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| import os | |
| import time | |
| import gradio as gr | |
| import soundfile | |
| import torch | |
| import infer_tool | |
| convert_cnt = [0] | |
| dev = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| # model_name = "83_epochs.pth" | |
| model_name = "mg_1255_epochs_v0.0.6.pth" | |
| config_name = "milky_green.json" | |
| net_g_ms, hubert_soft, feature_input, hps_ms = infer_tool.load_model(f"{model_name}", f"configs/{config_name}") | |
| # 获取config参数 | |
| target_sample = hps_ms.data.sampling_rate | |
| spk_dict = { | |
| "明前奶绿": 0, | |
| "云灏": 2, | |
| "即霜": 3, | |
| "奕兰秋": 4 | |
| } | |
| def list_models(): | |
| global model_name | |
| res = [] | |
| dir = os.getcwd() | |
| for f in os.listdir(dir): | |
| if(f.startswith("D_")): | |
| continue | |
| if(f.endswith(".pth")): | |
| res.append(f) | |
| if len(f) >= len(model_name): | |
| model_name = f | |
| return res | |
| def vc_fn(sid, audio_record, audio_upload, tran): | |
| print(sid, time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())) | |
| if audio_upload is not None: | |
| audio_path = audio_upload | |
| elif audio_record is not None: | |
| audio_path = audio_record | |
| else: | |
| return "你需要上传wav文件或使用网页内置的录音！", None | |
| audio, sampling_rate = infer_tool.format_wav(audio_path, target_sample) | |
| duration = audio.shape[0] / sampling_rate | |
| if duration > 600: | |
| return "请上传小于600s的音频，需要转换长音频请使用colab", None | |
| o_audio, out_sr = infer_tool.infer(audio_path, spk_dict[sid], tran, net_g_ms, hubert_soft, feature_input) | |
| out_path = f"./out_temp.wav" | |
| soundfile.write(out_path, o_audio, target_sample) | |
| infer_tool.f0_plt(audio_path, out_path, tran, hubert_soft, feature_input) | |
| mistake, var = infer_tool.calc_error(audio_path, out_path, tran, feature_input) | |
| return f"半音偏差：{mistake}\n半音方差：{var}", ( | |
| target_sample, o_audio), gr.Image.update("temp.jpg") | |
| def change_model(model): | |
| global model_name | |
| global net_g_ms | |
| global hubert_soft | |
| global feature_input | |
| global hps_ms | |
| model_name = model | |
| net_g_ms, hubert_soft, feature_input, hps_ms = infer_tool.load_model(f"{model_name}", f"configs/{config_name}") | |
| return "载入模型："+model_name | |
| available_models = list_models() | |
| app = gr.Blocks() | |
| with app: | |
| with gr.Tabs(): | |
| with gr.TabItem("Basic"): | |
| gr.Markdown(value=""" | |
| 本模型为 [sovits_f0](https://huggingface.co/spaces/innnky/nyaru-svc2.0-advanced) 魔改。含AI奶绿（aka. [明前奶绿](https://space.bilibili.com/2132180406)）音色，支持**60s以内**的**无伴奏**wav、mp3（单声道）格式，或使用**网页内置**的录音（二选一） | |
| 转换效果取决于源音频语气、节奏是否与目标音色相近，以及音域是否超出目标音色音域范围 | |
| 奶绿高音数据效果稍差，一些音高过高的需要考虑降调 | |
| 该模型基于 [innnky/so-vits-svc](https://github.com/innnky/so-vits-svc)，如果想自己制作并训练模型可以访问这个 [GitHub 仓库](https://github.com/IceKyrin/sovits_guide) | |
| """) | |
| model_selected = gr.Dropdown(choices=available_models, label = "模型", value=model_name) | |
| current_model_text = gr.Markdown("") | |
| model_selected.change(change_model, inputs=[model_selected], outputs=[current_model_text]) | |
| speaker_id = gr.Dropdown(label="音色", choices=['明前奶绿'], value="明前奶绿") | |
| record_input = gr.Audio(source="microphone", label="录制你的声音", type="filepath", elem_id="audio_inputs") | |
| upload_input = gr.Audio(source="upload", label="上传音频（长度小于60秒）", type="filepath", | |
| elem_id="audio_inputs") | |
| vc_transform = gr.Number(label="升降半音（整数，可以正负，半音数量，升高八度就是12）", value=0) | |
| vc_submit = gr.Button("转换", variant="primary") | |
| out_audio = gr.Audio(label="Output Audio") | |
| gr.Markdown(value=""" | |
| 输出信息为音高平均偏差半音数量，体现转换音频的跑调情况（一般平均小于0.5个半音） | |
| """) | |
| out_message = gr.Textbox(label="跑调误差信息") | |
| gr.Markdown(value="""f0曲线可以直观的显示跑调情况，蓝色为输入音高，橙色为合成音频的音高 | |
| 若**只看见橙色**，说明蓝色曲线被覆盖，转换效果较好 | |
| """) | |
| f0_image = gr.Image(label="f0曲线") | |
| vc_submit.click(vc_fn, [speaker_id, record_input, upload_input, vc_transform], | |
| [out_message, out_audio, f0_image]) | |
| with gr.TabItem("使用说明"): | |
| gr.Markdown(value=""" | |
| 0、合集：https://github.com/IceKyrin/sovits_guide/blob/main/README.md | |
| 1、仅支持sovit_f0（sovits2.0）模型 | |
| 2、自行下载hubert-soft-0d54a1f4.pt改名为hubert.pt放置于pth文件夹下（已经下好了） | |
| https://github.com/bshall/hubert/releases/tag/v0.1 | |
| 3、pth文件夹下放置sovits2.0的模型 | |
| 4、与模型配套的xxx.json，需有speaker项——人物列表 | |
| 5、放无伴奏的音频、或网页内置录音，不要放奇奇怪怪的格式 | |
| 6、仅供交流使用，不对用户行为负责 | |
| """) | |
| app.launch() | |