opencv/opencv-python

Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.

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Summary Information

Updated 2 minutes ago
Added to GitGenius on September 12th, 2026
Created on April 8th, 2016
Open Issues & Pull Requests: 201 (+0)
GitHub issues: Enabled
Number of forks: 1,041
Total Stargazers: 5,386 (+0)
Total Subscribers: 85 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.8 days
Mean response time: 34.1 days
90th percentile: 88.1 days
Tracked items: 169

Most active contributors

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 98% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 60% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 4% of issues opened in the past year have been closed. Three people close 69% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 115
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 651 days
Stale 30+ days: 98
Stale 90+ days: 91

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • question (15)
  • bug (9)
  • incomplete (7)
  • enhancement (4)
  • wontfix (3)
  • help wanted (2)
  • duplicate (1)

Detailed Description

opencv-python is a Python package distribution tool that provides precompiled OpenCV binaries for multiple platforms and configurations.

The project solves the problem of making OpenCV accessible to Python developers without requiring compilation from source. It distributes prebuilt wheel packages through PyPI, eliminating the need for users to compile OpenCV themselves or manage complex build dependencies. The approach uses an automated CI toolchain to generate these precompiled packages across different operating systems and Python versions, supporting the manylinux standard for broad Linux compatibility.

Developers should choose this tool if they need OpenCV in Python without the overhead of building from source. The project offers four distinct package variants to match different deployment scenarios: standard packages for desktop environments with GUI support, and headless variants for server deployments like Docker containers that do not require graphical functionality. The headless packages are notably smaller because they exclude GUI library dependencies like Qt and X11, making them preferable for containerized applications or cloud environments. Users working with GPU acceleration or needing custom module compilation should build manually from source instead, as these precompiled packages are CPU-only. The README emphasizes selecting exactly one package variant for any given environment, as all packages share the same namespace and installing multiple variants causes conflicts.

The project maintains active CI infrastructure to produce and distribute packages across supported Python versions and platforms. Development activity shows consistent attention to dependency management and build tooling, with documentation covering installation prerequisites, package selection guidance, and troubleshooting for common setup issues. The project includes sections on manual builds, debug builds, source distributions, and development builds, indicating ongoing support for users with specialized compilation needs.