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import gradio as gr |
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from playdiffusion import PlayDiffusion, RVCInput |
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import os |
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import wget |
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print("--- Checking and Downloading Model Assets ---") |
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MODEL_FILES = { |
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"kmeans_10k.npy": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/kmeans_10k.npy", |
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"last_250k_fixed.pkl": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/last_250k_fixed.pkl", |
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"tokenizer-multi_bpe16384_merged_extended_58M.json": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/tokenizer-multi_bpe16384_merged_extended_58M.json", |
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"v090_g_01105000": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/v090_g_01105000", |
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"voice_encoder_1992000.pt": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/voice_encoder_1992000.pt", |
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"xlsr2_1b_v2_custom.pt": "https://huggingface.co/PlayHT/PlayDiffusion/resolve/main/xlsr2_1b_v2_custom.pt" |
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} |
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for filename, url in MODEL_FILES.items(): |
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if not os.path.exists(filename): |
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print(f"Downloading {filename}...") |
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wget.download(url, filename) |
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else: |
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print(f"{filename} already exists. Skipping download.") |
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print("Initializing PlayDiffusion... This will load the models into memory.") |
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inpainter = PlayDiffusion() |
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print("PlayDiffusion initialized successfully.") |
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def speech_rvc(rvc_source_speech, rvc_target_voice): |
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if rvc_source_speech is None or rvc_target_voice is None: |
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raise gr.Error("Please provide both a source speech audio and a target voice audio.") |
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print("Starting voice conversion...") |
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converted_audio = inpainter.rvc(RVCInput(source_speech=rvc_source_speech, target_voice=rvc_target_voice)) |
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print("Voice conversion finished.") |
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return converted_audio |
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with gr.Blocks(theme=gr.themes.Soft(), title="PlayDiffusion Voice Conversion") as demo: |
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gr.Markdown("# 🗣️ PlayDiffusion Voice Conversion") |
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gr.Markdown("Upload a **Source Speech** audio and a **Target Voice** audio to convert the speech.") |
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with gr.Row(): |
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rvc_source_speech = gr.Audio(label="Source Speech", sources=["upload", "microphone"], type="filepath") |
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rvc_target_voice = gr.Audio(label="Target Voice", sources=["upload", "microphone"], type="filepath") |
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rvc_submit = gr.Button("🚀 Run Voice Conversion", variant="primary") |
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gr.Markdown("### Converted Speech Output") |
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rvc_output = gr.Audio(label="Result", interactive=False) |
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rvc_submit.click(fn=speech_rvc, inputs=[rvc_source_speech, rvc_target_voice], outputs=[rvc_output]) |
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demo.launch() |
