| | import gradio as gr |
| | from inference import infer |
| |
|
| | def greet(image, prompt): |
| | restore_img = infer(img=image, text_prompt=prompt) |
| | return restore_img |
| |
|
| | title = "🖼️ ICDR 🖼️" |
| | description = ''' ## ICDR: Image Restoration Framework for Composite Degradation following Human Instructions |
| | |
| | Our Github : https://github.com/kimww42/ICDR |
| | |
| | Siwon Kim, Donghyeon Yoon |
| | |
| | Ajou Univ |
| | |
| | it can take a long time to operate in cpu environment. (30 minutes per sheet), In this case, you can run app.py directly to test demo in a local environment.(https://github.com/kimww42/ICDR) |
| | |
| | ''' |
| |
|
| |
|
| | article = "<p style='text-align: center'><a href='https://github.com/kimww42/ICDR' target='_blank'>ICDR</a></p>" |
| |
|
| | |
| | examples = [['input/00013.png', "Remove the rain as much as possible like the picture taken on a clear day."], |
| | ['input/00010.png', "I love this photo, could you remove the haze and more brighter?"], |
| | ['input/00058.png', "I have to post an emotional shot on Instagram, but it was shot too foggy and too dark. Change it like a sunny day and brighten it up!"], |
| | ['input/00075.png', "Remove the rain from the video, remove the brightness and fog"], |
| | ] |
| |
|
| | css = """ |
| | .image-frame img, .image-container img { |
| | width: auto; |
| | height: auto; |
| | max-width: none; |
| | } |
| | """ |
| |
|
| |
|
| | demo = gr.Interface( |
| | fn=greet, |
| | inputs=[gr.Image(type="pil", label="Input"), |
| | gr.Text(label="Prompt") ], |
| | outputs=[gr.Image(type="pil", label="Ouput")], |
| | title=title, |
| | description=description, |
| | article=article, |
| | examples=examples, |
| | css=css, |
| | ) |
| |
|
| | if __name__ == "__main__": |
| | demo.launch() |
