| if driven_vtt: | |
| return video, driven_vtt | |
| else: | |
| return video | |
| def MuseTalker_response(source_video, bbox_shift, question_audio = None, text = '', | |
| voice = 'zh-CN-XiaoxiaoNeural', rate = 0, volume = 100, pitch = 0, | |
| am = 'fastspeech2', voc = 'pwgan', lang = 'zh', male = False, | |
| inp_ref = None, prompt_text = "", prompt_language = "", text_language = "", how_to_cut = "", use_mic_voice = False, | |
| tts_method = 'Edge-TTS', batch_size = 4, | |
| progress=gr.Progress(track_tqdm=True)): | |
| default_voice = None | |
| voice = default_voice if not voice else voice | |
| if not voice: | |
| gr.Warning('请选择声音') | |
| driven_audio, driven_vtt, _ = LLM_response(question_audio, text, | |
| voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method) | |
| print(driven_audio, driven_vtt) | |
| video = musetalker.inference_noprepare(driven_audio, | |
| source_video, | |
| bbox_shift, | |
| batch_size, | |
| fps = 25) | |
| if driven_vtt: | |
| return (video, driven_vtt) | |
| else: | |
| return video | |
| GPT_SoVITS_ckpt = "GPT_SoVITS/pretrained_models" | |
| def load_vits_model(gpt_path, sovits_path, progress=gr.Progress(track_tqdm=True)): | |
| global vits | |
| print("模型加载中...", gpt_path, sovits_path) | |
| all_gpt_path, all_sovits_path = os.path.join(GPT_SoVITS_ckpt, gpt_path), os.path.join(GPT_SoVITS_ckpt, sovits_path) | |
| vits.load_model(all_gpt_path, all_sovits_path) | |
| gr.Info("模型加载成功") | |
| return gpt_path, sovits_path | |
| def list_models(dir, endwith = ".pth"): | |
| list_folder = os.listdir(dir) | |
| list_folder = [i for i in list_folder if i.endswith(endwith)] | |
| return list_folder | |
| def character_change(character): | |
| if character == '女性角色': | |
| # 女性角色 | |
| source_image = r'./inputs/girl.png' | |
| elif character == '男性角色': | |
| # 男性角色 | |
| source_image = r'./inputs/boy.png' | |
| elif character == '自定义角色': | |
| # gr.Warnings("自定义角色暂未更新，请继续关注后续，可通过自由上传图片模式进行自定义角色") | |
| source_image = None | |
| return source_image | |
| def webui_setting(talk = False): | |
| if not talk: | |
| with gr.Tabs(): | |
| with gr.TabItem('数字人形象设定'): | |
| source_image = gr.Image(label="Source image", type="filepath") | |
| else: | |
| source_image = None | |
| with gr.Tabs("TTS Method"): | |
| with gr.Accordion("TTS Method语音方法调节 ", open=True): | |
| with gr.Tab("Edge-TTS"): | |
| voice = gr.Dropdown(edgetts.SUPPORTED_VOICE, | |
| value='zh-CN-XiaoxiaoNeural', | |
| label="Voice 声音选择") | |
| rate = gr.Slider(minimum=-100, | |
| maximum=100, | |
| value=0, | |
| step=1.0, | |
| label='Rate 速率') | |
| volume = gr.Slider(minimum=0, | |
| maximum=100, | |
| value=100, | |
| step=1, | |
| label='Volume 音量') | |
| pitch = gr.Slider(minimum=-100, | |
| maximum=100, | |
| value=0, | |
| step=1, | |
| label='Pitch 音调') | |
| with gr.Tab("PaddleTTS"): | |
| am = gr.Dropdown(["FastSpeech2"], label="声学模型选择", value = 'FastSpeech2') | |
| voc = gr.Dropdown(["PWGan", "HifiGan"], label="声码器选择", value = 'PWGan') | |
| lang = gr.Dropdown(["zh", "en", "mix", "canton"], label="语言选择", value = 'zh') | |
| male = gr.Checkbox(label="男声(Male)", value=False) | |
| with gr.Tab('GPT-SoVITS'): | |
| with gr.Row(): | |
| gpt_path = gr.FileExplorer(root = GPT_SoVITS_ckpt, glob = "*.ckpt", value = "s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt", file_count='single', label="GPT模型路径") | |
| sovits_path = gr.FileExplorer(root = GPT_SoVITS_ckpt, glob = "*.pth", value = "s2G488k.pth", file_count='single', label="SoVITS模型路径") | |
| # gpt_path = gr.Dropdown(choices=list_models(GPT_SoVITS_ckpt, 'ckpt')) | |
| # sovits_path = gr.Dropdown(choices=list_models(GPT_SoVITS_ckpt, 'pth')) | |
| # gpt_path = gr.Textbox(label="GPT模型路径", | |
| # value="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt") | |
| # sovits_path = gr.Textbox(label="SoVITS模型路径", | |
| # value="GPT_SoVITS/pretrained_models/s2G488k.pth") | |
| button = gr.Button("加载模型") | |
| button.click(fn = load_vits_model, | |
| inputs=[gpt_path, sovits_path], | |
| outputs=[gpt_path, sovits_path]) | |
| with gr.Row(): | |
| inp_ref = gr.Audio(label="请上传3~10秒内参考音频，超过会报错！", sources=["microphone", "upload"], type="filepath") | |
| use_mic_voice = gr.Checkbox(label="使用语音问答的麦克风") | |
| prompt_text = gr.Textbox(label="参考音频的文本", value="") | |
| prompt_language = gr.Dropdown( | |
| label="参考音频的语种", choices=["中文", "英文", "日文"], value="中文" | |
| ) | |
| asr_button = gr.Button("语音识别 - 克隆参考音频") | |
| asr_button.click(fn=Asr,inputs=[inp_ref],outputs=[prompt_text]) | |
| with gr.Row(): | |
| text_language = gr.Dropdown( | |
| label="需要合成的语种", choices=["中文", "英文", "日文", "中英混合", "日英混合", "多语种混合"], value="中文" | |
| ) | |
| how_to_cut = gr.Dropdown( | |
| label="怎么切", | |
| choices=["不切", "凑四句一切", "凑50字一切", "按中文句号。切", "按英文句号.切", "按标点符号切" ], | |
| value="凑四句一切", | |
| interactive=True, | |
| ) | |
| with gr.Column(variant='panel'): | |
| batch_size = gr.Slider(minimum=1, | |
| maximum=10, | |
| value=2, | |
| step=1, | |
| label='Talker Batch size') | |
| character = gr.Radio(['女性角色', | |
| '男性角色', | |
| '自定义角色'], | |
| label="角色选择", value='自定义角色') | |
| character.change(fn = character_change, inputs=[character], outputs = [source_image]) | |
| tts_method = gr.Radio(['Edge-TTS', 'PaddleTTS', 'GPT-SoVITS克隆声音', 'Comming Soon!!!'], label="Text To Speech Method", | |
| value = 'Edge-TTS') | |
| tts_method.change(fn = tts_model_change, inputs=[tts_method], outputs = [tts_method]) | |
| asr_method = gr.Radio(choices = ['Whisper-tiny', 'Whisper-base', 'FunASR', 'Comming Soon!!!'], value='Whisper-base', label = '语音识别模型选择') | |
| asr_method.change(fn = asr_model_change, inputs=[asr_method], outputs = [asr_method]) | |
| talker_method = gr.Radio(choices = ['SadTalker', 'Wav2Lip', 'NeRFTalk', 'Comming Soon!!!'], | |
| value = 'SadTalker', label = '数字人模型选择') | |
| talker_method.change(fn = talker_model_change, inputs=[talker_method], outputs = [talker_method]) | |
| llm_method = gr.Dropdown(choices = ['Qwen', 'Qwen2', 'Linly', 'Gemini', 'ChatGLM', 'ChatGPT', 'GPT4Free', '直接回复 Direct Reply', 'Comming Soon!!!'], value = '直接回复 Direct Reply', label = 'LLM 模型选择') | |
| llm_method.change(fn = llm_model_change, inputs=[llm_method], outputs = [llm_method]) | |
| return (source_image, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method) | |
| def exmaple_setting(asr, text, character, talk , tts, voice, llm): | |
| # 默认text的Example | |
| examples = [ | |
| ['Whisper-base', '应对压力最有效的方法是什么？', '女性角色', 'SadTalker', 'Edge-TTS', 'zh-CN-XiaoxiaoNeural', '直接回复 Direct Reply'], | |
| ['Whisper-tiny', '应对压力最有效的方法是什么？', '女性角色', 'SadTalker', 'PaddleTTS', 'None', '直接回复 Direct Reply'], | |
| ['Whisper-base', '应对压力最有效的方法是什么？', '女性角色', 'SadTalker', 'Edge-TTS', 'zh-CN-XiaoxiaoNeural', 'Qwen'], | |
| ['FunASR', '如何进行时间管理？','男性角色', 'SadTalker', 'Edge-TTS', 'zh-CN-YunyangNeural', 'Qwen'], | |
| ['Whisper-tiny', '为什么有些人选择使用纸质地图或寻求方向，而不是依赖GPS设备或智能手机应用程序？','女性角色', 'Wav2Lip', 'PaddleTTS', 'None', 'Qwen'], | |
| ] | |
| with gr.Row(variant='panel'): | |
| with gr.Column(variant='panel'): | |
| gr.Markdown("## Test Examples") | |
| gr.Examples( | |
| examples = examples, | |
| inputs = [asr, text, character, talk , tts, voice, llm], | |
| ) | |
| def app(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) 文本/语音对话")) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant='panel'): | |
| (source_image, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.TabItem('对话'): | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label = '语音对话') | |
| input_text = gr.Textbox(label="输入文字/问题", lines=3) | |
| asr_text = gr.Button('语音识别（语音对话后点击）') | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[input_text]) | |
| # with gr.TabItem('SadTalker数字人参数设置'): | |
| # with gr.Accordion("Advanced Settings", | |
| # open=False): | |
| # gr.Markdown("SadTalker: need help? please visit our [[best practice page](https://github.com/OpenTalker/SadTalker/blob/main/docs/best_practice.md)] for more detials") | |
| # with gr.Column(variant='panel'): | |
| # # width = gr.Slider(minimum=64, elem_id="img2img_width", maximum=2048, step=8, label="Manually Crop Width", value=512) # img2img_width | |
| # # height = gr.Slider(minimum=64, elem_id="img2img_height", maximum=2048, step=8, label="Manually Crop Height", value=512) # img2img_width | |
| # with gr.Row(): | |
| # pose_style = gr.Slider(minimum=0, maximum=45, step=1, label="Pose style", value=0) # | |
| # exp_weight = gr.Slider(minimum=0, maximum=3, step=0.1, label="expression scale", value=1) # | |
| # blink_every = gr.Checkbox(label="use eye blink", value=True) | |
| # with gr.Row(): | |
| # size_of_image = gr.Radio([256, 512], value=256, label='face model resolution', info="use 256/512 model? 256 is faster") # | |
| # preprocess_type = gr.Radio(['crop', 'resize','full'], value='full', label='preprocess', info="How to handle input image?") | |
| # with gr.Row(): | |
| # is_still_mode = gr.Checkbox(label="Still Mode (fewer head motion, works with preprocess `full`)") | |
| # facerender = gr.Radio(['facevid2vid'], value='facevid2vid', label='facerender', info="which face render?") | |
| # with gr.Row(): | |
| # # batch_size = gr.Slider(label="batch size in generation", step=1, maximum=10, value=1) | |
| # fps = gr.Slider(label='fps in generation', step=1, maximum=30, value =20) | |
| # enhancer = gr.Checkbox(label="GFPGAN as Face enhancer(slow)") | |
| with gr.Tabs(): | |
| with gr.TabItem('数字人问答'): | |
| gen_video = gr.Video(label="生成视频", format="mp4", autoplay=False) | |
| video_button = gr.Button("🎬 生成数字人视频", variant='primary') | |
| video_button.click(fn=Talker_response,inputs=[question_audio, talker_method, input_text, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character],outputs=[gen_video]) | |
| exmaple_setting(asr_method, input_text, character, talker_method, tts_method, voice, llm_method) | |
| return inference | |
| def app_multi(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) 多轮GPT对话")) | |
| with gr.Row(): | |
| with gr.Column(): | |
| (source_image, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| video = gr.Video(label = '数字人问答', scale = 0.5) | |
| video_button = gr.Button("🎬 生成数字人视频（对话后）", variant = 'primary') | |
| with gr.Column(): | |
| with gr.Tabs(elem_id="sadtalker_checkbox"): | |
| with gr.TabItem('SadTalker数字人参数设置'): | |
| with gr.Accordion("Advanced Settings", | |
| open=False): | |
| gr.Markdown("SadTalker: need help? please visit our [[best practice page](https://github.com/OpenTalker/SadTalker/blob/main/docs/best_practice.md)] for more detials") | |
| with gr.Column(variant='panel'): | |
| # width = gr.Slider(minimum=64, elem_id="img2img_width", maximum=2048, step=8, label="Manually Crop Width", value=512) # img2img_width | |
| # height = gr.Slider(minimum=64, elem_id="img2img_height", maximum=2048, step=8, label="Manually Crop Height", value=512) # img2img_width | |
| with gr.Row(): | |
| pose_style = gr.Slider(minimum=0, maximum=45, step=1, label="Pose style", value=0) # | |
| exp_weight = gr.Slider(minimum=0, maximum=3, step=0.1, label="expression scale", value=1) # | |
| blink_every = gr.Checkbox(label="use eye blink", value=True) | |
| with gr.Row(): | |
| size_of_image = gr.Radio([256, 512], value=256, label='face model resolution', info="use 256/512 model? 256 is faster") # | |
| preprocess_type = gr.Radio(['crop', 'resize','full', 'extcrop', 'extfull'], value='crop', label='preprocess', info="How to handle input image?") | |
| with gr.Row(): | |
| is_still_mode = gr.Checkbox(label="Still Mode (fewer head motion, works with preprocess `full`)") | |
| facerender = gr.Radio(['facevid2vid'], value='facevid2vid', label='facerender', info="which face render?") | |
| with gr.Row(): | |
| fps = gr.Slider(label='fps in generation', step=1, maximum=30, value =20) | |
| enhancer = gr.Checkbox(label="GFPGAN as Face enhancer(slow)") | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| system_input = gr.Textbox(value=default_system, lines=1, label='System (设定角色)') | |
| with gr.Column(scale=1): | |
| modify_system = gr.Button("🛠️ 设置system并清除历史对话", scale=2) | |
| system_state = gr.Textbox(value=default_system, visible=False) | |
| chatbot = gr.Chatbot(height=400, show_copy_button=True) | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label='语音对话', autoplay=False) | |
| asr_text = gr.Button('🎤 语音识别（语音对话后点击）') | |
| # 创建一个文本框组件，用于输入 prompt。 | |
| msg = gr.Textbox(label="Prompt/问题") | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[msg]) | |
| with gr.Row(): | |
| clear_history = gr.Button("🧹 清除历史对话") | |
| sumbit = gr.Button("🚀 发送", variant = 'primary') | |
| # 设置按钮的点击事件。当点击时，调用上面定义的 函数，并传入用户的消息和聊天历史记录，然后更新文本框和聊天机器人组件。 | |
| sumbit.click(chat_response, inputs=[system_input, msg, chatbot], | |
| outputs=[msg, chatbot]) | |
| # 点击后清空后端存储的聊天记录 | |
| clear_history.click(fn = clear_session, outputs = [msg, chatbot]) | |
| # 设置system并清除历史对话 | |
| modify_system.click(fn=modify_system_session, | |
| inputs=[system_input], | |
| outputs=[system_state, system_input, chatbot]) | |
| video_button.click(fn = human_response, inputs = [source_image, chatbot, question_audio, talker_method, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, character,preprocess_type, | |
| is_still_mode, enhancer, batch_size, size_of_image, | |
| pose_style, facerender, exp_weight, blink_every, fps], outputs = [video]) | |
| exmaple_setting(asr_method, msg, character, talker_method, tts_method, voice, llm_method) | |
| return inference | |
| def app_img(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) 个性化角色互动")) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant='panel'): | |
| (source_image, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| # driven_audio = 'answer.wav' | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.TabItem('对话'): | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label = '语音对话') | |
| input_text = gr.Textbox(label="输入文字/问题", lines=3) | |
| asr_text = gr.Button('语音识别（语音对话后点击）') | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[input_text]) | |
| with gr.Tabs(elem_id="text_examples"): | |
| gr.Markdown("## Text Examples") | |
| examples = [ | |
| ['应对压力最有效的方法是什么？'], | |
| ['如何进行时间管理？'], | |
| ['为什么有些人选择使用纸质地图或寻求方向，而不是依赖GPS设备或智能手机应用程序？'], | |
| ] | |
| gr.Examples( | |
| examples = examples, | |
| inputs = [input_text], | |
| ) | |
| with gr.Tabs(elem_id="sadtalker_checkbox"): | |
| with gr.TabItem('SadTalker数字人参数设置'): | |
| with gr.Accordion("Advanced Settings", | |
| open=False): | |
| gr.Markdown("SadTalker: need help? please visit our [[best practice page](https://github.com/OpenTalker/SadTalker/blob/main/docs/best_practice.md)] for more detials") | |
| with gr.Column(variant='panel'): | |
| # width = gr.Slider(minimum=64, elem_id="img2img_width", maximum=2048, step=8, label="Manually Crop Width", value=512) # img2img_width | |
| # height = gr.Slider(minimum=64, elem_id="img2img_height", maximum=2048, step=8, label="Manually Crop Height", value=512) # img2img_width | |
| with gr.Row(): | |
| pose_style = gr.Slider(minimum=0, maximum=45, step=1, label="Pose style", value=0) # | |
| exp_weight = gr.Slider(minimum=0, maximum=3, step=0.1, label="expression scale", value=1) # | |
| blink_every = gr.Checkbox(label="use eye blink", value=True) | |
| with gr.Row(): | |
| size_of_image = gr.Radio([256, 512], value=256, label='face model resolution', info="use 256/512 model? 256 is faster") # | |
| preprocess_type = gr.Radio(['crop', 'resize','full', 'extcrop', 'extfull'], value='crop', label='preprocess', info="How to handle input image?") | |
| with gr.Row(): | |
| is_still_mode = gr.Checkbox(label="Still Mode (fewer head motion, works with preprocess `full`)") | |
| facerender = gr.Radio(['facevid2vid'], value='facevid2vid', label='facerender', info="which face render?") | |
| with gr.Row(): | |
| fps = gr.Slider(label='fps in generation', step=1, maximum=30, value =20) | |
| enhancer = gr.Checkbox(label="GFPGAN as Face enhancer(slow)") | |
| with gr.Tabs(elem_id="sadtalker_genearted"): | |
| gen_video = gr.Video(label="数字人视频", format="mp4") | |
| submit = gr.Button('🎬 生成数字人视频', elem_id="sadtalker_generate", variant='primary') | |
| submit.click( | |
| fn=Talker_response_img, | |
| inputs=[question_audio, | |
| talker_method, | |
| input_text, | |
| voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, | |
| source_image, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer, | |
| batch_size, | |
| size_of_image, | |
| pose_style, | |
| facerender, | |
| exp_weight, | |
| blink_every, | |
| fps], | |
| outputs=[gen_video] | |
| ) | |
| with gr.Row(): | |
| examples = [ | |
| [ | |
| 'examples/source_image/full_body_2.png', 'SadTalker', | |
| 'crop', | |
| False, | |
| False | |
| ], | |
| [ | |
| 'examples/source_image/full_body_1.png', 'SadTalker', | |
| 'full', | |
| True, | |
| False | |
| ], | |
| [ | |
| 'examples/source_image/full4.jpeg', 'SadTalker', | |
| 'crop', | |
| False, | |
| True | |
| ], | |
| ] | |
| gr.Examples(examples=examples, | |
| inputs=[ | |
| source_image, talker_method, | |
| preprocess_type, | |
| is_still_mode, | |
| enhancer], | |
| outputs=[gen_video], | |
| # cache_examples=True, | |
| ) | |
| return inference | |
| def app_vits(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) 语音克隆")) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant='panel'): | |
| (source_image, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.TabItem('对话'): | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label = '语音对话') | |
| input_text = gr.Textbox(label="输入文字/问题", lines=3) | |
| asr_text = gr.Button('语音识别（语音对话后点击）') | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[input_text]) | |
| with gr.Tabs(): | |
| with gr.TabItem('数字人问答'): | |
| gen_video = gr.Video(label="数字人视频", format="mp4", autoplay=False) | |
| video_button = gr.Button("🎬 生成数字人视频", variant='primary') | |
| video_button.click(fn=Talker_response,inputs=[question_audio, talker_method, input_text, voice, rate, volume, pitch, am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character],outputs=[gen_video]) | |
| exmaple_setting(asr_method, input_text, character, talker_method, tts_method, voice, llm_method) | |
| return inference | |
| def app_talk(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) 数字人播报")) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.Tab("图片人物"): | |
| source_image = gr.Image(label='Source image', type = 'filepath') | |
| with gr.Tab("视频人物"): | |
| source_video = gr.Video(label="Source video") | |
| (_, voice, rate, volume, pitch, | |
| am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.TabItem('对话'): | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label = '语音对话') | |
| input_text = gr.Textbox(label="输入文字/问题", lines=3) | |
| asr_text = gr.Button('语音识别（语音对话后点击）') | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[input_text]) | |
| with gr.Tabs(): | |
| with gr.TabItem('SadTalker数字人参数设置'): | |
| with gr.Accordion("Advanced Settings", | |
| open=False): | |
| gr.Markdown("SadTalker: need help? please visit our [[best practice page](https://github.com/OpenTalker/SadTalker/blob/main/docs/best_practice.md)] for more detials") | |
| with gr.Column(variant='panel'): | |
| # width = gr.Slider(minimum=64, elem_id="img2img_width", maximum=2048, step=8, label="Manually Crop Width", value=512) # img2img_width | |
| # height = gr.Slider(minimum=64, elem_id="img2img_height", maximum=2048, step=8, label="Manually Crop Height", value=512) # img2img_width | |
| with gr.Row(): | |
| pose_style = gr.Slider(minimum=0, maximum=45, step=1, label="Pose style", value=0) # | |
| exp_weight = gr.Slider(minimum=0, maximum=3, step=0.1, label="expression scale", value=1) # | |
| blink_every = gr.Checkbox(label="use eye blink", value=True) | |
| with gr.Row(): | |
| size_of_image = gr.Radio([256, 512], value=256, label='face model resolution', info="use 256/512 model? 256 is faster") # | |
| preprocess_type = gr.Radio(['crop', 'resize','full'], value='full', label='preprocess', info="How to handle input image?") | |
| with gr.Row(): | |
| is_still_mode = gr.Checkbox(label="Still Mode (fewer head motion, works with preprocess `full`)") | |
| facerender = gr.Radio(['facevid2vid'], value='facevid2vid', label='facerender', info="which face render?") | |
| with gr.Row(): | |
| # batch_size = gr.Slider(label="batch size in generation", step=1, maximum=10, value=1) | |
| fps = gr.Slider(label='fps in generation', step=1, maximum=30, value =20) | |
| enhancer = gr.Checkbox(label="GFPGAN as Face enhancer(slow)") | |
| with gr.Tabs(): | |
| gen_video = gr.Video(label="数字人视频", format="mp4") | |
| video_button = gr.Button('🎬 生成数字人视频', elem_id="sadtalker_generate", variant='primary') | |
| video_button.click(fn=Talker_Say,inputs=[preprocess_type, is_still_mode, enhancer, batch_size, size_of_image, | |
| pose_style, facerender, exp_weight, blink_every, fps, | |
| source_image, source_video, question_audio, talker_method, input_text, voice, rate, volume, pitch, am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, character],outputs=[gen_video]) | |
| with gr.Row(): | |
| with gr.Column(variant='panel'): | |
| gr.Markdown("## Test Examples") | |
| gr.Examples( | |
| examples = [ | |
| [ | |
| 'examples/source_image/full_body_2.png', | |
| '应对压力最有效的方法是什么？', | |
| ], | |
| [ | |
| 'examples/source_image/full_body_1.png', | |
| '如何进行时间管理？', | |
| ], | |
| [ | |
| 'examples/source_image/full3.png', | |
| '为什么有些人选择使用纸质地图或寻求方向，而不是依赖GPS设备或智能手机应用程序？', | |
| ], | |
| ], | |
| fn = Talker_Say, | |
| inputs = [source_image, input_text], | |
| ) | |
| return inference | |
| def load_musetalk_model(): | |
| gr.Warning("若显存不足，可能会导致模型加载失败，可以尝试使用其他摸型或者换其他设备尝试。") | |
| gr.Info("MuseTalk模型导入中...") | |
| musetalker.init_model() | |
| gr.Info("MuseTalk模型导入成功") | |
| return "MuseTalk模型导入成功" | |
| def musetalk_prepare_material(source_video, bbox_shift): | |
| if musetalker.load is False: | |
| gr.Warning("请先加载MuseTalk模型后重新上传文件") | |
| return source_video, None | |
| return musetalker.prepare_material(source_video, bbox_shift) | |
| def app_muse(): | |
| with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference: | |
| gr.HTML(get_title("Linly 智能对话系统 (Linly-Talker) MuseTalker数字人实时对话")) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant='panel'): | |
| with gr.TabItem('MuseV Video'): | |
| gr.Markdown("MuseV: need help? please visit MuseVDemo to generate Video https://huggingface.co/spaces/AnchorFake/MuseVDemo") | |
| with gr.Row(): | |
| source_video = gr.Video(label="Reference Video",sources=['upload']) | |
| gr.Markdown("BBox_shift 推荐值下限，在生成初始结果后生成相应的 bbox 范围。如果结果不理想，可以根据该参考值进行调整。\n一般来说，在我们的实验观察中，我们发现正值（向下半部分移动）通常会增加嘴巴的张开度，而负值（向上半部分移动）通常会减少嘴巴的张开度。然而，需要注意的是，这并不是绝对的规则，用户可能需要根据他们的具体需求和期望效果来调整该参数。") | |
| with gr.Row(): | |
| bbox_shift = gr.Number(label="BBox_shift value, px", value=0) | |
| bbox_shift_scale = gr.Textbox(label="bbox_shift_scale", | |
| value="",interactive=False) | |
| load_musetalk = gr.Button("加载MuseTalk模型(传入视频前先加载)", variant='primary') | |
| load_musetalk.click(fn=load_musetalk_model, outputs=bbox_shift_scale) | |
| # (_, voice, rate, volume, pitch, | |
| # am, voc, lang, male, | |
| # inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| # tts_method, batch_size, character, talker_method, asr_method, llm_method)= webui_setting() | |
| with gr.Tabs("TTS Method"): | |
| with gr.Accordion("TTS Method语音方法调节 ", open=True): | |
| with gr.Tab("Edge-TTS"): | |
| voice = gr.Dropdown(edgetts.SUPPORTED_VOICE, | |
| value='zh-CN-XiaoxiaoNeural', | |
| label="Voice 声音选择") | |
| rate = gr.Slider(minimum=-100, | |
| maximum=100, | |
| value=0, | |
| step=1.0, | |
| label='Rate 速率') | |
| volume = gr.Slider(minimum=0, | |
| maximum=100, | |
| value=100, | |
| step=1, | |
| label='Volume 音量') | |
| pitch = gr.Slider(minimum=-100, | |
| maximum=100, | |
| value=0, | |
| step=1, | |
| label='Pitch 音调') | |
| with gr.Tab("PaddleTTS"): | |
| am = gr.Dropdown(["FastSpeech2"], label="声学模型选择", value = 'FastSpeech2') | |
| voc = gr.Dropdown(["PWGan", "HifiGan"], label="声码器选择", value = 'PWGan') | |
| lang = gr.Dropdown(["zh", "en", "mix", "canton"], label="语言选择", value = 'zh') | |
| male = gr.Checkbox(label="男声(Male)", value=False) | |
| with gr.Tab('GPT-SoVITS'): | |
| with gr.Row(): | |
| gpt_path = gr.FileExplorer(root = GPT_SoVITS_ckpt, glob = "*.ckpt", value = "s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt", file_count='single', label="GPT模型路径") | |
| sovits_path = gr.FileExplorer(root = GPT_SoVITS_ckpt, glob = "*.pth", value = "s2G488k.pth", file_count='single', label="SoVITS模型路径") | |
| # gpt_path = gr.Dropdown(choices=list_models(GPT_SoVITS_ckpt, 'ckpt')) | |
| # sovits_path = gr.Dropdown(choices=list_models(GPT_SoVITS_ckpt, 'pth')) | |
| # gpt_path = gr.Textbox(label="GPT模型路径", | |
| # value="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt") | |
| # sovits_path = gr.Textbox(label="SoVITS模型路径", | |
| # value="GPT_SoVITS/pretrained_models/s2G488k.pth") | |
| button = gr.Button("加载模型") | |
| button.click(fn = load_vits_model, | |
| inputs=[gpt_path, sovits_path], | |
| outputs=[gpt_path, sovits_path]) | |
| with gr.Row(): | |
| inp_ref = gr.Audio(label="请上传3~10秒内参考音频，超过会报错！", sources=["microphone", "upload"], type="filepath") | |
| use_mic_voice = gr.Checkbox(label="使用语音问答的麦克风") | |
| prompt_text = gr.Textbox(label="参考音频的文本", value="") | |
| prompt_language = gr.Dropdown( | |
| label="参考音频的语种", choices=["中文", "英文", "日文"], value="中文" | |
| ) | |
| asr_button = gr.Button("语音识别 - 克隆参考音频") | |
| asr_button.click(fn=Asr,inputs=[inp_ref],outputs=[prompt_text]) | |
| with gr.Row(): | |
| text_language = gr.Dropdown( | |
| label="需要合成的语种", choices=["中文", "英文", "日文", "中英混合", "日英混合", "多语种混合"], value="中文" | |
| ) | |
| how_to_cut = gr.Dropdown( | |
| label="怎么切", | |
| choices=["不切", "凑四句一切", "凑50字一切", "按中文句号。切", "按英文句号.切", "按标点符号切" ], | |
| value="凑四句一切", | |
| interactive=True, | |
| ) | |
| with gr.Column(variant='panel'): | |
| batch_size = gr.Slider(minimum=1, | |
| maximum=10, | |
| value=2, | |
| step=1, | |
| label='Talker Batch size') | |
| tts_method = gr.Radio(['Edge-TTS', 'PaddleTTS', 'GPT-SoVITS克隆声音', 'Comming Soon!!!'], label="Text To Speech Method", | |
| value = 'Edge-TTS') | |
| tts_method.change(fn = tts_model_change, inputs=[tts_method], outputs = [tts_method]) | |
| asr_method = gr.Radio(choices = ['Whisper-tiny', 'Whisper-base', 'FunASR', 'Comming Soon!!!'], value='Whisper-base', label = '语音识别模型选择') | |
| asr_method.change(fn = asr_model_change, inputs=[asr_method], outputs = [asr_method]) | |
| llm_method = gr.Dropdown(choices = ['Qwen', 'Qwen2', 'Linly', 'Gemini', 'ChatGLM', 'ChatGPT', 'GPT4Free', '直接回复 Direct Reply', 'Comming Soon!!!'], value = '直接回复 Direct Reply', label = 'LLM 模型选择') | |
| llm_method.change(fn = llm_model_change, inputs=[llm_method], outputs = [llm_method]) | |
| source_video.change(fn=musetalk_prepare_material, inputs=[source_video, bbox_shift], outputs=[source_video, bbox_shift_scale]) | |
| with gr.Column(variant='panel'): | |
| with gr.Tabs(): | |
| with gr.TabItem('对话'): | |
| with gr.Group(): | |
| question_audio = gr.Audio(sources=['microphone','upload'], type="filepath", label = '语音对话') | |
| input_text = gr.Textbox(label="输入文字/问题", lines=3) | |
| asr_text = gr.Button('语音识别（语音对话后点击）') | |
| asr_text.click(fn=Asr,inputs=[question_audio],outputs=[input_text]) | |
| with gr.TabItem("MuseTalk Video"): | |
| gen_video = gr.Video(label="数字人视频", format="mp4") | |
| submit = gr.Button('Generate', elem_id="sadtalker_generate", variant='primary') | |
| examples = [os.path.join('Musetalk/data/video', video) for video in os.listdir("Musetalk/data/video")] | |
| # ['Musetalk/data/video/yongen_musev.mp4', 'Musetalk/data/video/musk_musev.mp4', 'Musetalk/data/video/monalisa_musev.mp4', 'Musetalk/data/video/sun_musev.mp4', 'Musetalk/data/video/seaside4_musev.mp4', 'Musetalk/data/video/sit_musev.mp4', 'Musetalk/data/video/man_musev.mp4'] | |
| gr.Markdown("## MuseV Video Examples") | |
| gr.Examples( | |
| examples=[ | |
| ['Musetalk/data/video/yongen_musev.mp4', 5], | |
| ['Musetalk/data/video/musk_musev.mp4', 5], | |
| ['Musetalk/data/video/monalisa_musev.mp4', 5], | |
| ['Musetalk/data/video/sun_musev.mp4', 5], | |
| ['Musetalk/data/video/seaside4_musev.mp4', 5], | |
| ['Musetalk/data/video/sit_musev.mp4', 5], | |
| ['Musetalk/data/video/man_musev.mp4', 5] | |
| ], | |
| inputs =[source_video, bbox_shift], | |
| ) | |
| submit.click( | |
| fn=MuseTalker_response, | |
| inputs=[source_video, bbox_shift, question_audio, input_text, voice, rate, volume, pitch, am, voc, lang, male, | |
| inp_ref, prompt_text, prompt_language, text_language, how_to_cut, use_mic_voice, | |
| tts_method, batch_size], | |
| outputs=[gen_video] | |
| ) | |
| return inference | |
| def asr_model_change(model_name, progress=gr.Progress(track_tqdm=True)): | |
| global asr | |
| # 清理显存，在加载新的模型之前释放不必要的显存 | |
| clear_memory() | |
| if model_name == "Whisper-tiny": | |
| try: | |
| if os.path.exists('Whisper/tiny.pt'): | |
| asr = WhisperASR('Whisper/tiny.pt') | |
| else: | |
| asr = WhisperASR('tiny') | |
| gr.Info("Whisper-tiny模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"Whisper-tiny模型下载失败 {e}") | |
| elif model_name == "Whisper-base": | |
| try: | |
| if os.path.exists('Whisper/base.pt'): | |
| asr = WhisperASR('Whisper/base.pt') | |
| else: | |
| asr = WhisperASR('base') | |
| gr.Info("Whisper-base模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"Whisper-base模型下载失败 {e}") | |
| elif model_name == 'FunASR': | |
| try: | |
| from ASR import FunASR | |
| asr = FunASR() | |
| gr.Info("FunASR模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"FunASR模型下载失败 {e}") | |
| else: | |
| gr.Warning("未知ASR模型，可提issue和PR 或者 建议更新模型") | |
| return model_name | |
| def llm_model_change(model_name, progress=gr.Progress(track_tqdm=True)): | |
| global llm | |
| gemini_apikey = "" | |
| openai_apikey = "" | |
| proxy_url = None | |
| # 清理显存，在加载新的模型之前释放不必要的显存 | |
| clear_memory() | |
| if model_name == 'Linly': | |
| try: | |
| llm = llm_class.init_model('Linly', 'Linly-AI/Chinese-LLaMA-2-7B-hf', prefix_prompt=prefix_prompt) | |
| gr.Info("Linly模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"Linly模型下载失败 {e}") | |
| elif model_name == 'Qwen': | |
| try: | |
| llm = llm_class.init_model('Qwen', 'Qwen/Qwen-1_8B-Chat', prefix_prompt=prefix_prompt) | |
| gr.Info("Qwen模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"Qwen模型下载失败 {e}") | |
| elif model_name == 'Qwen2': | |
| try: | |
| llm = llm_class.init_model('Qwen2', 'Qwen/Qwen1.5-0.5B-Chat', prefix_prompt=prefix_prompt) | |
| gr.Info("Qwen2模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"Qwen2模型下载失败 {e}") | |
| elif model_name == 'Gemini': | |
| if gemini_apikey: | |
| llm = llm_class.init_model('Gemini', 'gemini-pro', gemini_apikey, proxy_url) | |
| gr.Info("Gemini模型导入成功") | |
| else: | |
| gr.Warning("请填写Gemini的api_key") | |
| elif model_name == 'ChatGLM': | |
| try: | |
| llm = llm_class.init_model('ChatGLM', 'THUDM/chatglm3-6b', prefix_prompt=prefix_prompt) | |
| gr.Info("ChatGLM模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"ChatGLM模型导入失败 {e}") | |
| elif model_name == 'ChatGPT': | |
| if openai_apikey: | |
| llm = llm_class.init_model('ChatGPT', api_key=openai_apikey, proxy_url=proxy_url, prefix_prompt=prefix_prompt) | |
| else: | |
| gr.Warning("请填写OpenAI的api_key") | |
| elif model_name == '直接回复 Direct Reply': | |
| llm =llm_class.init_model(model_name) | |
| gr.Info("直接回复，不实用LLM模型") | |
| elif model_name == 'GPT4Free': | |
| try: | |
| llm = llm_class.init_model('GPT4Free', prefix_prompt=prefix_prompt) | |
| gr.Info("GPT4Free模型导入成功, 请注意GPT4Free可能不稳定") | |
| except Exception as e: | |
| gr.Warning(f"GPT4Free模型下载失败 {e}") | |
| else: | |
| gr.Warning("未知LLM模型，可提issue和PR 或者 建议更新模型") | |
| return model_name | |
| def talker_model_change(model_name, progress=gr.Progress(track_tqdm=True)): | |
| global talker | |
| # 清理显存，在加载新的模型之前释放不必要的显存 | |
| clear_memory() | |
| if model_name not in ['SadTalker', 'Wav2Lip', 'NeRFTalk']: | |
| gr.Warning("其他模型还未集成，请等待") | |
| if model_name == 'SadTalker': | |
| try: | |
| from TFG import SadTalker | |
| talker = SadTalker(lazy_load=True) | |
| gr.Info("SadTalker模型导入成功") | |
| except Exception as e: | |
| gr.Warning("SadTalker模型加载失败", e) | |
| elif model_name == 'Wav2Lip': | |
| try: | |
| from TFG import Wav2Lip | |
| clear_memory() | |
| talker = Wav2Lip("checkpoints/wav2lip_gan.pth") | |
| gr.Info("Wav2Lip模型导入成功") | |
| except Exception as e: | |
| gr.Warning("Wav2Lip模型加载失败", e) | |
| elif model_name == 'NeRFTalk': | |
| try: | |
| from TFG import ERNeRF | |
| talker = ERNeRF() | |
| talker.init_model('checkpoints/Obama_ave.pth', 'checkpoints/Obama.json') | |
| gr.Info("NeRFTalk模型导入成功") | |
| gr.Warning("NeRFTalk模型是针对单个人进行训练的，内置了奥班马Obama的模型，上传图片无效") | |
| except Exception as e: | |
| gr.Warning("NeRFTalk模型加载失败", e) | |
| else: | |
| gr.Warning("未知TFG模型，可提issue和PR 或者 建议更新模型") | |
| return model_name | |
| def tts_model_change(model_name, progress=gr.Progress(track_tqdm=True)): | |
| global tts | |
| # 清理显存，在加载新的模型之前释放不必要的显存 | |
| clear_memory() | |
| if model_name == 'Edge-TTS': | |
| # tts = EdgeTTS() | |
| if edgetts.network: | |
| gr.Info("EdgeTTS模型导入成功") | |
| else: | |
| gr.Warning("EdgeTTS模型加载失败，请检查网络是否正常连接，否则无法使用") | |
| elif model_name == 'PaddleTTS': | |
| try: | |
| from TTS import PaddleTTS | |
| tts = PaddleTTS() | |
| gr.Info("PaddleTTS模型导入成功") | |
| except Exception as e: | |
| gr.Warning(f"PaddleTTS模型下载失败 {e}") | |
| elif model_name == 'GPT-SoVITS克隆声音': | |
| try: | |
| gpt_path = "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt" | |
| sovits_path = "GPT_SoVITS/pretrained_models/s2G488k.pth" | |
| vits.load_model(gpt_path, sovits_path) | |
| gr.Info("模型加载成功") | |
| except Exception as e: | |
| gr.Warning(f"模型加载失败 {e}") | |
| gr.Warning("注意注意⚠️：GPT-SoVITS要上传参考音频进行克隆，请点击TTS Method语音方法调节操作") | |
| else: | |
| gr.Warning("未知TTS模型，可提issue和PR 或者 建议更新模型") | |
| return model_name | |
| def success_print(text): | |
| print(f"\033[1;32;40m{text}\033[0m") | |
| def error_print(text): | |
| print(f"\033[1;31;40m{text}\033[0m") | |
| if __name__ == "__main__": | |
| llm_class = LLM(mode='offline') | |
| llm = llm_class.init_model('直接回复 Direct Reply') | |
| success_print("默认不使用LLM模型，直接回复问题，同时减少显存占用！") | |
| try: | |
| from VITS import * | |
| vits = GPT_SoVITS() | |
| success_print("Success!!! GPT-SoVITS模块加载成功，语音克隆默认使用GPT-SoVITS模型") | |
| # gpt_path = "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt" | |
| # sovits_path = "GPT_SoVITS/pretrained_models/s2G488k.pth" | |
| # vits.load_model(gpt_path, sovits_path) | |
| except Exception as e: | |
| error_print(f"GPT-SoVITS Error: {e}") | |
| error_print("如果使用VITS，请先下载GPT-SoVITS模型和安装环境") | |
| try: | |
| from TFG import SadTalker | |
| talker = SadTalker(lazy_load=True) | |
| success_print("Success!!! SadTalker模块加载成功，默认使用SadTalker模型") | |
| except Exception as e: | |
| error_print(f"SadTalker Error: {e}") | |
| error_print("如果使用SadTalker，请先下载SadTalker模型") | |
| try: | |
| from ASR import WhisperASR | |
| if os.path.exists('Whisper/base.pt'): | |
| asr = WhisperASR('Whisper/base.pt') | |
| else: | |
| asr = WhisperASR('base') | |
| success_print("Success!!! WhisperASR模块加载成功，默认使用Whisper-base模型") | |
| except Exception as e: | |
| error_print(f"ASR Error: {e}") | |
| error_print("如果使用FunASR，请先下载WhisperASR模型和安装环境") | |
| # 判断显存是否8g，若小于8g不建议使用MuseTalk功能 | |
| # Check if GPU is available and has at least 8GB of memory | |
| if torch.cuda.is_available(): | |
| gpu_memory = torch.cuda.get_device_properties(0).total_memory / (1024 ** 3) # Convert bytes to GB | |
| if gpu_memory < 8: | |
| error_print("警告: 您的显卡显存小于8GB，不建议使用MuseTalk功能") | |
| try: | |
| from TFG import MuseTalk_RealTime | |
| musetalker = MuseTalk_RealTime() | |
| success_print("Success!!! MuseTalk模块加载成功") | |
| except Exception as e: | |
| error_print(f"MuseTalk Error: {e}") | |
| error_print("如果使用MuseTalk，请先下载MuseTalk模型") | |
| tts = edgetts | |
| if not tts.network: | |
| error_print("EdgeTTS模块加载失败，请检查网络是否正常连接，否则无法使用") | |
| gr.close_all() | |
| # demo_app = app() | |
| demo_img = app_img() | |
| demo_multi = app_multi() | |
| # demo_vits = app_vits() | |
| # demo_talk = app_talk() | |
| demo_muse = app_muse() | |
| demo = gr.TabbedInterface(interface_list = [ | |
| # demo_app, | |
| demo_img, | |
| demo_multi, | |
| # demo_vits, | |
| # demo_talk, | |
| demo_muse, | |
| ], | |
| tab_names = [ | |
| "个性化角色互动", | |
| "数字人多轮智能对话", | |
| "MuseTalk数字人实时对话" | |
| ], | |
| title = "Linly-Talker WebUI") | |
| demo.queue() | |
| demo.launch(server_name=ip, # 本地端口localhost:127.0.0.1 全局端口转发:"0.0.0.0" | |
| server_port=port, | |
| # 似乎在Gradio4.0以上版本可以不使用证书也可以进行麦克风对话 | |
| # ssl_certfile=ssl_certfile, | |
| # ssl_keyfile=ssl_keyfile, | |
| # ssl_verify=False, | |
| # share=True, | |
| debug=True, | |
| ) |