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on
T4
| import gradio as gr | |
| import subprocess | |
| from moviepy.editor import VideoFileClip | |
| def convert_to_mp4_with_aac(input_path, output_path): | |
| # Load the video | |
| video = VideoFileClip(input_path) | |
| # Set the output format to mp4 with AAC codec | |
| video.write_videofile(output_path, codec="libx264", audio_codec="aac") | |
| return output_path | |
| def load_audio(audio_listed): | |
| return f"data/audio/{audio_listed}" | |
| def execute_command(command: str) -> None: | |
| subprocess.run(command, check=True) | |
| def infer(audio_input, image_path, emotional_style): | |
| output_name = "lipsynced_result" | |
| command = [ | |
| f"python", | |
| f"inference_for_demo_video.py", | |
| f"--wav_path={audio_input}", | |
| f"--style_clip_path=data/style_clip/3DMM/{emotional_style}", | |
| f"--pose_path=data/pose/RichardShelby_front_neutral_level1_001.mat", | |
| f"--image_path={image_path}", | |
| f"--cfg_scale=1.0", | |
| f"--max_gen_len=30", | |
| f"--output_name={output_name}" | |
| ] | |
| execute_command(command) | |
| # Convert video to compatible codecs | |
| input_file = f"output_video/{output_name}.mp4" | |
| output_file = f"{output_name}.mp4" | |
| result = convert_to_mp4_with_aac(input_file, output_file) | |
| return result | |
| css=""" | |
| #col-container{ | |
| margin: 0 auto; | |
| max-width: 940px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.HTML(""" | |
| <h1 style="text-align: center;">DreamTalk</h1> | |
| <h2 style="text-align: center;">When Expressive Talking Head Generation Meets Diffusion Probabilistic Models</h2> | |
| <p style="text-align: center;"> | |
| DreamTalk is a diffusion-based audio-driven expressive talking head generation framework that can produce high-quality talking head videos across diverse speaking styles. <br /> | |
| DreamTalk exhibits robust performance with a diverse array of inputs, including songs, speech in multiple languages, noisy audio, and out-of-domain portraits. | |
| </p> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_path = gr.Image(label="Image", type="filepath", sources=["upload"]) | |
| audio_input = gr.Audio(label="Audio input", type="filepath", sources=["upload"], value="data/audio/acknowledgement_english.m4a") | |
| with gr.Row(): | |
| audio_list = gr.Dropdown( | |
| label="Choose an audio (optional)", | |
| choices=[ | |
| "German1.wav", "German2.wav", "German3.wav", "German4.wav", | |
| "acknowledgement_chinese.m4a", "acknowledgement_english.m4a", | |
| "chinese1_haierlizhi.wav", "chinese2_guanyu.wav", | |
| "french1.wav", "french2.wav", "french3.wav", | |
| "italian1.wav", "italian2.wav", "italian3.wav", | |
| "japan1.wav", "japan2.wav", "japan3.wav", | |
| "korean1.wav", "korean2.wav", "korean3.wav", | |
| "noisy_audio_cafeter_snr_0.wav", "noisy_audio_meeting_snr_0.wav", "noisy_audio_meeting_snr_10.wav", "noisy_audio_meeting_snr_20.wav", "noisy_audio_narrative.wav", "noisy_audio_office_snr_0.wav", "out_of_domain_narrative.wav", | |
| "spanish1.wav", "spanish2.wav", "spanish3.wav" | |
| ], | |
| value = "acknowledgement_english.m4a" | |
| ) | |
| audio_list.change( | |
| fn = load_audio, | |
| inputs = [audio_list], | |
| outputs = [audio_input] | |
| ) | |
| emotional_style = gr.Dropdown( | |
| label = "emotional style", | |
| choices = [ | |
| "M030_front_angry_level3_001.mat", | |
| "M030_front_contempt_level3_001.mat", | |
| "M030_front_disgusted_level3_001.mat", | |
| "M030_front_fear_level3_001.mat", | |
| "M030_front_happy_level3_001.mat", | |
| "M030_front_neutral_level1_001.mat", | |
| "M030_front_sad_level3_001.mat", | |
| "M030_front_surprised_level3_001.mat", | |
| "W009_front_angry_level3_001.mat", | |
| "W009_front_contempt_level3_001.mat", | |
| "W009_front_disgusted_level3_001.mat", | |
| "W009_front_fear_level3_001.mat", | |
| "W009_front_happy_level3_001.mat", | |
| "W009_front_neutral_level1_001.mat", | |
| "W009_front_sad_level3_001.mat", | |
| "W009_front_surprised_level3_001.mat", | |
| "W011_front_angry_level3_001.mat", | |
| "W011_front_contempt_level3_001.mat", | |
| "W011_front_disgusted_level3_001.mat", | |
| "W011_front_fear_level3_001.mat", | |
| "W011_front_happy_level3_001.mat", | |
| "W011_front_neutral_level1_001.mat", | |
| "W011_front_sad_level3_001.mat", | |
| "W011_front_surprised_level3_001.mat" | |
| ], | |
| value = "M030_front_neutral_level1_001.mat" | |
| ) | |
| gr.Examples( | |
| examples = [ | |
| "data/src_img/uncropped/face3.png", | |
| "data/src_img/uncropped/male_face.png", | |
| "data/src_img/uncropped/uncut_src_img.jpg", | |
| "data/src_img/cropped/chpa5.png", | |
| "data/src_img/cropped/cut_img.png", | |
| "data/src_img/cropped/f30.png", | |
| "data/src_img/cropped/menglu2.png", | |
| "data/src_img/cropped/nscu2.png", | |
| "data/src_img/cropped/zp1.png", | |
| "data/src_img/cropped/zt12.png" | |
| ], | |
| inputs=[image_path], | |
| examples_per_page=5 | |
| ) | |
| run_btn = gr.Button("Run") | |
| with gr.Column(): | |
| output_video = gr.Video(format="mp4") | |
| gr.HTML(""" | |
| <img src="https://github.com/ali-vilab/dreamtalk/raw/main/media/teaser.gif" style="margin: 0 auto;border-radius: 10px;" /> | |
| """) | |
| run_btn.click( | |
| fn = infer, | |
| inputs = [audio_input, image_path, emotional_style], | |
| outputs = [output_video] | |
| ) | |
| demo.queue().launch() |