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| import gradio as gr | |
| import torch | |
| from diffusers import ShapEPipeline | |
| from diffusers.utils import export_to_gif | |
| # Load the ShapE model | |
| ckpt_id = "openai/shap-e" | |
| pipe = ShapEPipeline.from_pretrained(ckpt_id) | |
| def generate_shap_e_gif(prompt): | |
| guidance_scale = 15.0 | |
| images = pipe( | |
| prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=64, | |
| ).images | |
| gif_path = export_to_gif(images, f"{prompt}_3d.gif") | |
| return gif_path | |
| # Create the Gradio interface | |
| demo = gr.Interface( | |
| fn=generate_shap_e_gif, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter a prompt"), | |
| outputs=gr.File(), | |
| title="ShapE 3D GIF Generator", | |
| description="Enter a prompt to generate a 3D GIF using the ShapE model." | |
| ) | |
| # Run the app | |
| if __name__ == "__main__": | |
| demo.launch() | |