Spaces:
Running
on
Zero
Running
on
Zero
add description
Browse files- README.md +1 -1
- app.py +14 -1
- demo_utils/examples/log.csv +1 -1
README.md
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@@ -9,7 +9,7 @@ sdk_version: 5.35.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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short_description: SceneDINO
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app_file: app.py
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pinned: false
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license: apache-2.0
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short_description: SceneDINO (ICCV 2025)
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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@@ -190,6 +190,18 @@ def demo_run(image: str,
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return output_2d, glb_path
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demo = gr.Interface(
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demo_run,
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inputs=[
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gr.Radio(label="Backbone", choices=["DINO (ViT-B)", "DINOv2 (ViT-B)"]),
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gr.Radio(label="Mode", choices=["Feature PCA 1-3", "Feature PCA 4-6", "Feature PCA 7-9", "SSC (unsup.)", "SSC (linear)"]),
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gr.Slider(label="Density threshold", minimum=0, maximum=1, step=0.05, value=0.2),
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gr.Slider(label="Resolution [m]", minimum=0.05, maximum=0.5, step=0.
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gr.Slider(label="X Range [m]", minimum=1, maximum=50, step=1, value=10),
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gr.Slider(label="Y Range [m]", minimum=1, maximum=50, step=1, value=10),
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gr.Slider(label="Z Range [m]", minimum=1, maximum=100, step=1, value=20),
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@@ -212,6 +224,7 @@ demo = gr.Interface(
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],
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title="SceneDINO Demo",
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examples="demo_utils/examples",
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)
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demo.launch()
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return output_2d, glb_path
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markdown_description = """
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[Paper](https://arxiv.org/abs/xxxx.xxxxx) | [Code](https://github.com/tum-vision/scenedino) | [Project Page](https://visinf.github.io/scenedino/)
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Upload a single image to infer 3D geometry and semantics with **SceneDINO**. You can find some example images below.
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- **Feature PCA**
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We visualize our high-dimensional feature field using PCA and visualizing three of the components in RGB. Interactively adjust which are visualized.
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- **SSC** (Semantic Scene Completion)
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Our features are used downstream for semantic predictions. Choose between the fully unsupervised approach or the linear probing approach.
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<span style="color:orange">⚠️ NOTE: We assume the intrinsic camera matrix of KITTI-360, images are cropped and rescaled to 192x640. Further note our demo's voxel limit of 5M. </span>
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"""
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demo = gr.Interface(
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demo_run,
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inputs=[
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gr.Radio(label="Backbone", choices=["DINO (ViT-B)", "DINOv2 (ViT-B)"]),
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gr.Radio(label="Mode", choices=["Feature PCA 1-3", "Feature PCA 4-6", "Feature PCA 7-9", "SSC (unsup.)", "SSC (linear)"]),
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gr.Slider(label="Density threshold", minimum=0, maximum=1, step=0.05, value=0.2),
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gr.Slider(label="Resolution [m]", minimum=0.05, maximum=0.5, step=0.05, value=0.2),
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gr.Slider(label="X Range [m]", minimum=1, maximum=50, step=1, value=10),
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gr.Slider(label="Y Range [m]", minimum=1, maximum=50, step=1, value=10),
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gr.Slider(label="Z Range [m]", minimum=1, maximum=100, step=1, value=20),
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],
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title="SceneDINO Demo",
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examples="demo_utils/examples",
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description=markdown_description,
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)
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demo.launch()
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demo_utils/examples/log.csv
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image, mode, sigma_threshold, resolution, x_range, y_range, z_range
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"kitti-360.png","
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image, mode, sigma_threshold, resolution, x_range, y_range, z_range
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"kitti-360.png","DINOv2 (ViT-B)","Feature PCA 1-3",0.25,0.25,20,20,50
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