# Tom94/tev

High dynamic range (HDR) image viewer for people who care about colors

Repository: https://github.com/Tom94/tev
Canonical: https://ross.abutalabs.com/products/tev
Language: C++
License: GPL-3.0
License Family: copyleft
Topics: exr, hdr, macos, avif, heic, heif, jxl, linux, png, windows, dds, dng, raw, tiff, webp, cicp, color, icc, viewer, jxr
Last push: 2026-08-23T05:03:42+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 99, longevity 100
- inputs: {"age_days": 3294, "days_push": 10, "days_rel": 10, "gap_med": 10.0, "n_releases_24m": 29}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1426, forks 123 (observed 2026-08-28T04:04:41.694796+00:00)

## What it is
tev is a high dynamic range (HDR/EDR) image viewer written in C++ for people who care about accurate colors. It supports many formats (EXR, AVIF, JXL, PNG, TIFF, RAW, etc.), color profiles (ICC, CICP), and offers comparison tools like histograms, tonemaps, and error metrics.

## Use cases
- view HDR images with accurate colors
- compare two EXR renders with false-color error metrics
- inspect multi-layer OpenEXR images with aux channels
- pixel-peep images with histograms and tonemaps
- view images with ICC or CICP color profiles
- quickly browse hundreds of images
- display HDR content on any operating system

## When to avoid
- you only need a lightweight viewer for plain SDR photos
- you need a full image editor with retouching tools
- you need batch image conversion or processing rather than viewing

## Facets
- artifact type: application
- maturity: active
- function: image-processing, gui, cli
- domain: graphics, image-processing, photography, media, developer-tools
- platform: windows, cross-platform
- tags: hdr, exr, image-viewer, color-management, icc, cicp, tonemapping, false-color, error-metrics, raw-formats, macos, linux

## Member repositories
- Tom94/tev (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.694796+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 2026-08-30T04:37:25.396888+00:00, confidence not recorded.
  - readme: https://github.com/Tom94/tev (fetched 2026-08-28T04:04:41.694796+00:00, sha d6fff334203e)
- Data as of 2026-08-30T08:39:29.467469+00:00.