import spaces import os from PIL import Image import gradio as gr from pathlib import Path import uuid import torch import shutil OUTPUT_DIR = "./output" os.makedirs(OUTPUT_DIR, exist_ok=True) @spaces.GPU @torch.inference_mode() def generate_and_process_3d(image: Image.Image) -> tuple[str | None, str | None]: try: # Export to GLB unique_id = str(uuid.uuid4()) filename = f'model_{unique_id}.glb' output_path = os.path.join(OUTPUT_DIR, filename) public_url = f"https://john6666-image-to-3d-test2.hf.space/gradio_api/file={Path(output_path).resolve()}" image_path = "image.png" image.save(image_path) shutil.copy(image_path, output_path) return output_path, public_url except Exception as e: print(f"Error during generation: {str(e)}") return None, None css = """ .image { margin: 0px auto; object-fit: contain; !important; } .info { align-items: center; text-align: center; } """ # Create Gradio app using Blocks with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, fill_height=True, elem_id="container", css=css) as demo: gr.Markdown("This space is based on [Stable Point-Aware 3D](https://huggingface.co/spaces/stabilityai/stable-point-aware-3d) by Stability AI, [Text to 3D](https://huggingface.co/spaces/jbilcke-hf/text-to-3d) by jbilcke-hf.", elem_classes="info") input_img = gr.Image( type="pil", label="Input Image", sources="upload", image_mode="RGBA", width=40, elem_classes="image", ) model_output = gr.Model3D( label="Generated .GLB model", clear_color=[0.0, 0.0, 0.0, 0.0], visible=False ) output_url = gr.Textbox(label="Output URL", value="", lines=1, interactive=False, show_copy_button=True) # Event handler input_img.upload( fn=generate_and_process_3d, inputs=[input_img], outputs=[model_output, output_url], api_name="generate" ) if __name__ == "__main__": demo.queue().launch(ssr_mode=False, allowed_paths=[Path(OUTPUT_DIR).resolve()])