| import gradio as gr | |
| from gradio_client import Client, file | |
| # def greet(name, intensity): | |
| # return "Hello, " + name + "!" * int(intensity) | |
| def test(text): | |
| client = Client("stabilityai/stable-fast-3d") | |
| result = client.predict( | |
| input_image=file('https://stabilityai-stable-fast-3d.hf.space/file=/tmp/gradio/cedf71215ac1d8f6d44cd9cc94a65c5c2b5b76b0/banana.jpg'), | |
| foreground_ratio=0.85, | |
| api_name="/run_button" | |
| ) | |
| # client = Client("stabilityai/TripoSR") | |
| # result = client.predict( | |
| # "https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png", # filepath in 'Processed Image' Image component | |
| # 32, # float (numeric value between 32 and 320) in 'Marching Cubes Resolution' Slider component | |
| # api_name="/generate" | |
| # ) | |
| return result | |
| # demo = gr.Interface( | |
| # fn=greet, | |
| # inputs=["text", "slider"], | |
| # outputs=["text"], | |
| # ) | |
| demo = gr.Interface( | |
| fn=test, | |
| inputs=["text"], | |
| outputs=["text"], | |
| ) | |
| demo.launch(share=True) | |