192 lines
9.3 KiB
Python
192 lines
9.3 KiB
Python
import os
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import yaml
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import gradio as gr
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import asyncio
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import requests
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from inferenceapi import setup_args, inference
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from thirdparty.edgetts.azuretts import textToSpeechAsync, SUPPORTED_VOICES as AZURE_SUPPORTED_VOICES
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from thirdparty.aliyun.aliyuntts import aliyun_text_to_speech, SUPPORTED_VOICES as ALIYUN_SUPPORTED_VOICES
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from thirdparty.ui.gradiotheme import EnhancedSeafoam
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# 安装 PyYAML 库
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# pip install pyyaml
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# 加载Avatar配置文件
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def load_avatar_configs(config_file="avatar_configs.yaml"):
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with open(config_file, "r", encoding="utf-8") as f:
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data = yaml.safe_load(f)
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return data
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avatar_data = load_avatar_configs()
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avatars = avatar_data["avatars"]
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# 定义全局模型缓存字典
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models = {}
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# 获取所有音频文件的唯一列表，用于下拉菜单和上传组件
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all_audios = list(set(aud for avatar in avatars for aud in avatar["config"]["audios"]))
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def run_inference(path, workspace, seed, test, test_train, aud):
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args_dict = {
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"path": path,
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"workspace": workspace,
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"seed": seed,
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"test": test,
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"test_train": test_train,
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"aud": aud
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}
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opt = setup_args(None, args_dict)
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assert os.path.exists(opt.workspace), "Workspace directory does not exist."
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assert os.path.exists(opt.path), "Dataset path does not exist."
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video_path = inference(opt)
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return video_path
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def update_params(avatar_index):
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config = avatars[avatar_index]["config"]
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default_audio = config['audios'][0] if config['audios'] else all_audios[0]
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return config["path"], config["workspace"], config["seed"], default_audio
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def find_examples(folder_path, extensions):
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full_path = os.path.abspath(folder_path)
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examples = []
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for f in os.listdir(full_path):
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if f.endswith(extensions):
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file_path = os.path.join(full_path, f)
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if os.path.exists(file_path):
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examples.append(file_path)
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else:
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print(f"Warning: File not found: {file_path}")
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return examples
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base_dir = os.path.dirname(os.path.abspath(__file__))
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audio_folder = os.path.join(base_dir, "assets", "")
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audio_examples = find_examples(audio_folder, ('.mp3', '.wav', '.ogg'))
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def save_uploaded_audio(file):
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if not os.path.exists("assets"):
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os.makedirs("assets")
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file_path = os.path.join("assets", "temp_input.wav")
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with open(file_path, "wb") as f:
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f.write(file.read())
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return file_path
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def textToSpeechUnifiedAzure(text, voice, rate, volume):
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return asyncio.run(textToSpeechAsync(text, voice, rate, volume))
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def textToSpeechUnifiedAliyun(text, voice, rate, volume):
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return asyncio.run(aliyun_text_to_speech(text, voice, rate, volume))[1]
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def textToSpeechUnifiedCosy(text, sft_name="康辉", speaker_name="", prompt_text="", prompt_speech=""):
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url = "http://localhost:8000/inference/tts"
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headers = {"accept": "application/json", "Content-Type": "application/json"}
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data = {"query": text, "speaker_name": speaker_name, "sft_name": sft_name, "prompt_text": prompt_text, "prompt_speech": prompt_speech}
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response = requests.post(url, headers=headers, json=data)
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if response.status_code == 200:
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audio_content = response.content
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file_path = f"assets/cosy_tmp.wav"
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with open(file_path, "wb") as f:
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f.write(audio_content)
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return file_path
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else:
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raise Exception(f"CosyVoice TTS request failed with status {response.status_code}")
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enhanced_seafoam = EnhancedSeafoam()
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logo_path = os.path.join(base_dir, "assets", "company_logo_small_1.png")
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def get_version_details():
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with open("version_history.md", "r", encoding="utf-8") as markdown_file:
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version_details = markdown_file.read()
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return version_details
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def gradio_interface():
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with gr.Blocks(css="""footer {display: none !important;} #audio_button {color: black !important;} #output_video {color: blue !important;} """, theme=enhanced_seafoam) as app:
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logo = gr.Image(logo_path, show_label=False, container=False)
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gr.Markdown('<h1 style="text-align: center;">真人复刻数字人 v1.2</h1>', elem_id="title")
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gr.Markdown('<p style="text-align: center;">Choose an avatar and configure parameters for generating animated models based on speech.</p>', elem_id="subtitle")
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with gr.Accordion("版本更新说明", open=False):
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gr.Markdown(get_version_details())
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gr.Markdown('<p style="text-align: center;">本应用仅供测试体验，非法版权人像传播引起的一切后果请自行承担！</p>', elem_id="subtitle")
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown("### Choose Avatar")
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avatar_gallery = gr.Gallery(label="Avatar Preview", value=[(avatar['photo'], avatar['name']) for avatar in avatars])
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with gr.Column(scale=1):
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output_video = gr.Video(label="Inference Result", elem_id="output_video")
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gr.Markdown("### Input Audio驱动用的音频，以下三种方式三选一")
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with gr.Row():
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audio_output = gr.Audio(label="Upload Audio上传或者麦克风录制语音", type="filepath")
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with gr.Column(scale=1):
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gr.Examples(examples=[[audio] for audio in audio_examples], inputs=[audio_output], label="Audio Examples", elem_id="audio_button")
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with gr.Column(scale=2):
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with gr.Tabs():
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with gr.Tab("CosyVoice TTS（声音复刻，本地部署）"):
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with gr.Column():
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cosy_input_text = gr.Textbox(label="Input Text for CosyVoice TTS")
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cosy_speaker_name = gr.Dropdown(choices=["康辉", "rayray","其他可用说话人"], label="Speaker Name")
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cosy_generate = gr.Button("点击语音合成")
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with gr.Tab("Aliyun TTS（推荐）"):
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with gr.Column():
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aliyun_input_text = gr.Textbox(label="Input Text for Aliyun TTS")
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aliyun_voice = gr.Dropdown(choices=list(ALIYUN_SUPPORTED_VOICES.keys()), label="Aliyun TTS Voice")
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aliyun_generate = gr.Button("点击语音合成")
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with gr.Tab("Azure TTS (海外不稳定)"):
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with gr.Column():
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azure_input_text = gr.Textbox(label="Input Text for Azure TTS")
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azure_voice = gr.Dropdown(choices=list(AZURE_SUPPORTED_VOICES.keys()), label="Azure TTS Voice")
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azure_generate = gr.Button("点击语音合成")
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cosy_generate.click(textToSpeechUnifiedCosy, inputs=[cosy_input_text, cosy_speaker_name], outputs=audio_output)
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def handle_uploaded_audio(file):
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if isinstance(file, str): return file
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else: return save_uploaded_audio(file)
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audio_output.change(fn=handle_uploaded_audio, inputs=[audio_output], outputs=[audio_output])
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with gr.Row():
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with gr.Accordion("Basic Parameters", open=False):
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path_input = gr.Textbox(label="Data Path", value=avatars[0]["config"]["path"])
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workspace_input = gr.Textbox(label="Workspace Directory", value=avatars[0]["config"]["workspace"])
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seed_input = gr.Number(label="Random Seed", value=avatars[0]["config"]["seed"], precision=0)
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test_input = gr.Checkbox(label="Test Mode", value=True)
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test_train_input = gr.Checkbox(label="Test Train Mode", value=True)
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with gr.Accordion("TTS Advanced Settings语音TTS高级设置", open=False):
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tts_rate = gr.Slider(-100, 100, value=0, label="Speech Rate")
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tts_volume = gr.Slider(-100, 100, value=0, label="Volume")
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run_button = gr.Button("生成")
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def select_avatar(evt: gr.SelectData):
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return update_params(evt.index)
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avatar_gallery.select(fn=select_avatar, inputs=[], outputs=[path_input, workspace_input, seed_input, audio_output])
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azure_generate.click(
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textToSpeechUnifiedAzure,
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inputs=[azure_input_text, azure_voice, tts_rate, tts_volume],
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outputs=audio_output
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)
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aliyun_generate.click(
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textToSpeechUnifiedAliyun,
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inputs=[aliyun_input_text, aliyun_voice, tts_rate, tts_volume],
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outputs=audio_output
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)
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# 事件绑定：运行推理
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run_button.click(
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fn=run_inference,
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inputs=[path_input, workspace_input, seed_input, test_input, test_train_input, audio_output],
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outputs=output_video
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)
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gr.HTML("""
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<div align="center" style="text-align: center; font-size: 12px;">
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<p style="display: inline; margin-right: 10px;">© 2024 未来式智能</p>
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<a href="https://agentspro.cn/" target="_blank" style="display: inline;">autoagents.ai</a>
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</div>
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""")
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return app
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if __name__ == "__main__":
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# 启动Gradio服务
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app = gradio_interface()
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app.queue(max_size=20)
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app.launch(server_name="0.0.0.0", server_port=8080, share=True) |