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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() | |