get rid of i18n requirement

app.py

@@ -31,7 +31,6 @@ os.makedirs(os.path.join(now_dir, "weights"), exist_ok=True)
 os.environ["TEMP"] = tmp
 warnings.filterwarnings("ignore")
 torch.manual_seed(114514)
-from i18n import I18nAuto
 
 import edge_tts, asyncio
 from ilariatts import tts_order_voice
@@ -175,7 +174,7 @@ def update_fshift_presets(preset, qfrency, tmbre):
         {"value": tmbre, "__type__": "update"},
     )
 
-i18n = I18nAuto()
+# i18n = I18nAuto()
 #i18n.print()
 # 判断是否有能用来训练和加速推理的N卡
 ngpu = torch.cuda.device_count()
@@ -221,7 +220,7 @@ if if_gpu_ok == True and len(gpu_infos) > 0:
     gpu_info = "\n".join(gpu_infos)
     default_batch_size = min(mem) // 2
 else:
-    gpu_info = i18n("很遗憾您这没有能用的显卡来支持您训练")
+    gpu_info = "test"
     default_batch_size = 1
 gpus = "-".join([i[0] for i in gpu_infos])
 from lib.infer_pack.models import (
@@ -984,7 +983,7 @@ def train1key(
         % (trainset_dir4, sr_dict[sr2], np7, model_log_dir)
         + str(config.noparallel)
     )
-    yield get_info_str(i18n("step1:正在处理数据"))
+    yield get_info_str("step1: step 1")
     yield get_info_str(cmd)
     p = Popen(cmd, shell=True)
     p.wait()
@@ -1006,9 +1005,9 @@ def train1key(
         with open(extract_f0_feature_log_path, "r") as f:
             print(f.read())
     else:
-        yield get_info_str(i18n("step2a:无需提取音高"))
+        yield get_info_str("step2a:step2a")
     #######step2b:提取特征
-    yield get_info_str(i18n("step2b:正在提取特征"))
+    yield get_info_str("step2b:step2b")
     gpus = gpus16.split("-")
     leng = len(gpus)
     ps = []
@@ -1031,7 +1030,7 @@ def train1key(
     with open(extract_f0_feature_log_path, "r") as f:
         print(f.read())
     #######step3a:训练模型
-    yield get_info_str(i18n("step3a:正在训练模型"))
+    yield get_info_str("step3a:step3a")
     # 生成filelist
     if if_f0_3:
         f0_dir = "%s/2a_f0" % model_log_dir
@@ -1133,7 +1132,7 @@ def train1key(
     yield get_info_str(cmd)
     p = Popen(cmd, shell=True, cwd=now_dir)
     p.wait()
-    yield get_info_str(i18n("训练结束, 您可查看控制台训练日志或实验文件夹下的train.log"))
+    yield get_info_str("training done, in train.log")
     #######step3b:训练索引
     npys = []
     listdir_res = list(os.listdir(feature_dir))
@@ -1173,7 +1172,7 @@ def train1key(
         "成功构建索引, added_IVF%s_Flat_nprobe_%s_%s_%s.index"
         % (n_ivf, index_ivf.nprobe, exp_dir1, version19)
     )
-    yield get_info_str(i18n("全流程结束！"))
+    yield get_info_str("yes!")
 
 
 def whethercrepeornah(radio):
@@ -1649,7 +1648,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                     minimum=0,
                     maximum=2333,
                     step=1,
-                    label=i18n("请选择说话人id"),
+                    label="speaker id",
                     value=0,
                     visible=False,
                     interactive=True,
@@ -1776,7 +1775,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                             index_rate1 = gr.Slider(
                                 minimum=0,
                                 maximum=1,
-                                label=i18n("检索特征占比"),
+                                label="index rate",
                                 value=0,
                                 interactive=True,
                                 )
@@ -1804,7 +1803,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="label",
                             value=3,
                             step=1,
                             interactive=True,
@@ -1812,7 +1811,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="label",
                             value=0,
                             step=1,
                             interactive=True,
@@ -1821,14 +1820,14 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="label",
                             value=0.21,
                             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"),
+                            label="label",
                             value=0,
                             step=0.01,
                             interactive=True,
@@ -1884,7 +1883,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
             
             with gr.Row():
                 vc_output1 = gr.Textbox("")
-                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)
+                f0_file = gr.File(label="f0 file", visible=False)
                 
                 but0.click(
                     vc_single,
@@ -1911,13 +1910,11 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                 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
+                            label="speaker id", value=0
                         )
-                        opt_input = gr.Textbox(label=i18n("指定输出文件夹"), value="opt")
+                        opt_input = gr.Textbox(label="opt", value="opt")
                         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"
-                            ),
+                            label="f0 method",
                             choices=["pm", "harvest", "crepe", "rmvpe"],
                             value="rmvpe",
                             interactive=True,
@@ -1925,19 +1922,19 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="harvest",
                             value=3,
                             step=1,
                             interactive=True,
                         )
                     with gr.Column():
                         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"),
+                            label="file index",
                             value="",
                             interactive=True,
                         )
                         file_index4 = gr.Dropdown(
-                            label=i18n("自动检测index路径,下拉式选择(dropdown)"),
+                            label="index path (dropdown)",
                             choices=sorted(index_paths),
                             interactive=True,
                         )
@@ -1954,7 +1951,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         index_rate2 = gr.Slider(
                             minimum=0,
                             maximum=1,
-                            label=i18n("检索特征占比"),
+                            label="index rate 2",
                             value=1,
                             interactive=True,
                         )
@@ -1962,7 +1959,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="resample rate",
                             value=0,
                             step=1,
                             interactive=True,
@@ -1970,37 +1967,35 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         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"),
+                            label="rms mix rate",
                             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"
-                            ),
+                            label="protection rate",
                             value=0.33,
                             step=0.01,
                             interactive=True,
                         )
                     with gr.Column():
                         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)"),
+                            label="directory input",
                             value="E:\codes\py39\\test-20230416b\\todo-songs",
                         )
                         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")
+                            file_count="multiple", label="input"
                         )
                     with gr.Row():
                         format1 = gr.Radio(
-                            label=i18n("导出文件格式"),
+                            label="output format",
                             choices=["wav", "flac", "mp3", "m4a"],
                             value="flac",
                             interactive=True,
                         )
-                        but1 = gr.Button(i18n("转换"), variant="primary")
-                        vc_output3 = gr.Textbox(label=i18n("输出信息"))
+                        but1 = gr.Button("primary", variant="primary")
+                        vc_output3 = gr.Textbox(label="label")
                     but1.click(
                         vc_multi,
                         [
@@ -2050,14 +2045,14 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                     with gr.Column():
                         exp_dir1 = gr.Textbox(label="Voice Name:", value="My-Voice")
                         sr2 = gr.Radio(
-                            label=i18n("目标采样率"),
+                            label="sample rate",
                             choices=["40k", "48k"],
                             value="40k",
                             interactive=True,
                             visible=False
                         )
                         if_f0_3 = gr.Radio(
-                            label=i18n("模型是否带音高指导(唱歌一定要, 语音可以不要)"),
+                            label="extract f0",
                             choices=[True, False],
                             value=True,
                             interactive=True,
@@ -2092,23 +2087,21 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                             minimum=0,
                             maximum=4,
                             step=1,
-                            label=i18n("请指定说话人id"),
+                            label="speaker id",
                             value=0,
                             interactive=True,
                             visible=False
                         )
                         with gr.Accordion('GPU Settings', open=False, visible=False):
                             gpus6 = gr.Textbox(
-                                label=i18n("以-分隔输入使用的卡号, 例如   0-1-2   使用卡0和卡1和卡2"),
+                                label="0-1-2",
                                 value=gpus,
                                 interactive=True,
                                 visible=False
                             )
-                            gpu_info9 = gr.Textbox(label=i18n("显卡信息"), value=gpu_info)
+                            gpu_info9 = gr.Textbox(label="GPU", value=gpu_info)
                         f0method8 = gr.Radio(
-                            label=i18n(
-                                "选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢"
-                            ),
+                            label="f0 method",
                             choices=["harvest","crepe", "mangio-crepe", "rmvpe"], # Fork feature: Crepe on f0 extraction for training.
                             value="rmvpe",
                             interactive=True,
@@ -2118,7 +2111,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                             minimum=1,
                             maximum=512,
                             step=1,
-                            label=i18n("crepe_hop_length"),
+                            label="crepe_hop_length",
                             value=128,
                             interactive=True,
                             visible=False,
@@ -2194,17 +2187,17 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                 with gr.Group():
                     with gr.Accordion("Base Model Locations:", open=False, visible=False):
                         pretrained_G14 = gr.Textbox(
-                            label=i18n("加载预训练底模G路径"),
+                            label="G PATH",
                             value="pretrained_v2/f0G40k.pth",
                             interactive=True,
                         )
                         pretrained_D15 = gr.Textbox(
-                            label=i18n("加载预训练底模D路径"),
+                            label="D PATH",
                             value="pretrained_v2/f0D40k.pth",
                             interactive=True,
                         )
                         gpus16 = gr.Textbox(
-                            label=i18n("以-分隔输入使用的卡号, 例如   0-1-2   使用卡0和卡1和卡2"),
+                            label="GPU NUM",
                             value=gpus,
                             interactive=True,
                         )
@@ -2223,7 +2216,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose")
                         [if_f0_3, sr2, version19],
                         [f0method8, pretrained_G14, pretrained_D15],
                     )
-                    but5 = gr.Button(i18n("一键训练"), variant="primary", visible=False)
+                    but5 = gr.Button("label", variant="primary", visible=False)
                     but3.click(
                         click_train,
                         [

requirements.txt

@@ -14,7 +14,6 @@ ffmpeg-python
 praat-parselmouth
 pyworld
 numpy==1.23.5
-i18n
 numba==0.56.4
 librosa==0.9.2
 mega.py