import gradio as gr
from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("uripper/GIANNIS", revision="ONNX")
pipeline.to("cuda")
im = pipeline(height=1,width=1,num_channels=1, num_inference_steps=1).images[0]
im.show()
# When a user clicks button, pipeline will generate an image

# def pipeline_interface():
#     pipeline.to("cuda")
#     return pipeline("height=100,width=100").images[0]

# iface = gr.Interface(fn=pipeline_interface, inputs=[], outputs="image")

# iface.launch()