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| import gradio as gr | |
| import voiceClone as vc | |
| import videoGenerate as vg | |
| model_list = [] | |
| output_audio = None | |
| image_error = None | |
| # Function to create model from audio file | |
| def create_voice_model(title, audio_file): | |
| global model_list | |
| new_model = vc.create_model(audio_file, title) | |
| if new_model: | |
| model_list.append((title, new_model)) # Store as (title, id) | |
| return f"Voice model {title} created" | |
| def update_dropdown_choices(): | |
| return gr.Dropdown(choices=[title for title, _ in model_list]) | |
| def on_model_select(selected_item): | |
| return next((model_id for title, model_id in model_list if title == selected_item), None) | |
| def generate_tts(model_id, text): | |
| return vc.tts(model_id, text) | |
| def create_talking_face(audio, image, aspect_ratio, resolution, text_prompt, seed): | |
| output_path = vg.generate_video(audio, image, aspect_ratio, resolution, text_prompt, seed) | |
| return output_path | |
| # Gradio UI components | |
| with gr.Blocks() as app: | |
| gr.Markdown(" # Deepfake Generator") | |
| gr.Markdown(""" ## Voice Cloning """) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("Generate Voice Model") | |
| audio_input = gr.Audio(sources=["upload", "microphone"], label="Record Voice Sample", type="filepath", interactive = True, info = "20-30 seconds of audio is recommended") | |
| title_input = gr.Textbox(label="Model Title", placeholder="Enter model title") | |
| output_textbox = gr.Label(label="Output", value = "") | |
| generate_model_button = gr.Button("Generate Voice Model") | |
| generate_model_button.click(create_voice_model, inputs=[title_input, audio_input], outputs=output_textbox) | |
| with gr.Column(scale=1): | |
| gr.Markdown("Generate Text to Speech (TTS)") | |
| update_models = gr.Button("Update Models") | |
| reference_id = gr.Textbox(label="Model ID", interactive=False, visible=False) | |
| model_dropdown = gr.Dropdown(label="Select Model", choices=[], interactive=True, info = "Select a model to use for TTS") | |
| model_dropdown.change(fn=on_model_select, inputs=model_dropdown, outputs= reference_id) | |
| update_models.click(update_dropdown_choices, outputs=model_dropdown) | |
| text_input = gr.Textbox(label="Text for TTS", placeholder="Enter text to synthesize", lines=3, max_length=300, | |
| info="Text for generated speech. You can add special effects to enhance the result: (break), (long-break), (breath), (laugh), (cough), (lip-smacking), (sigh)") | |
| tts_output = gr.Audio(label="TTS Output", type="filepath", interactive=False) | |
| generate_tts_button = gr.Button("Generate TTS") | |
| generate_tts_button.click(generate_tts, inputs=[reference_id, text_input], outputs=tts_output) | |
| gr.Markdown(""" ## Avatar Creation""") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| image_input = gr.Image(label="Upload Image", type="filepath", sources=["upload", "webcam"], interactive=True) | |
| aspect_ratio = gr.Radio(choices= ["1:1", "16:9", "9:16"], value= "1:1", label="Aspect Ratio") | |
| resolution = gr.Radio(choices= ["540p", "720p"], value= "720p", label="Resolution") | |
| text_prompt = gr.Textbox(label="(Optional) Text Prompt", placeholder="Enter text prompt to describe your avatar", lines=3, max_length = 150,info= "Influence the expressivity of generated avatar") | |
| seed = gr.Slider(minimum=1, maximum=10000, value=None, label="(Optional) Seed for generation ") | |
| with gr.Column(scale=1): | |
| output_video = gr.Video(label="Talking Head") | |
| generate_video_button = gr.Button("Generate Talking Face Avatar") | |
| generate_video_button.click(create_talking_face, inputs=[tts_output, image_input, aspect_ratio, resolution, text_prompt, seed], outputs=output_video) | |
| if __name__ == "__main__": | |
| app.launch() | |