| import gradio as gr | |
| from gradio_client import Client, handle_file | |
| def get_speech(text, voice): | |
| client = Client("collabora/WhisperSpeech") | |
| result = client.predict( | |
| multilingual_text=text, | |
| speaker_audio=voice, | |
| speaker_url="", | |
| cps=14, | |
| api_name="/whisper_speech_demo" | |
| ) | |
| print(result) | |
| return result | |
| def get_dreamtalk(image_in, speech): | |
| client = Client("fffiloni/dreamtalk") | |
| result = client.predict( | |
| audio_input=handle_file(speech), | |
| image_path=handle_file(image_in), | |
| emotional_style="M030_front_neutral_level1_001.mat", | |
| api_name="/infer" | |
| ) | |
| print(result) | |
| return result['video'] | |
| def pipe (text, voice, image_in): | |
| speech = get_speech(text, voice) | |
| try: | |
| video = get_dreamtalk(image_in, speech) | |
| except: | |
| raise gr.Error('An error occurred while loading DreamTalk: Image may not contain any face') | |
| return video | |
| with gr.Blocks() as demo: | |
| with gr.Column(): | |
| gr.HTML(""" | |
| <h2 style="text-align: center;"> | |
| Whisper Speech X Dreamtalk | |
| </h2> | |
| <p style="text-align: center;"></p> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_in = gr.Image(label="Portrait IN", type="filepath", value="./einstein.jpg") | |
| with gr.Column(): | |
| voice = gr.Audio(type="filepath", label="Upload or Record Speaker audio (Optional voice cloning)") | |
| text = gr.Textbox(label="text") | |
| submit_btn = gr.Button('Submit') | |
| with gr.Column(): | |
| video_o = gr.Video(label="Video result") | |
| submit_btn.click( | |
| fn = pipe, | |
| inputs = [ | |
| text, voice, image_in | |
| ], | |
| outputs = [ | |
| video_o | |
| ], | |
| concurrency_limit = 3 | |
| ) | |
| demo.queue(max_size=10).launch(show_error=True, show_api=False) |