import gradio as gr import torch from gradio_depth_pred import create_demo as create_depth_pred_demo from gradio_im_to_3d import create_demo as create_im_to_3d_demo from gradio_pano_to_3d import create_demo as create_pano_to_3d_demo css = """ #img-display-container { max-height: 50vh; } #img-display-input { max-height: 40vh; } #img-display-output { max-height: 40vh; } """ DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu' model = torch.hub.load('isl-org/ZoeDepth', "ZoeD_N", pretrained=True).to(DEVICE).eval() title = "# ZoeDepth" description = """Official demo for **ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth**. ZoeDepth is a deep learning model for metric depth estimation from a single image. Please refer to our [paper](https://arxiv.org/abs/2302.12288) or [github](https://github.com/isl-org/ZoeDepth) for more details.""" with gr.Blocks(css=css) as demo: gr.Markdown(title) gr.Markdown(description) with gr.Tab("Depth Prediction"): create_depth_pred_demo(model) with gr.Tab("Image to 3D"): create_im_to_3d_demo(model) with gr.Tab("360 Panorama to 3D"): create_pano_to_3d_demo(model) if __name__ == '__main__': demo.queue().launch()