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| import os | |
| import shutil | |
| import gradio as gr | |
| from PIL import Image | |
| import subprocess | |
| #os.chdir('Restormer') | |
| examples = [['project/cartoon2.jpg','project/video1.mp4'], | |
| ['project/cartoon3.jpg','project/video2.mp4'], | |
| ['project/celeb1.jpg','project/video1.mp4'], | |
| ['project/celeb2.jpg','project/video2.mp4'], | |
| ] | |
| title = "DaGAN" | |
| description = """ | |
| Gradio demo for <b>Depth-Aware Generative Adversarial Network for Talking Head Video Generation</b>, CVPR 2022. <a href='https://arxiv.org/abs/2203.06605'>[Paper]</a><a href='https://github.com/harlanhong/CVPR2022-DaGAN'>[Github Code]</a>\n Read more at the links below. Upload a video file (cropped to face), a facial image and have fun :D. Please note that your video will be trimmed to first 8 seconds. | |
| """ | |
| ##With Restormer, you can perform: (1) Image Denoising, (2) Defocus Deblurring, (3) Motion Deblurring, and (4) Image Deraining. | |
| ##To use it, simply upload your own image, or click one of the examples provided below. | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2203.06605'>Depth-Aware Generative Adversarial Network for Talking Head Video Generation</a> | <a href='https://github.com/harlanhong/CVPR2022-DaGAN'>Github Repo</a></p>" | |
| def inference(img, video): | |
| if not os.path.exists('temp'): | |
| os.system('mkdir temp') | |
| # trim video to 8 seconds | |
| cmd = f"ffmpeg -y -ss 00:00:00 -i {video} -to 00:00:08 -c copy video_input.mp4" | |
| subprocess.run(cmd.split()) | |
| video = "video_input.mp4" | |
| #### Resize the longer edge of the input image | |
| # os.system("ffmpeg -y -ss 00:00:00 -i {video} -to 00:00:08 -c copy temp/driving_video.mp4") | |
| # driving_video = "video_input.mp4" | |
| os.system("python demo_dagan.py --source_image {} --driving_video {} --output 'temp/rst.mp4'".format(img,video)) | |
| return f'temp/rst.mp4' | |
| gr.Interface( | |
| inference, | |
| [ | |
| gr.inputs.Image(type="filepath", label="Source Image"), | |
| gr.inputs.Video(type='mp4',label="Driving Video"), | |
| ], | |
| gr.outputs.Video(type="mp4", label="Output Video"), | |
| title=title, | |
| description=description, | |
| article=article, | |
| theme ="huggingface", | |
| examples=examples, | |
| allow_flagging=False, | |
| ).launch(debug=False,enable_queue=True) | |