import gradio as gr def predict_image(image,find,transform): if(transform == "oreo cake"): return("cake_oreo.png") elif(transform == "ice"): return("cake_ice.png") elif(transform == "brioche"): return("cake_brioche.png") elif(transform == "spinach moss cake"): return("cake_spinach.png") def predict_video(image,find,transform): if(transform == "stained glass giraffe"): return("giraffe_stainedglass.mp4") elif(transform == "giraffe with a neck warmer"): return("giraffe_neck_warmer.mp4") elif(transform=="giraffe with a hairy colorful mane"): return("giraffe_hairy_colorful_mane.mp4") #Image inputs image_editing = gr.Image(label="Input image",interactive=False) prompt_find = gr.Textbox(label="What to find on the image", interactive=False) prompt_transform = gr.Textbox(label="What to turn the image into", interactive=False) image_out = gr.outputs.Image() results_image = ['cake_oreo.png',"cake_ice.png","cake_brioche.png", "cake_spinach.png"] examples_image=[['cake.jpg','cake','oreo cake'], ['cake.jpg','cake','ice'], ['cake.jpg','cake','brioche'], ['cake.jpg','cake','spinach moss cake']] #Video inputs video_editing = gr.Video(label="Input video", interactive=False) prompt_find_video = gr.Textbox(label="What to find on the image", interactive=False) prompt_transform_video = gr.Textbox(label="What to turn the image into", interactive=False) video_out = gr.outputs.Video() results_video = ['cake_oreo.png',"cake_ice.png","cake_brioche.png", "cake_spinach.png"] examples_video=[['giraffe.mp4','giraffe','stained glass giraffe'], ['giraffe.mp4','giraffe','giraffe with a neck warmer'], ['giraffe.mp4','giraffe','giraffe with a hairy colorful mane']] with gr.Blocks() as demo: gr.Markdown('''# Text2LIVE: Text-Driven Layered Image and Video Editing This an interactive pre-processed demo for Text2Live. Check out the [paper](https://arxiv.org/abs/2204.02491) and the [code](https://github.com/omerbt/Text2LIVE) and the [project page](https://text2live.github.io/) ''') with gr.Tabs(): with gr.TabItem("Image editing"): gr.Interface( fn=predict_image, inputs=[image_editing, prompt_find, prompt_transform], outputs=image_out, examples=examples_image, allow_flagging=False, live=True) with gr.TabItem("Video editing"): gr.Interface( fn=predict_video, inputs=[video_editing, prompt_find_video, prompt_transform_video], outputs=video_out, examples=examples_video, allow_flagging=False, live=True) gr.Markdown("Bibtex") gr.Markdown('''``` @article{bar2022text2live, title = {Text2LIVE: Text-Driven Layered Image and Video Editing}, author = {Bar-Tal, Omer and Ofri-Amar, Dolev and Fridman, Rafail and Kasten, Yoni and Dekel, Tali}, journal = {arXiv preprint arXiv:2204.02491}, year = {2022} } ```''') demo.launch()