Upload openvoice_app.py with huggingface_hub

openvoice_app.py

@@ -18,7 +18,7 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 output_dir = 'outputs'
 os.makedirs(output_dir, exist_ok=True)
 
-# load models
+# Load models
 en_base_speaker_tts = BaseSpeakerTTS(f'{en_ckpt_base}/config.json', device=device)
 en_base_speaker_tts.load_ckpt(f'{en_ckpt_base}/checkpoint.pth')
 zh_base_speaker_tts = BaseSpeakerTTS(f'{zh_ckpt_base}/config.json', device=device)
@@ -26,152 +26,80 @@ zh_base_speaker_tts.load_ckpt(f'{zh_ckpt_base}/checkpoint.pth')
 tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
 tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
 
-# load speaker embeddings
+# Load speaker embeddings
 en_source_default_se = torch.load(f'{en_ckpt_base}/en_default_se.pth').to(device)
 en_source_style_se = torch.load(f'{en_ckpt_base}/en_style_se.pth').to(device)
 zh_source_se = torch.load(f'{zh_ckpt_base}/zh_default_se.pth').to(device)
 
-# This online demo mainly supports English and Chinese
+# Supported languages
 supported_languages = ['zh', 'en']
 
 def predict(prompt, style, audio_file_pth):
-    # initialize an empty info
     text_hint = ''
 
-    # set agree to True by default
-    agree = True
-
-    # first detect the input language
+    # Detect the input language
     language_predicted = langid.classify(prompt)[0].strip()
     print(f"Detected language: {language_predicted}")
 
     if language_predicted not in supported_languages:
-        text_hint += f"[ERROR] The detected language {language_predicted} for your input text is not in our Supported Languages: {supported_languages}\n"
-        gr.Warning(
-            f"The detected language {language_predicted} for your input text is not in our Supported Languages: {supported_languages}"
-        )
-
-        return (
-            text_hint,
-            None,
-            None,
-        )
-    
+        text_hint += f"[ERROR] The detected language {language_predicted} is not supported. Supported languages: {supported_languages}\n"
+        gr.Warning(f"The detected language {language_predicted} is not supported. Supported languages: {supported_languages}")
+        return text_hint, None, None
+
     if language_predicted == "zh":
         tts_model = zh_base_speaker_tts
         source_se = zh_source_se
         language = 'Chinese'
-        if style not in ['default']:
-            text_hint += f"[ERROR] The style {style} is not supported for Chinese, which should be in ['default']\n"
-            gr.Warning(f"The style {style} is not supported for Chinese, which should be in ['default']")
-            return (
-                text_hint,
-                None,
-                None,
-            )
-
+        if style != 'default':
+            text_hint += f"[ERROR] The style {style} is not supported for Chinese. Supported style: 'default'\n"
+            gr.Warning(f"The style {style} is not supported for Chinese. Supported style: 'default'")
+            return text_hint, None, None
     else:
         tts_model = en_base_speaker_tts
-        if style == 'default':
-            source_se = en_source_default_se
-        else:
-            source_se = en_source_style_se
+        source_se = en_source_default_se if style == 'default' else en_source_style_se
         language = 'English'
         if style not in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']:
-            text_hint += f"[ERROR] The style {style} is not supported for English, which should be in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']\n"
-            gr.Warning(f"The style {style} is not supported for English, which should be in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']")
-            return (
-                text_hint,
-                None,
-                None,
-            )
-
-    speaker_wav = audio_file_pth
+            text_hint += f"[ERROR] The style {style} is not supported for English. Supported styles: ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']\n"
+            gr.Warning(f"The style {style} is not supported for English. Supported styles: ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']")
+            return text_hint, None, None
 
     if len(prompt) < 2:
-        text_hint += f"[ERROR] Please give a longer prompt text \n"
-        gr.Warning("Please give a longer prompt text")
-        return (
-            text_hint,
-            None,
-            None,
-        )
+        text_hint += "[ERROR] Please provide a longer prompt text.\n"
+        gr.Warning("Please provide a longer prompt text.")
+        return text_hint, None, None
     if len(prompt) > 200:
-        text_hint += f"[ERROR] Text length limited to 200 characters for this demo, please try shorter text. You can clone our open-source repo and try for your usage \n"
-        gr.Warning(
-            "Text length limited to 200 characters for this demo, please try shorter text. You can clone our open-source repo for your usage"
-        )
-        return (
-            text_hint,
-            None,
-            None,
-        )
-    
-    # note diffusion_conditioning not used on hifigan (default mode), it will be empty but need to pass it to model.inference
+        text_hint += "[ERROR] Text length limited to 200 characters. Please try shorter text.\n"
+        gr.Warning("Text length limited to 200 characters. Please try shorter text.")
+        return text_hint, None, None
+
     try:
-        target_se, audio_name = se_extractor.get_se(speaker_wav, tone_color_converter, target_dir='processed', vad=True)
-        # base_speaker = f"{output_dir}/openai_source_output.mp3"
-        # source_se, audio_name = se_extractor.get_se(base_speaker, tone_color_converter, vad=True)
+        target_se, audio_name = se_extractor.get_se(audio_file_pth, tone_color_converter, target_dir='processed', vad=True)
     except Exception as e:
-        text_hint += f"[ERROR] Get target tone color error {str(e)} \n"
-        gr.Warning(
-            "[ERROR] Get target tone color error {str(e)} \n"
-        )
-        return (
-            text_hint,
-            None,
-            None,
-        )
+        text_hint += f"[ERROR] Error extracting tone color: {str(e)}\n"
+        gr.Warning(f"[ERROR] Error extracting tone color: {str(e)}")
+        return text_hint, None, None
 
     src_path = f'{output_dir}/tmp.wav'
     tts_model.tts(prompt, src_path, speaker=style, language=language)
 
     save_path = f'{output_dir}/output.wav'
-    # Run the tone color converter
     encode_message = "@MyShell"
-    tone_color_converter.convert(
-        audio_src_path=src_path, 
-        src_se=source_se, 
-        tgt_se=target_se, 
-        output_path=save_path,
-        message=encode_message)
-
-    text_hint += f'''Get response successfully \n'''
-
-    return (
-        text_hint,
-        save_path,
-        speaker_wav,
-    )
+    tone_color_converter.convert(audio_src_path=src_path, src_se=source_se, tgt_se=target_se, output_path=save_path, message=encode_message)
 
+    text_hint += "Response generated successfully.\n"
+    return text_hint, save_path, audio_file_pth
 
 title = "MyShell OpenVoice"
 
-examples = [
-    [
-        "今天天气真好，我们一起出去吃饭吧。",
-        'default',
-        "resources/demo_speaker1.mp3",
-    ],[
-        "This audio is generated by open voice with a half-performance model.",
-        'whispering',
-        "resources/demo_speaker2.mp3",
-    ],
-    [
-        "He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.",
-        'sad',
-        "resources/demo_speaker0.mp3",
-    ],
-]
-
-# Define custom CSS to set the background color to white
-custom_css = """
-body {
-    background-color: white !important;
-}
-"""
-
-with gr.Blocks(css=custom_css, analytics_enabled=False) as demo:
+class WhiteTheme(gr.themes.Base):
+    def __init__(self):
+        super().__init__()
+        self.body_background = "white"
+        self.block_background = "white"
+        self.text_color = "black"
+        self.secondary_text_color = "black"
+
+with gr.Blocks(theme=WhiteTheme()) as demo:
     with gr.Row():
         with gr.Column():
             input_text_gr = gr.Textbox(
@@ -191,10 +119,8 @@ with gr.Blocks(css=custom_css, analytics_enabled=False) as demo:
                 type="filepath",
                 value="resources/demo_speaker2.mp3",
             )
-
             tts_button = gr.Button("Send", elem_id="send-btn", visible=True)
 
-
         with gr.Column():
             out_text_gr = gr.Text(label="Info")
             audio_gr = gr.Audio(label="Synthesised Audio", autoplay=True)