Create inference.py

app/tabs/inference.py

@@ -0,0 +1,301 @@
+import gradio as gr
+from original import *
+
+
+def infer_tabs():
+    with gr.TabItem(i18n("模型推理")):
+            with gr.Row():
+                sid0 = gr.Dropdown(label=i18n("推理音色"), choices=sorted(names))
+                with gr.Column():
+                    refresh_button = gr.Button(
+                        i18n("刷新音色列表和索引路径"), variant="primary"
+                    )
+                    clean_button = gr.Button(i18n("卸载音色省显存"), variant="primary")
+                spk_item = gr.Slider(
+                    minimum=0,
+                    maximum=2333,
+                    step=1,
+                    label=i18n("请选择说话人id"),
+                    value=0,
+                    visible=False,
+                    interactive=True,
+                )
+                clean_button.click(
+                    fn=clean, inputs=[], outputs=[sid0], api_name="infer_clean"
+                )
+            with gr.TabItem(i18n("单次推理")):
+                with gr.Group():
+                    with gr.Row():
+                        with gr.Column():
+                            vc_transform0 = gr.Number(
+                                label=i18n("变调(整数, 半音数量, 升八度12降八度-12)"),
+                                value=0,
+                            )
+                            input_audio0 = gr.Textbox(
+                                label=i18n(
+                                    "输入待处理音频文件路径(默认是正确格式示例)"
+                                ),
+                                placeholder="C:\\Users\\Desktop\\audio_example.wav",
+                            )
+                            file_index1 = gr.Textbox(
+                                label=i18n(
+                                    "特征检索库文件路径,为空则使用下拉的选择结果"
+                                ),
+                                placeholder="C:\\Users\\Desktop\\model_example.index",
+                                interactive=True,
+                            )
+                            file_index2 = gr.Dropdown(
+                                label=i18n("自动检测index路径,下拉式选择(dropdown)"),
+                                choices=sorted(index_paths),
+                                interactive=True,
+                            )
+                            f0method0 = gr.Radio(
+                                label=i18n(
+                                    "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
+                                ),
+                                choices=(
+                                    ["pm", "harvest", "crepe", "rmvpe"]
+                                    if config.dml == False
+                                    else ["pm", "harvest", "rmvpe"]
+                                ),
+                                value="rmvpe",
+                                interactive=True,
+                            )
+
+                        with gr.Column():
+                            resample_sr0 = gr.Slider(
+                                minimum=0,
+                                maximum=48000,
+                                label=i18n("后处理重采样至最终采样率，0为不进行重采样"),
+                                value=0,
+                                step=1,
+                                interactive=True,
+                            )
+                            rms_mix_rate0 = gr.Slider(
+                                minimum=0,
+                                maximum=1,
+                                label=i18n(
+                                    "输入源音量包络替换输出音量包络融合比例，越靠近1越使用输出包络"
+                                ),
+                                value=0.25,
+                                interactive=True,
+                            )
+                            protect0 = gr.Slider(
+                                minimum=0,
+                                maximum=0.5,
+                                label=i18n(
+                                    "保护清辅音和呼吸声，防止电音撕裂等artifact，拉满0.5不开启，调低加大保护力度但可能降低索引效果"
+                                ),
+                                value=0.33,
+                                step=0.01,
+                                interactive=True,
+                            )
+                            filter_radius0 = gr.Slider(
+                                minimum=0,
+                                maximum=7,
+                                label=i18n(
+                                    ">=3则使用对harvest音高识别的结果使用中值滤波，数值为滤波半径，使用可以削弱哑音"
+                                ),
+                                value=3,
+                                step=1,
+                                interactive=True,
+                            )
+                            index_rate1 = gr.Slider(
+                                minimum=0,
+                                maximum=1,
+                                label=i18n("检索特征占比"),
+                                value=0.75,
+                                interactive=True,
+                            )
+                            f0_file = gr.File(
+                                label=i18n(
+                                    "F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调"
+                                ),
+                                visible=False,
+                            )
+
+                            refresh_button.click(
+                                fn=change_choices,
+                                inputs=[],
+                                outputs=[sid0, file_index2],
+                                api_name="infer_refresh",
+                            )
+                            # file_big_npy1 = gr.Textbox(
+                            #     label=i18n("特征文件路径"),
+                            #     value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
+                            #     interactive=True,
+                            # )
+                with gr.Group():
+                    with gr.Column():
+                        but0 = gr.Button(i18n("转换"), variant="primary")
+                        with gr.Row():
+                            vc_output1 = gr.Textbox(label=i18n("输出信息"))
+                            vc_output2 = gr.Audio(
+                                label=i18n("输出音频(右下角三个点,点了可以下载)")
+                            )
+
+                        but0.click(
+                            vc.vc_single,
+                            [
+                                spk_item,
+                                input_audio0,
+                                vc_transform0,
+                                f0_file,
+                                f0method0,
+                                file_index1,
+                                file_index2,
+                                # file_big_npy1,
+                                index_rate1,
+                                filter_radius0,
+                                resample_sr0,
+                                rms_mix_rate0,
+                                protect0,
+                            ],
+                            [vc_output1, vc_output2],
+                            api_name="infer_convert",
+                        )
+            with gr.TabItem(i18n("批量推理")):
+                gr.Markdown(
+                    value=i18n(
+                        "批量转换, 输入待转换音频文件夹, 或上传多个音频文件, 在指定文件夹(默认opt)下输出转换的音频. "
+                    )
+                )
+                with gr.Row():
+                    with gr.Column():
+                        vc_transform1 = gr.Number(
+                            label=i18n("变调(整数, 半音数量, 升八度12降八度-12)"),
+                            value=0,
+                        )
+                        opt_input = gr.Textbox(
+                            label=i18n("指定输出文件夹"), value="opt"
+                        )
+                        file_index3 = gr.Textbox(
+                            label=i18n("特征检索库文件路径,为空则使用下拉的选择结果"),
+                            value="",
+                            interactive=True,
+                        )
+                        file_index4 = gr.Dropdown(
+                            label=i18n("自动检测index路径,下拉式选择(dropdown)"),
+                            choices=sorted(index_paths),
+                            interactive=True,
+                        )
+                        f0method1 = gr.Radio(
+                            label=i18n(
+                                "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
+                            ),
+                            choices=(
+                                ["pm", "harvest", "crepe", "rmvpe"]
+                                if config.dml == False
+                                else ["pm", "harvest", "rmvpe"]
+                            ),
+                            value="rmvpe",
+                            interactive=True,
+                        )
+                        format1 = gr.Radio(
+                            label=i18n("导出文件格式"),
+                            choices=["wav", "flac", "mp3", "m4a"],
+                            value="wav",
+                            interactive=True,
+                        )
+
+                        refresh_button.click(
+                            fn=lambda: change_choices()[1],
+                            inputs=[],
+                            outputs=file_index4,
+                            api_name="infer_refresh_batch",
+                        )
+                        # file_big_npy2 = gr.Textbox(
+                        #     label=i18n("特征文件路径"),
+                        #     value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
+                        #     interactive=True,
+                        # )
+
+                    with gr.Column():
+                        resample_sr1 = gr.Slider(
+                            minimum=0,
+                            maximum=48000,
+                            label=i18n("后处理重采样至最终采样率，0为不进行重采样"),
+                            value=0,
+                            step=1,
+                            interactive=True,
+                        )
+                        rms_mix_rate1 = gr.Slider(
+                            minimum=0,
+                            maximum=1,
+                            label=i18n(
+                                "输入源音量包络替换输出音量包络融合比例，越靠近1越使用输出包络"
+                            ),
+                            value=1,
+                            interactive=True,
+                        )
+                        protect1 = gr.Slider(
+                            minimum=0,
+                            maximum=0.5,
+                            label=i18n(
+                                "保护清辅音和呼吸声，防止电音撕裂等artifact，拉满0.5不开启，调低加大保护力度但可能降低索引效果"
+                            ),
+                            value=0.33,
+                            step=0.01,
+                            interactive=True,
+                        )
+                        filter_radius1 = gr.Slider(
+                            minimum=0,
+                            maximum=7,
+                            label=i18n(
+                                ">=3则使用对harvest音高识别的结果使用中值滤波，数值为滤波半径，使用可以削弱哑音"
+                            ),
+                            value=3,
+                            step=1,
+                            interactive=True,
+                        )
+                        index_rate2 = gr.Slider(
+                            minimum=0,
+                            maximum=1,
+                            label=i18n("检索特征占比"),
+                            value=1,
+                            interactive=True,
+                        )
+                with gr.Row():
+                    dir_input = gr.Textbox(
+                        label=i18n(
+                            "输入待处理音频文件夹路径(去文件管理器地址栏拷就行了)"
+                        ),
+                        placeholder="C:\\Users\\Desktop\\input_vocal_dir",
+                    )
+                    inputs = gr.File(
+                        file_count="multiple",
+                        label=i18n("也可批量输入音频文件, 二选一, 优先读文件夹"),
+                    )
+
+                with gr.Row():
+                    but1 = gr.Button(i18n("转换"), variant="primary")
+                    vc_output3 = gr.Textbox(label=i18n("输出信息"))
+
+                    but1.click(
+                        vc.vc_multi,
+                        [
+                            spk_item,
+                            dir_input,
+                            opt_input,
+                            inputs,
+                            vc_transform1,
+                            f0method1,
+                            file_index3,
+                            file_index4,
+                            # file_big_npy2,
+                            index_rate2,
+                            filter_radius1,
+                            resample_sr1,
+                            rms_mix_rate1,
+                            protect1,
+                            format1,
+                        ],
+                        [vc_output3],
+                        api_name="infer_convert_batch",
+                    )
+                sid0.change(
+                    fn=vc.get_vc,
+                    inputs=[sid0, protect0, protect1],
+                    outputs=[spk_item, protect0, protect1, file_index2, file_index4],
+                    api_name="infer_change_voice",
+                )