imgviz
Image Visualization Tools
Decision gist · record as of 2026-08-14
Yes. imgviz is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. Install it if you work with non-RGB image data (depth, labels, masks) in computer vision or ML and want a lightweight, ready-made toolkit for visualization rather than writing custom colorization and compositing code.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction: pure Python wheel, three lightweight runtime dependencies (numpy, pillow, cmap), and active maintenance with a release within the last 65 days.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute imgviz freely in commercial or private projects with minimal restrictions.
last release 2026-06-10 (65 days) · last repo commit 2026-08-05 · 265 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 103,382 downloads/mo, #12,808 on PyPI
Alternatives
Verify before relying
pip install imgviz
import numpy as np
import imgviz
data = imgviz.data.arc2017()
rgb = data["rgb"]
gray = imgviz.rgb2gray(rgb)
depth = data["depth"]
depthviz = imgviz.colorize(depth, vmin=0.3, vmax=1)- Whether optional dependencies (e.g., skimage) are required for specific visualization functions or only extend functionality.
- Performance characteristics when processing large images or batch operations.
What it is and what it does
imgviz is a Python library for converting and visualizing non-RGB image data—such as depth maps, semantic segmentation labels, instance masks, and custom per-pixel flags—into displayable RGB images. It wraps common visualization patterns (colorization with colormaps, label-to-color mapping, instance bounding boxes and masks, pie-chart glyphs) and provides utilities for image composition and tiling. The library depends on numpy for array operations, pillow for image I/O and basic manipulation, and cmap for colormap support.
The package is designed for computer vision and machine learning workflows where intermediate representations (depth, class labels, instance IDs) need to be rendered for inspection, debugging, or publication. It handles the boilerplate of mapping scalar or categorical data to colors, overlaying annotations on images, and arranging multiple visualizations into a grid.
Use it for
- Visualize depth sensor output by colorizing depth maps with a perceptually uniform colormap.
- Convert semantic segmentation label maps to RGB images with per-class colors and optional class name overlays.
- Render instance segmentation results by drawing bounding boxes, masks, and captions on a base image.
- Tile and arrange multiple visualization outputs (RGB, depth, labels, masks) into a single composite image for comparison.
- Overlay per-instance metadata (flags, statistics) as pie-chart glyphs at instance centroids.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
imgviz is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. Install it if you work with non-RGB image data (depth, labels, masks) in computer vision or ML and want a lightweight, ready-made toolkit for visualization rather than writing custom colorization and compositing code.
Install
imgviz on PyPI
Before you install
Low friction: pure Python wheel, three lightweight runtime dependencies (numpy, pillow, cmap), and active maintenance with a release within the last 65 days.
Requires Python 3.10 or later.
License in practice
MIT license is permissive; you can use, modify, and distribute imgviz freely in commercial or private projects with minimal restrictions.
Quickstart
pip install imgviz
import numpy as np
import imgviz
data = imgviz.data.arc2017()
rgb = data["rgb"]
gray = imgviz.rgb2gray(rgb)
depth = data["depth"]
depthviz = imgviz.colorize(depth, vmin=0.3, vmax=1)Verify before relying
- Whether optional dependencies (e.g., skimage) are required for specific visualization functions or only extend functionality.
- Performance characteristics when processing large images or batch operations.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagescmapnumpypillow |
| Maintenance | Actively maintained 65 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 103,382 / month, #12,808 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development :: Libraries :: Python Modules |
Evidence: imgviz-2.1.0-py3-none-any.whl
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