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| import gradio as gr | |
| import os | |
| from lib.infer import infer_audio | |
| from pydub import AudioSegment | |
| main_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | |
| # Function for inference | |
| def inference(model_name, audio, f0_change, f0_method, min_pitch, max_pitch, crepe_hop_length, | |
| index_rate, filter_radius, rms_mix_rate, protect, split_infer, min_silence, | |
| silence_threshold, seek_step, keep_silence, quefrency, timbre, | |
| f0_autotune, output_format): | |
| # Perform inference | |
| inferred_audio = infer_audio( | |
| model_name, | |
| audio_path, | |
| f0_change, | |
| f0_method, | |
| min_pitch, | |
| max_pitch, | |
| crepe_hop_length, | |
| index_rate, | |
| filter_radius, | |
| rms_mix_rate, | |
| protect, | |
| split_infer, | |
| min_silence, | |
| silence_threshold, | |
| seek_step, | |
| keep_silence, | |
| quefrency, | |
| timbre, | |
| f0_autotune, | |
| output_format | |
| ) | |
| # Convert the output audio | |
| os.chdir(main_dir) | |
| output_audio = AudioSegment.from_file(inferred_audio) | |
| # Save the output audio and return | |
| output_path = f"output.{output_format}" | |
| output_audio.export(output_path, format=output_format) | |
| return output_path | |
| # Gradio UI | |
| with gr.Blocks(theme="Ryouko65777/ryo", js="() => {document.body.classList.toggle('dark');}") as demo: | |
| gr.Markdown("# Ryo RVC ") | |
| with gr.Tabs(): | |
| audio_input = gr.Audio(label="Input Audio", type="filepath") | |
| model_name = gr.Textbox(label="Model Name") | |
| f0_change = gr.Number(label="Pitch Change (F0 Change)", value=0) | |
| f0_method = gr.Dropdown( | |
| label="F0 Method", | |
| choices= | |
| [ | |
| "crepe", | |
| "harvest", | |
| "mangio-crepe", | |
| "rmvpe", | |
| "rmvpe+", | |
| "fcpe", | |
| "fcpe_legacy", | |
| "hybrid[mangio-crepe+rmvpe]", | |
| "hybrid[mangio-crepe+fcpe]", | |
| "hybrid[rmvpe+fcpe]", | |
| "hybrid[mangio-crepe+rmvpe+fcpe]", | |
| ], | |
| value="fcpe", | |
| ) | |
| min_pitch = gr.Textbox(label="Min Pitch", value="50") | |
| max_pitch = gr.Textbox(label="Max Pitch", value="1100") | |
| crepe_hop_length = gr.Number(label="CREPE Hop Length", value=120) | |
| index_rate = gr.Slider(label="Index Rate", minimum=0, maximum=1, value=0.75) | |
| filter_radius = gr.Number(label="Filter Radius", value=3) | |
| rms_mix_rate = gr.Slider(label="RMS Mix Rate", minimum=0, maximum=1, value=0.25) | |
| protect = gr.Slider(label="Protect", minimum=0, maximum=1, value=0.33) | |
| split_infer = gr.Checkbox(label="Enable Split Inference", value=False) | |
| min_silence = gr.Number(label="Min Silence (ms)", value=500) | |
| silence_threshold = gr.Number(label="Silence Threshold (dB)", value=-50) | |
| seek_step = gr.Slider(label="Seek Step (ms)", minimum=1, maximum=10, value=1) | |
| keep_silence = gr.Number(label="Keep Silence (ms)", value=200) | |
| quefrency = gr.Number(label="Quefrency", value=0) | |
| timbre = gr.Number(label="Timbre", value=1) | |
| f0_autotune = gr.Checkbox(label="Enable F0 Autotune", value=False) | |
| output_format = gr.Dropdown(label="Output Format", choices=["wav", "flac", "mp3"], value="wav") | |
| output_audio = gr.Audio(label="Output Audio") | |
| submit_btn = gr.Button("Run Inference") | |
| # Define the interaction between input and function | |
| submit_btn.click(fn=inference, | |
| inputs=[model_name, audio_input, f0_change, f0_method, min_pitch, max_pitch, | |
| crepe_hop_length, index_rate, filter_radius, rms_mix_rate, protect, | |
| split_infer, min_silence, silence_threshold, seek_step, keep_silence, | |
| quefrency, timbre, f0_autotune, output_format], | |
| outputs=output_audio) | |
| # Launch the demo | |
| demo.launch() | |