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import torch |
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from transformers import pipeline |
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import numpy as np |
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import gradio as gr |
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def _grab_best_device(use_gpu=True): |
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if torch.cuda.device_count() > 0 and use_gpu: |
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device = "cuda" |
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else: |
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device = "cpu" |
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return device |
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device = _grab_best_device() |
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HUB_PATH = "ylacombe/vits_vctk_welsh_male" |
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pipe_dict = { |
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"current_model": "ylacombe/vits_ljs_welsh_male", |
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"pipe": pipeline("text-to-speech", model=HUB_PATH, device=0), |
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} |
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title = "# 🐶 VITS" |
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description = """ |
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""" |
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max_speakers = 15 |
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def generate_audio(text, model_id): |
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if pipe_dict["current_model"] != model_id: |
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gr.Warning("Model has changed - loading new model") |
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pipe_dict["pipe"] = pipeline("text-to-speech", model=model_id, device=0) |
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pipe_dict["current_model"] = model_id |
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num_speakers = pipe_dict["pipe"].model.config.num_speakers |
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out = [] |
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if num_speakers>1: |
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for i in range(min(num_speakers, max_speakers)): |
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forward_params = {"speaker_id": i} |
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output = pipe_dict["pipe"](text, forward_params=forward_params) |
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output = gr.Audio(value = (output["sampling_rate"], output["audio"].squeeze()), type="numpy", autoplay=False, label=f"Generated Audio - speaker {i}", show_label=True, |
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visible=True) |
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out.append(output) |
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out.extend([gr.Audio(visible=False)]*(max_speakers-num_speakers)) |
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else: |
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output = pipe_dict["pipe"](text) |
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output = gr.Audio(value = (output["sampling_rate"], output["audio"].squeeze()), type="numpy", autoplay=False, label="Generated Audio - Mono speaker", show_label=True, |
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visible=True) |
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out.append(output) |
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out.extend([gr.Audio(visible=False)]*(max_speakers-1)) |
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return out |
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with gr.Blocks() as demo_blocks: |
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gr.Markdown(title) |
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gr.Markdown(description) |
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with gr.Row(): |
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with gr.Column(): |
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inp_text = gr.Textbox(label="Input Text", info="What would you like bark to synthesise?") |
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btn = gr.Button("Generate Audio!") |
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model_id = gr.Dropdown( |
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[ |
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"ylacombe/vits_vctk_welsh_male", |
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"ylacombe/vits_vctk_welsh_female", |
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"ylacombe/vits_ljs_welsh_male", |
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"ylacombe/vits_ljs_welsh_female", |
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"ylacombe/vits_vctk_irish_male", |
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"ylacombe/vits_vctk_scottish_female", |
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"ylacombe/vits_ljs_irish_male", |
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"ylacombe/vits_ljs_scottish_female", |
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"ylacombe/mms-tam-finetuned-multispeaker", |
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"ylacombe/mms-spa-finetuned-chilean-multispeaker", |
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"ylacombe/mms-spa-finetuned-chilean", |
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"ylacombe/mms-tam-finetuned" |
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], |
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value="ylacombe/vits_ljs_welsh_male", |
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label="Model", |
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info="Model you want to test", |
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) |
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with gr.Column(): |
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outputs = [] |
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for i in range(max_speakers): |
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out_audio = gr.Audio(type="numpy", autoplay=False, label=f"Generated Audio - speaker {i}", show_label=True, visible=False) |
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outputs.append(out_audio) |
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btn.click(generate_audio, [inp_text, model_id], outputs) |
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demo_blocks.queue().launch() |
