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Update app.py
Browse files
app.py
CHANGED
@@ -84,10 +84,11 @@ def convert_wav_to_mp3(wav_file):
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os.system(" ".join(command))
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return output_path_mp3
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def tts_generator(text,
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global net_g
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model_path = models[model]
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net_g, _, _, _ = utils.load_checkpoint(model_path, net_g, None, skip_optimizer=True)
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try:
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with torch.no_grad():
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audio = infer(text, sdp_ratio=sdp_ratio, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=length_scale, sid=speaker,model_dir=model)
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@@ -111,10 +112,18 @@ if __name__ == "__main__":
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_ = net_g.eval()
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speaker_ids = hps.data.spk2id
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with gr.Column():
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gr.Markdown("测试用")
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@@ -123,8 +132,8 @@ if __name__ == "__main__":
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info="使用huggingface的免费CPU进行推理,因此速度不快,一次性不要输入超过500汉字")
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model = gr.Radio(choices=list(models.keys()), value=list(models.keys())[0], label='音声模型')
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#model = gr.Dropdown(choices=models,value=models[0], label='音声模型')
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speaker = gr.Radio(choices=speakers, value=speakers[0], label='Speaker')
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gr.Markdown(value="
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sdp_ratio = gr.Slider(minimum=0, maximum=1, value=0.2, step=0.01, label='语调变化')
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noise_scale = gr.Slider(minimum=0.1, maximum=1.5, value=0.5, step=0.01, label='感情变化')
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noise_scale_w = gr.Slider(minimum=0.1, maximum=1.4, value=0.9, step=0.01, label='音节长度')
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@@ -139,7 +148,7 @@ if __name__ == "__main__":
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""")
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btn.click(
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tts_generator,
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inputs=[text,
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outputs=[text_output, audio_output,MP3_output]
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)
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os.system(" ".join(command))
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return output_path_mp3
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def tts_generator(text, sdp_ratio, noise_scale, noise_scale_w, length_scale, model):
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global net_g,speakers
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model_path = models[model]
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net_g, _, _, _ = utils.load_checkpoint(model_path, net_g, None, skip_optimizer=True)
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try:
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with torch.no_grad():
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audio = infer(text, sdp_ratio=sdp_ratio, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=length_scale, sid=speaker,model_dir=model)
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_ = net_g.eval()
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speaker_ids = hps.data.spk2id
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speaker = list(speaker_ids.keys())[0]
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css='''
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#main {background-color: #ffffff;opacity: 0.8;background-image: repeating-linear-gradient(45deg, #edffe1 25%, transparent 25%, transparent 75%, #edffe1 75%, #edffe1), repeating-linear-gradient(45deg, #edffe1 25%, #ffffff 25%, #ffffff 75%, #edffe1 75%, #edffe1);
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background-position: 0 0, 40px 40px;background-size: 80px 80px;}
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#mainContainer {max-width: 700px; margin-left: auto; margin-right: auto;background-color:transparent;}
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#btn {border: 2px solid #3ed6e500; margin-left: auto; margin-right: auto;background-color:#3ed6e500;border-radius: 5px;
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:hover{color: #92ccd8; } }
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'''
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with gr.Blocks(css=css) as app:
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with gr.Row(elem_id="main"):
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with gr.Column():
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gr.Markdown("测试用")
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info="使用huggingface的免费CPU进行推理,因此速度不快,一次性不要输入超过500汉字")
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model = gr.Radio(choices=list(models.keys()), value=list(models.keys())[0], label='音声模型')
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#model = gr.Dropdown(choices=models,value=models[0], label='音声模型')
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#speaker = gr.Radio(choices=speakers, value=speakers[0], label='Speaker')
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gr.Markdown(value="生成参数")
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sdp_ratio = gr.Slider(minimum=0, maximum=1, value=0.2, step=0.01, label='语调变化')
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noise_scale = gr.Slider(minimum=0.1, maximum=1.5, value=0.5, step=0.01, label='感情变化')
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noise_scale_w = gr.Slider(minimum=0.1, maximum=1.4, value=0.9, step=0.01, label='音节长度')
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""")
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btn.click(
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tts_generator,
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inputs=[text, sdp_ratio, noise_scale, noise_scale_w, length_scale, model],
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outputs=[text_output, audio_output,MP3_output]
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)
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