isl-org/MiDaS

Health v2 · maintenance only

Flags: archived

Adoption not part of the score

5420 stars · 724 forks observed · 2026-08-28

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

MiDaS is a Python library with pretrained models for robust monocular depth estimation from a single image, based on the TPAMI 2022 paper and Vision Transformers for Dense Prediction. It offers multiple model variants trading off quality and speed, including small models for embedded devices and OpenVINO support for Intel CPUs.

Use cases

• estimate depth from a single photo
• run monocular depth estimation on embedded devices
• add depth maps to a computer vision pipeline
• compare depth estimation model quality vs speed
• use pretrained depth models without training data

When to choose

• you need state-of-the-art zero-shot depth estimation from single images
• you want a range of model sizes from embedded to high accuracy
• you want MIT-licensed pretrained depth models

When to avoid

• you need metric depth in real-world units rather than relative depth
• you need stereo or multi-view depth from multiple cameras
• you need real-time depth on CPU without OpenVINO-compatible hardware

Facets

library · maturity stable

machine-learning deep-learning computer-vision image-processing computer-vision machine-learning deep-learning robotics python cross-platform monocular-depth-estimation depth-prediction vision-transformer zero-shot-transfer pretrained-models pytorch gpu

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