import gradio as gr from gradio_imageslider import ImageSlider from pipeline_demofusion_sdxl import DemoFusionSDXLPipeline import torch import subprocess from subprocess import getoutput gpu_info = getoutput('nvidia-smi') def generate_images(prompt, negative_prompt, height, width, num_inference_steps, guidance_scale, cosine_scale_1, cosine_scale_2, cosine_scale_3, sigma, view_batch_size, stride, seed): if not("A100" in gpu_info): raise gr.Error("This demo will only run on A100 GPU upgrade.") model_ckpt = "stabilityai/stable-diffusion-xl-base-1.0" pipe = DemoFusionSDXLPipeline.from_pretrained(model_ckpt, torch_dtype=torch.float16) pipe = pipe.to("cuda") generator = torch.Generator(device="cuda") generator = generator.manual_seed(int(seed)) images = pipe(prompt, negative_prompt=negative_prompt, generator=generator, height=int(height), width=int(width), view_batch_size=int(view_batch_size), stride=int(stride), num_inference_steps=int(num_inference_steps), guidance_scale=guidance_scale, cosine_scale_1=cosine_scale_1, cosine_scale_2=cosine_scale_2, cosine_scale_3=cosine_scale_3, sigma=sigma, multi_decoder=True, show_image=False ) #return [image for _, image in enumerate(images)] return (images[0], images[-1]) iface = gr.Interface( fn=generate_images, inputs=[ gr.Textbox(label="Prompt"), gr.Textbox(label="Negative Prompt", value="blurry, ugly, duplicate, poorly drawn, deformed, mosaic"), gr.Slider(minimum=1024, maximum=4096, step=1024, value=2048, label="Height"), gr.Slider(minimum=1024, maximum=4096, step=1024, value=2048, label="Width"), gr.Slider(minimum=10, maximum=100, step=1, value=50, label="Num Inference Steps"), gr.Slider(minimum=1, maximum=20, step=0.1, value=7.5, label="Guidance Scale"), gr.Slider(minimum=0, maximum=5, step=0.1, value=3, label="Cosine Scale 1"), gr.Slider(minimum=0, maximum=5, step=0.1, value=1, label="Cosine Scale 2"), gr.Slider(minimum=0, maximum=5, step=0.1, value=1, label="Cosine Scale 3"), gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.8, label="Sigma"), gr.Slider(minimum=4, maximum=32, step=4, value=16, label="View Batch Size"), gr.Slider(minimum=8, maximum=96, step=8, value=64, label="Stride"), gr.Number(label="Seed", value=2013) ], #outputs=gr.Gallery(label="Generated Images"), outputs=ImageSlider(label="Comparison of SDXL and DemoFusion"), title="DemoFusion Gradio Demo", description="Generate images with the DemoFusion SDXL Pipeline. Runs on A100 GPU." ) iface.launch()