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27e967e
1 Parent(s): a5a7ed0

Update app.py

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  1. app.py +84 -63
app.py CHANGED
@@ -9,6 +9,14 @@ from text import text_to_sequence
9
  import numpy as np
10
  import os
11
  import translators.server as tss
 
 
 
 
 
 
 
 
12
  def get_text(text, hps):
13
  text_norm = text_to_sequence(text, hps.data.text_cleaners)
14
  if hps.data.add_blank:
@@ -16,6 +24,7 @@ def get_text(text, hps):
16
  text_norm = torch.LongTensor(text_norm)
17
  return text_norm
18
 
 
19
  hps = utils.get_hparams_from_file("./configs/uma87.json")
20
  net_g = SynthesizerTrn(
21
  len(symbols),
@@ -25,29 +34,10 @@ net_g = SynthesizerTrn(
25
  **hps.model)
26
  _ = net_g.eval()
27
 
28
- _ = utils.load_checkpoint("pretrained_models/G_1153000.pth", net_g, None)
29
-
30
- title = "Umamusume voice synthesizer \n 赛马娘语音合成器"
31
- description = """
32
- This synthesizer is created based on [VITS][paper] model, trained on voice data extracted from mobile game Umamusume Pretty Derby\n
33
- 这个合成器是基于VITS文本到语音模型,在从手游《賽馬娘:Pretty Derby》解包的语音数据上训练得到。\n
34
- [introduction video][video] [模型介绍视频][video]\n
35
- Due to some unknown reason, VITS inference on CPU results in accumulative memory leakage, resulting in Runtime error:Memory limit exceeded.\n
36
- In case of space crash, you may duplicate this space or [open in Colab][colab] to run it privately and without any queue.\n
37
- 由于未知原因,VITS模型在CPU上执行推理时会有逐步累积的内存泄漏,最终导致空间报错Runtime error:Memory limit exceeded,目前正在排查。\n
38
- 以防该空间崩溃,您可以复制该空间至私人空间运行或打开[Google Colab][colab]在线运行。\n
39
- If your input language is not Japanese, it will be translated to Japanese by Google translator, but accuracy is not guaranteed.\n
40
- 如果您的输入语言不是日语,则会由谷歌翻译自动翻译为日语,但是准确性不能保证。\n\n
41
- [video]: https://www.bilibili.com/video/BV1T84y1e7p5/?vd_source=6d5c00c796eff1cbbe25f1ae722c2f9f#reply607277701
42
- [paper]: https://arxiv.org/abs/2106.06103
43
- [colab]: https://colab.research.google.com/drive/1J2Vm5dczTF99ckyNLXV0K-hQTxLwEaj5?usp=sharing
44
- """
45
- article = """
46
-
47
- """
48
-
49
 
50
  def infer(text, character, language, duration, noise_scale, noise_scale_w):
 
51
  if language == '日本語':
52
  pass
53
  elif language == '简体中文':
@@ -60,50 +50,81 @@ def infer(text, character, language, duration, noise_scale, noise_scale_w):
60
  x_tst = stn_tst.unsqueeze(0)
61
  x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
62
  sid = torch.LongTensor([char_id])
63
- audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=duration)[0][0,0].data.cpu().float().numpy()
64
- return (text,(22050, audio))
 
 
 
65
 
66
- # We instantiate the Textbox class
67
- textbox = gr.Textbox(label="Text", placeholder="Type your sentence here", lines=2)
68
- # select character
69
- char_dropdown = gr.Dropdown(['0:特别周','1:无声铃鹿','2:东海帝王','3:丸善斯基',
70
- '4:富士奇迹','5:小栗帽','6:黄金船','7:伏特加',
71
- '8:大和赤骥','9:大树快车','10:草上飞','11:菱亚马逊',
72
- '12:目白麦昆','13:神鹰','14:好歌剧','15:成田白仁',
73
- '16:鲁道夫象征','17:气槽','18:爱丽数码','19:青云天空',
74
- '20:玉藻十字','21:美妙姿势','22:琵琶晨光','23:重炮',
75
- '24:曼城茶座','25:美普波旁','26:目白雷恩','27:菱曙',
76
- '28:雪之美人','29:米浴','30:艾尼斯风神','31:爱丽速子',
77
- '32:爱慕织姬','33:稻荷一','34:胜利奖券','35:空中神宫',
78
- '36:荣进闪耀','37:真机伶','38:川上公主','39:黄金城市',
79
- '40:樱花进王','41:采珠','42:新光风','43:东商变革',
80
- '44:超级小溪','45:醒目飞鹰','46:荒漠英雄','47:东瀛佐敦',
81
- '48:中山庆典','49:成田大进','50:西野花','51:春乌拉拉',
82
- '52:青竹回忆','53:微光飞驹','54:美丽周日','55:待兼福来',
83
- '56:Mr.C.B','57:名将怒涛','58:目白多伯','59:优秀素质',
84
- '60:帝王光环','61:待兼诗歌剧','62:生野狄杜斯','63:目白善信',
85
- '64:大拓太阳神','65:双涡轮','66:里见光钻','67:北部玄驹',
86
- '68:樱花千代王','69:天狼星象征','70:目白阿尔丹','71:八重无敌',
87
- '72:鹤丸刚志','73:目白光明','74:樱花桂冠','75:成田路',
88
- '76:也文摄辉','77:吉兆','78:谷野美酒','79:第一红宝石',
89
- '80:真弓快车','81:骏川手纲','82:凯斯奇迹','83:小林历奇',
90
- '84:北港火山','85:奇锐骏','86:秋川理事长'])
91
- language_dropdown = gr.Dropdown(['日本語','简体中文','English'])
92
- examples = [['お疲れ様です,トレーナーさん。', '1:无声铃鹿', '日本語', 1, 0.667, 0.8],
93
- ['張り切っていこう!', '67:北部玄驹', '日本語', 1, 0.667, 0.8],
94
- ['何でこんなに慣れでんのよ,私のほが先に好きだっだのに。', '10:草上飞','日本語', 1, 0.667, 0.8],
95
- ['授業中に出しだら,学校生活終わるですわ。', '12:目白麦昆','日本語', 1, 0.667, 0.8],
96
- ['お帰りなさい,お兄様!', '29:米浴','日本語', 1, 0.667, 0.8],
97
- ['私の処女をもらっでください!', '29:米浴','日本語', 1, 0.667, 0.8]]
98
-
99
- duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1, label='时长 Duration')
100
- noise_scale_slider = gr.Slider(minimum=0.1, maximum=5, value=0.667, step=0.001, label='噪声比例 noise_scale')
101
- noise_scale_w_slider = gr.Slider(minimum=0.1, maximum=5, value=0.8, step=0.1, label='噪声偏差 noise_scale_w')
102
-
103
- app = gr.Interface(fn=infer, inputs=[textbox, char_dropdown, language_dropdown, duration_slider, noise_scale_slider, noise_scale_w_slider,], outputs=["text","audio"],title=title, description=description, article=article, examples=examples)
104
-
105
- if __name__=="__main__":
106
  parser = argparse.ArgumentParser()
107
  parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
108
  args = parser.parse_args()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
109
  app.queue(concurrency_count=3).launch(show_api=False, share=args.share)
 
9
  import numpy as np
10
  import os
11
  import translators.server as tss
12
+ def show_memory_info(hint):
13
+ pid = os.getpid()
14
+ p = psutil.Process(pid)
15
+ info = p.memory_info()
16
+ memory = info.rss / 1024.0 / 1024
17
+ print("{} 内存占用: {} MB".format(hint, memory))
18
+
19
+
20
  def get_text(text, hps):
21
  text_norm = text_to_sequence(text, hps.data.text_cleaners)
22
  if hps.data.add_blank:
 
24
  text_norm = torch.LongTensor(text_norm)
25
  return text_norm
26
 
27
+
28
  hps = utils.get_hparams_from_file("./configs/uma87.json")
29
  net_g = SynthesizerTrn(
30
  len(symbols),
 
34
  **hps.model)
35
  _ = net_g.eval()
36
 
37
+ _ = utils.load_checkpoint("pretrained_models/uma_1153000.pth", net_g, None)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
38
 
39
  def infer(text, character, language, duration, noise_scale, noise_scale_w):
40
+ show_memory_info("infer调用前")
41
  if language == '日本語':
42
  pass
43
  elif language == '简体中文':
 
50
  x_tst = stn_tst.unsqueeze(0)
51
  x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
52
  sid = torch.LongTensor([char_id])
53
+ audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
54
+ length_scale=duration)[0][0, 0].data.cpu().float().numpy()
55
+ del stn_tst, x_tst, x_tst_lengths, sid
56
+ show_memory_info("infer调用后")
57
+ return (text, (22050, audio))
58
 
59
+ if __name__ == "__main__":
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
60
  parser = argparse.ArgumentParser()
61
  parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
62
  args = parser.parse_args()
63
+ app = gr.Blocks()
64
+ with app:
65
+ gr.Markdown("# Umamusume voice synthesizer 赛马娘语音合成器\n\n"
66
+ "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=Plachta.VITS-Umamusume-voice-synthesizer)\n\n"
67
+ "This synthesizer is created based on [VITS](https://arxiv.org/abs/2106.06103) model, trained on voice data extracted from mobile game Umamusume Pretty Derby \n\n"
68
+ "这个合成器是基于VITS文本到语音模型,在从手游《賽馬娘:Pretty Derby》解包的语音数据上训练得到。\n\n"
69
+ "[introduction video / 模型介绍视频](https://www.bilibili.com/video/BV1T84y1e7p5/?vd_source=6d5c00c796eff1cbbe25f1ae722c2f9f#reply607277701)\n\n"
70
+ "Due to some unknown reason, VITS inference on CPU results in accumulative memory leakage, resulting in Runtime error:Memory limit exceeded.\n\n"
71
+ "In case of space crash, you may duplicate this space or [open in Colab](https://colab.research.google.com/drive/1J2Vm5dczTF99ckyNLXV0K-hQTxLwEaj5?usp=sharing) to run it privately and without any queue.\n\n"
72
+ "由于未知原因,VITS模型在CPU上执行推理时会有逐步累积的内存泄漏,最终导致空间报错Runtime error:Memory limit exceeded,目前正在排查。\n\n"
73
+ "以防该空间崩溃,您可以复制该空间至私人空间运行或打开[Google Colab](https://colab.research.google.com/drive/1J2Vm5dczTF99ckyNLXV0K-hQTxLwEaj5?usp=sharing)在线运行。\n\n"
74
+ "If your input language is not Japanese, it will be translated to Japanese by Google translator, but accuracy is not guaranteed.\n\n"
75
+ "如果您的输入语言不是日语,则会由谷歌翻译自动翻译为日语,但是准确性不能保证。\n\n"
76
+ )
77
+ with gr.Row():
78
+ with gr.Column():
79
+ # We instantiate the Textbox class
80
+ textbox = gr.Textbox(label="Text", placeholder="Type your sentence here", lines=2)
81
+ # select character
82
+ char_dropdown = gr.Dropdown(choices=['0:特别周', '1:无声铃鹿', '2:东海帝王', '3:丸善斯基',
83
+ '4:富士奇迹', '5:小栗帽', '6:黄金船', '7:伏特加',
84
+ '8:大和赤骥', '9:大树快车', '10:草上飞', '11:菱亚马逊',
85
+ '12:目白麦昆', '13:神鹰', '14:好歌剧', '15:成田白仁',
86
+ '16:鲁道夫象征', '17:气槽', '18:爱丽数码', '19:青云天空',
87
+ '20:玉藻十字', '21:美妙姿势', '22:琵琶晨光', '23:重炮',
88
+ '24:曼城茶座', '25:美普波旁', '26:目白雷恩', '27:菱曙',
89
+ '28:雪之美人', '29:米浴', '30:艾尼斯风神', '31:爱丽速子',
90
+ '32:爱慕织姬', '33:稻荷一', '34:胜利奖券', '35:空中神宫',
91
+ '36:荣进闪耀', '37:真机伶', '38:川上公主', '39:黄金城市',
92
+ '40:樱花进王', '41:采珠', '42:新光风', '43:东商变革',
93
+ '44:超级小溪', '45:醒目飞鹰', '46:荒漠英雄', '47:东瀛佐敦',
94
+ '48:中山庆典', '49:成田大进', '50:西野花', '51:春乌拉拉',
95
+ '52:青竹回忆', '53:微光飞驹', '54:美丽周日', '55:待兼福来',
96
+ '56:Mr.C.B', '57:名将怒涛', '58:目白多伯', '59:优秀素质',
97
+ '60:帝王光环', '61:待兼诗歌剧', '62:生野狄杜斯', '63:目白善信',
98
+ '64:大拓太阳神', '65:双涡轮', '66:里见光钻', '67:北部玄驹',
99
+ '68:樱花千代王', '69:天狼星象征', '70:目白阿尔丹', '71:八重无敌',
100
+ '72:鹤丸刚志', '73:目白光明', '74:樱花桂冠', '75:成田路',
101
+ '76:也文摄辉', '77:吉兆', '78:谷野美酒', '79:第一红宝石',
102
+ '80:真弓快车', '81:骏川手纲', '82:凯斯奇迹', '83:小林历奇',
103
+ '84:北港火山', '85:奇锐骏', '86:秋川理事长'], label='character')
104
+ language_dropdown = gr.Dropdown(choices=['日本語', '简体中文', 'English'], label='language')
105
+
106
+
107
+ duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1, label='时长 Duration')
108
+ noise_scale_slider = gr.Slider(minimum=0.1, maximum=5, value=0.667, step=0.001, label='噪声比例 noise_scale')
109
+ noise_scale_w_slider = gr.Slider(minimum=0.1, maximum=5, value=0.8, step=0.1, label='噪声偏差 noise_scale_w')
110
+ with gr.Column():
111
+ text_output = gr.Textbox(label="Output Text")
112
+ audio_output = gr.Audio(label="Output Voice")
113
+ btn = gr.Button("Generate!")
114
+ btn.click(infer, inputs=[textbox, char_dropdown, language_dropdown,
115
+ duration_slider, noise_scale_slider, noise_scale_w_slider],
116
+ outputs=[text_output, audio_output])
117
+ examples = [['お疲れ様です,トレーナーさん。', '1:无声铃鹿', '日本語', 1, 0.667, 0.8],
118
+ ['張り切っていこう!', '67:北部玄驹', '日本語', 1, 0.667, 0.8],
119
+ ['何でこんなに慣れでんのよ,私のほが先に好きだっだのに。', '10:草上飞', '日本語', 1, 0.667, 0.8],
120
+ ['授業中に出しだら,学校生活終わるですわ。', '12:目白麦昆', '日本語', 1, 0.667, 0.8],
121
+ ['お帰りなさい,お兄様!', '29:米浴', '日本語', 1, 0.667, 0.8],
122
+ ['私の処女をもらっでください!', '29:米浴', '日本語', 1, 0.667, 0.8]]
123
+ gr.Examples(
124
+ examples=examples,
125
+ inputs=[textbox, char_dropdown, language_dropdown,
126
+ duration_slider, noise_scale_slider,noise_scale_w_slider],
127
+ outputs=[text_output, audio_output],
128
+ fn=infer
129
+ )
130
  app.queue(concurrency_count=3).launch(show_api=False, share=args.share)