# compphoto/BoostingMonocularDepth

Repository: https://github.com/compphoto/BoostingMonocularDepth
Canonical: https://ross.abutalabs.com/products/boostingmonoculardepth
Language: Python
License: NOASSERTION
License Family: other
Last push: 2024-08-06T21:34:51+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1919, "days_push": 757, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1507, forks 202 (observed 2026-08-28T04:04:55.170818+00:00)

## What it is
A Python research implementation for boosting monocular depth estimation to high resolution using a double-estimation merging operator, supporting MiDaS and LeRes depth networks. It produces high-resolution depth maps from single RGB images and includes a related scale-invariant depth estimation follow-up (SI-depth, SIGGRAPH 2024).

## Use cases
- generate high-resolution depth maps from single photos
- boost MiDaS or LeRes depth estimates to higher resolution
- estimate depth from a single RGB image
- merge low-res and high-res monocular depth predictions
- research on monocular depth estimation networks
- create depth maps for 3D projection from images

## When to choose
- you need high-resolution depth maps from single images
- you want to apply the double-estimation merging operator to MiDaS or LeRes outputs
- you are doing computer vision research on monocular depth estimation

## When to avoid
- you need real-time depth estimation on edge devices
- you want a production-ready supported product with a clear license
- you need a maintained library with active development

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, computer-vision, image-processing
- domain: computer-vision, machine-learning, image-processing, deep-learning
- platform: python, windows
- tags: monocular-depth-estimation, depth-maps, high-resolution, research-code, midas, leres, siggraph, linux, macos, gpu

## Member repositories
- compphoto/BoostingMonocularDepth (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:55.170818+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:32:36.102373+00:00, confidence not recorded.
  - readme: https://github.com/compphoto/BoostingMonocularDepth (fetched 2026-08-28T04:04:55.170818+00:00, sha 014912f251c4)
- Data as of 2026-08-30T08:39:29.467469+00:00.