mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-04-05 04:08:58 +08:00
168 lines
7.0 KiB
Python
168 lines
7.0 KiB
Python
import gradio as gr
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# Import modules from your packages
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from merged_ui.utils import generate_and_process_with_rvc, modified_get_vc
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from rvc_ui.initialization import config
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from rvc_ui.main import names, index_paths
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def build_merged_ui():
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"""
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Build the combined TTS-RVC UI interface using Gradio
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"""
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# Create the UI
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with gr.Blocks(title="Unified TTS-RVC Pipeline") as app:
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gr.Markdown("## Voice Generation and Conversion Pipeline")
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gr.Markdown("Generate speech with Spark TTS and process it through RVC for voice conversion")
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with gr.Tabs():
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with gr.TabItem("TTS-to-RVC Pipeline"):
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gr.Markdown("### Generate speech with Spark TTS and convert with RVC")
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gr.Markdown("*Note: For multi-sentence text, each sentence will be processed separately and then combined.*")
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# TTS Generation Section
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with gr.Row():
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prompt_wav_upload = gr.Audio(
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sources="upload",
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type="filepath",
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label="Reference voice (upload)",
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)
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prompt_wav_record = gr.Audio(
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sources="microphone",
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type="filepath",
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label="Reference voice (record)",
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)
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with gr.Row():
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tts_text_input = gr.Textbox(
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label="Text to synthesize",
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lines=3,
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placeholder="Enter text for TTS. Multiple sentences will be processed individually."
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)
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prompt_text_input = gr.Textbox(
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label="Text of prompt speech (Optional)",
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lines=3,
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placeholder="Enter text of the reference audio",
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)
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# RVC Settings
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with gr.Row():
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with gr.Column():
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sid0 = gr.Dropdown(
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label="Target voice model:", choices=sorted(names)
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)
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vc_transform0 = gr.Number(
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label="Transpose (semitones):",
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value=0,
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)
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f0method0 = gr.Radio(
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label="Pitch extraction algorithm:",
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choices=(
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["pm", "harvest", "crepe", "rmvpe"]
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if config.dml == False
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else ["pm", "harvest", "rmvpe"]
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),
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value="rmvpe",
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interactive=True,
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)
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file_index1 = gr.Textbox(
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label="Path to feature index file (leave blank for auto):",
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placeholder="Leave blank to use dropdown selection",
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interactive=True,
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)
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file_index2 = gr.Dropdown(
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label="Select feature index:",
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choices=sorted(index_paths),
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interactive=True,
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)
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with gr.Column():
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index_rate1 = gr.Slider(
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minimum=0,
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maximum=1,
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label="Feature search ratio (accent strength):",
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value=0.75,
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interactive=True,
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)
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filter_radius0 = gr.Slider(
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minimum=0,
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maximum=7,
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label="Median filter radius (3+ reduces breathiness):",
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value=3,
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step=1,
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interactive=True,
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)
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rms_mix_rate0 = gr.Slider(
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minimum=0,
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maximum=1,
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label="Volume envelope scaling (0=original, 1=constant):",
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value=0.25,
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interactive=True,
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)
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protect0 = gr.Slider(
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minimum=0,
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maximum=0.5,
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label="Consonant protection (0=max, 0.5=disable):",
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value=0.33,
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step=0.01,
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interactive=True,
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)
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resample_sr0 = gr.Slider(
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minimum=0,
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maximum=48000,
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label="Output sample rate (0=no resampling):",
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value=0,
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step=1,
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interactive=True,
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)
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# Speaker ID (hidden)
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spk_item = gr.Slider(
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minimum=0,
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maximum=2333,
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step=1,
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label="Speaker ID:",
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value=0,
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visible=False,
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interactive=True,
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)
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# Combined process button and outputs
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generate_with_rvc_button = gr.Button("Generate with RVC", variant="primary")
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with gr.Row():
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vc_output1 = gr.Textbox(label="Output information", lines=10)
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vc_output2 = gr.Audio(label="Final concatenated audio")
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# Connect generate function to button
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generate_with_rvc_button.click(
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generate_and_process_with_rvc,
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inputs=[
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tts_text_input,
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prompt_text_input,
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prompt_wav_upload,
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prompt_wav_record,
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spk_item,
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vc_transform0,
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f0method0,
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file_index1,
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file_index2,
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index_rate1,
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filter_radius0,
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resample_sr0,
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rms_mix_rate0,
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protect0,
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],
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outputs=[vc_output1, vc_output2],
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)
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# Connect modified_get_vc function for dropdown change
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sid0.change(
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fn=lambda sid0_val, protect0_val: modified_get_vc(sid0_val, protect0_val, file_index2),
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inputs=[sid0, protect0],
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outputs=[spk_item, protect0, file_index2],
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)
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return app
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if __name__ == "__main__":
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build_merged_ui() |