LiheYoung/Depth-Anything

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

8195 stars · 618 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Depth Anything is a monocular depth estimation foundation model trained on 1.5M labeled and 62M+ unlabeled images, released as a Python library with pretrained checkpoints. It supports zero-shot relative and metric depth estimation and integrates with ControlNet for image generation.

Use cases

• estimate depth from a single image
• generate depth maps for photos
• use depth conditioning in stable diffusion controlnet
• run monocular depth estimation on video frames
• fine-tune a depth model on NYUv2 or KITTI
• get metric depth estimates from images

When to choose

• you need robust zero-shot depth estimation from single images
• you want a depth processor for diffusion-based image generation
• you need a well-validated model with ONNX and TensorRT deployments available

When to avoid

• you need real-time depth on edge devices without GPU acceleration
• you need multi-view or stereo depth from camera rigs
• you want the newest model quality - Depth Anything V2 supersedes this version

Facets

library · maturity maintenance

machine-learning computer-vision image-processing deep-learning computer-vision deep-learning artificial-intelligence image-processing python cross-platform depth-estimation monocular-depth foundation-model controlnet stable-diffusion cvpr-2024 onnx tensorrt gpu

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markdown · JSON · MCP: product_card(name="LiheYoung/Depth-Anything")