Spaces:
Running
Running
Commit
·
cb9e52f
1
Parent(s):
d0a23bd
更新全员模型
Browse files
app.py
CHANGED
@@ -58,8 +58,19 @@ device = (
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BandList = {
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"MyGo":["燈","愛音","そよ","立希","楽奈"],
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"AveMujica":["祥子","睦","海鈴","にゃむ","初華"]
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}
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def get_net_g(model_path: str, version: str, device: str, hps):
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@@ -77,7 +88,7 @@ def get_net_g(model_path: str, version: str, device: str, hps):
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def get_text(text, language_str, hps, device):
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norm_text, phone, tone, word2ph = clean_text(text, language_str)
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phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
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print(text)
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if hps.data.add_blank:
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phone = commons.intersperse(phone, 0)
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tone = commons.intersperse(tone, 0)
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@@ -114,11 +125,12 @@ def get_text(text, language_str, hps, device):
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return bert, ja_bert, en_bert, phone, tone, language
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def get_emo_(reference_audio, emotion):
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return emo
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def get_emo(path):
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@@ -202,15 +214,15 @@ if __name__ == "__main__":
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REPO_ID = "audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim"
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emotional_processor = Wav2Vec2Processor.from_pretrained(emotional_model_name)
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emotional_model = EmotionModel.from_pretrained(emotional_model_name).to(device)
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hps = utils.get_hparams_from_file('Data/
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net_g = get_net_g(
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model_path='Data/
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)
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speaker_ids = hps.data.spk2id
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speakers = list(speaker_ids.keys())
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languages = [ "Auto", "ZH", "JP"]
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modelPaths = []
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for dirpath, dirnames, filenames in os.walk("Data/
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for filename in filenames:
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modelPaths.append(os.path.join(dirpath, filename))
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with gr.Blocks() as app:
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@@ -219,7 +231,7 @@ if __name__ == "__main__":
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for name in BandList[band]:
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with gr.TabItem(name):
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classifiedPaths = []
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for dirpath, dirnames, filenames in os.walk("Data/
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for filename in filenames:
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classifiedPaths.append(os.path.join(dirpath, filename))
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with gr.Row():
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@@ -234,7 +246,7 @@ if __name__ == "__main__":
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minimum=0.1, maximum=2, value=1, step=0.01, label="语速调节"
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)
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emotion = gr.Slider(
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minimum=-10, maximum=10, value=0, step=0.1, label="Emotion"
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)
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with gr.Accordion(label="参数设定", open=False):
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sdp_ratio = gr.Slider(
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@@ -260,7 +272,10 @@ if __name__ == "__main__":
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placeholder="输入纯日语或者中文",
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value="为什么要演奏春日影!",
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)
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btn = gr.Button("点击生成", variant="primary")
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audio_output = gr.Audio(label="Output Audio")
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'''
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)
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BandList = {
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"PoppinParty":["香澄","有咲","たえ","りみ","沙綾"],
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"Afterglow":["蘭","モカ","ひまり","巴","つぐみ"],
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"HelloHappyWorld":["こころ","美咲","薫","花音","はぐみ"],
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"PastelPalettes":["彩","日菜","千聖","イヴ","麻弥"],
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"Roselia":["友希那","紗夜","リサ","燐子","あこ"],
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"RaiseASuilen":["レイヤ","ロック","ますき","チュチュ","パレオ"],
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"Morfonica":["ましろ","瑠唯","つくし","七深","透子"],
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"MyGo":["燈","愛音","そよ","立希","楽奈"],
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"AveMujica":["祥子","睦","海鈴","にゃむ","初華"],
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"圣翔音乐学园":["華戀","光","香子","雙葉","真晝","純那","克洛迪娜","真矢","奈奈"],
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"凛明馆女子学校":["珠緒","壘","文","悠悠子","一愛"],
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"弗隆提亚艺术学校":["艾露","艾露露","菈樂菲","司","靜羽"],
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"西克菲尔特音乐学院":["晶","未知留","八千代","栞","美帆"]
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}
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def get_net_g(model_path: str, version: str, device: str, hps):
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def get_text(text, language_str, hps, device):
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norm_text, phone, tone, word2ph = clean_text(text, language_str)
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phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
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#print(text)
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if hps.data.add_blank:
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phone = commons.intersperse(phone, 0)
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tone = commons.intersperse(tone, 0)
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return bert, ja_bert, en_bert, phone, tone, language
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def get_emo_(reference_audio, emotion):
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if (emotion == 10 and reference_audio):
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emo = torch.from_numpy(get_emo(reference_audio))
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else:
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emo = torch.Tensor([emotion])
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return emo
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def get_emo(path):
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REPO_ID = "audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim"
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emotional_processor = Wav2Vec2Processor.from_pretrained(emotional_model_name)
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emotional_model = EmotionModel.from_pretrained(emotional_model_name).to(device)
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hps = utils.get_hparams_from_file('Data/Bushiroad/configs/config.json')
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net_g = get_net_g(
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model_path='Data/Bushiroad/models/G_29000.pth', version="2.1", device=device, hps=hps
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)
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speaker_ids = hps.data.spk2id
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speakers = list(speaker_ids.keys())
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languages = [ "Auto", "ZH", "JP"]
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modelPaths = []
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for dirpath, dirnames, filenames in os.walk("Data/Bushiroad/models/"):
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for filename in filenames:
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modelPaths.append(os.path.join(dirpath, filename))
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with gr.Blocks() as app:
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for name in BandList[band]:
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with gr.TabItem(name):
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classifiedPaths = []
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for dirpath, dirnames, filenames in os.walk("Data/Bushiroad/classifedSample/"+name):
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for filename in filenames:
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classifiedPaths.append(os.path.join(dirpath, filename))
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with gr.Row():
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minimum=0.1, maximum=2, value=1, step=0.01, label="语速调节"
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)
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emotion = gr.Slider(
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minimum=-10, maximum=10, value=0, step=0.1, label="Emotion参数(调至10开启音频参考,如不启动则设为0)"
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)
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with gr.Accordion(label="参数设定", open=False):
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sdp_ratio = gr.Slider(
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placeholder="输入纯日语或者中文",
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value="为什么要演奏春日影!",
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)
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try:
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reference_audio = gr.Dropdown(label = "情感参考", choices = classifiedPaths, value = classifiedPaths[0], type = "value")
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except:
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reference_audio = gr.Audio(label="情感参考音频)", type="filepath")
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btn = gr.Button("点击生成", variant="primary")
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audio_output = gr.Audio(label="Output Audio")
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'''
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