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| import gradio as gr | |
| from PIL import Image | |
| from diffusers import StableDiffusionLDM3DPipeline | |
| # Load the model. Do this once to avoid reloading on every request. | |
| pipe = StableDiffusionLDM3DPipeline.from_pretrained("Intel/ldm3d-pano") | |
| def generate_images(prompt, guidance_scale=7.0, num_inference_steps=50): | |
| output = pipe( | |
| prompt, | |
| width=1024, | |
| height=512, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_inference_steps, | |
| ) | |
| rgb_image, depth_image = output.rgb, output.depth | |
| # Convert to PIL Images for Gradio compatibility | |
| rgb_image = Image.fromarray(rgb_image[0]) | |
| depth_image = Image.fromarray(depth_image[0]) | |
| return rgb_image, depth_image | |
| iface = gr.Interface( | |
| fn=generate_images, | |
| inputs=[ | |
| "text", | |
| gr.Slider(0, 20, value=7.0, label="Guidance Scale"), | |
| gr.Slider(0, 100, value=50, label="Inference Steps") | |
| ], | |
| outputs=["image", "image"], | |
| title="ldm3d-pano Image Generator" | |
| ) | |
| iface.launch() | |