| 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) | |
| gr.HTML('''<br><br><br><center>You can duplicate this Space to skip the queue:<a href="https://huggingface.co/spaces/shariqfarooq/ZoeDepth?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a><br> | |
| <p><img src="https://visitor-badge.glitch.me/badge?page_id=shariqfarooq.zoedepth_demo_hf" alt="visitors"></p></center>''') | |
| if __name__ == '__main__': | |
| demo.queue().launch() |