lpiccinelli-eth/UniDepth

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1246 stars · 117 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

UniDepth is a Python library and research codebase for universal monocular metric depth estimation from single images, based on CVPR 2024 and UniDepthV2 papers from ETH Zurich. It provides pretrained models, inference, and training code that predict metric depth without requiring camera intrinsics.

Use cases

• estimate metric depth from a single image
• 3d reconstruction from monocular photos
• depth estimation for robotics or autonomous navigation
• run state-of-the-art depth models on KITTI or NYU Depth
• get point clouds from single camera images

When to choose

• you need metric (not just relative) depth from a single image without camera intrinsics
• you want a research-grade model with pretrained weights and training code
• you work in PyTorch and need benchmark-leading depth estimation

When to avoid

• you need real-time depth on low-power or CPU-only hardware
• you need a non-research license for commercial use (license is custom)
• you need stereo or multi-view depth rather than monocular

Facets

library · maturity active

computer-vision image-processing machine-learning deep-learning computer-vision machine-learning artificial-intelligence robotics python depth-estimation monocular-depth metric-depth 3d-reconstruction research-code pytorch linux gpu

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markdown · JSON · MCP: product_card(name="lpiccinelli-eth/UniDepth")