opencv-python 3.4.0.12

Wrapper package for OpenCV python bindings.

Unofficial OpenCV packages for Python.

This package contains only the OpenCV core modules without the optional contrib modules. If you are looking for a version which includes OpenCV contrib modules, please install opencv-contrib-python instead.

The packages contain pre-compiled OpenCV binary with Python bindings. This enables super fast (usually < 10 seconds) OpenCV installation for Python.

If you need only OpenCV Python bindings, no separate OpenCV installation is required.

Installation and Usage

1. If you have previous/other version of OpenCV installed (e.g. cv2 module in the root of Python’s site-packages), remove it before installation to avoid conflicts.

• To further avoid conflicts and to make development easier, Python’s virtual environments are highly recommended for development purposes.

1. If you have an existing opencv-contrib-python installation, run pip uninstall opencv-contrib-python
2. Install this package:

pip install opencv-python

1. Import the package:

import cv2

The package contains haarcascade files. cv2.data.haarcascades can be used as a shortcut to the data folder. For example:

cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

1. Read OpenCV documentation
2. Before opening a new issue, read the FAQ below and have a look at the other issues which are already open.

Frequently Asked Questions

Q: Do I need to install also OpenCV separately?

A: No, the packages are special wheel binary packages and they already contain statically built OpenCV binaries.

Q: Pip does not find package ``opencv-python``?

A: The wheel package format and manylinux builds are pretty new things. Most likely the issue is related to too old pip and can be fixed by running pip install --upgrade pip and pip install wheel.

Q: I need contrib modules?

A: Please install opencv-contrib-python instead. However, note that commercial usage might be restricted in some countries since the contrib modules might contain some non-free/patented algorithms.

Q: Import fails on Windows to some DLL load error?

A: If the import fails on Windows, make sure you have Visual C++ redistributable 2015 installed. If you are using older Windows version than Windows 10 and latest system updates are not installed, Universal C Runtime might be also required.

See also this issue if you are using Anaconda.

Q: I have some other import errors?

A: Make sure you have removed old manual installations of OpenCV Python bindings (cv2.so or cv2.pyd in site-packages).

Documentation for opencv-python

The aim of this repository is to provide means to package each new OpenCV release for the most used Python versions and platforms.

At the same time it allows anyone to build a custom version of OpenCV for any Python version: just fork this repo and modify the build files and scripts to fit your needs.

Build process

The project is structured like a normal Python package with a standard setup.py file. The build process for a single entry in the build matrices is as follows (see for example appveyor.yml file):

1. Checkout repository and submodules
   • OpenCV is included as submodule and the version is updated manually by maintainers when a new OpenCV release has been made
   • Contrib modules are also included as a submodule
2. Find OpenCV version from the sources
3. Install dependencies (numpy)
4. Build OpenCV
   • tests are disabled, otherwise build time increases too much
   • there are 2 build matrix entries for each build combination: with and without contrib modules
   • Linux builds run in manylinux Docker containers (CentOS 5)
5. Copy each .pyd/.so file to cv2 folder of this project and generate wheel
   • Linux and macOS wheels are checked with auditwheel and delocate
6. Install the generated wheel
7. Test that Python can import the library and run some sanity checks
8. Use twine to upload the generated wheel to PyPI (only in release builds)

Currently the find_version.py file parses OpenCV version information from the OpenCV sources. OpenCV depends on numpy, so setup.py checks the minimum required numpy version also with the help of pip.

The cv2.pyd/.so file is normally copied to site-packages. To avoid polluting the root folder this package wraps the statically built binary into cv2 package and __init__.py file in the package handles the import logic correctly.

Since both opencv-python and opencv-contrib-python use the same namespace explained above, it is highly recommended to uninstall the other package before switching from example from opencv-python to opencv-contrib-python package.

Licensing

Opencv-python package (scripts in this repository) is available under MIT license.

OpenCV itself is available under 3-clause BSD License (LICENSE-3RD-PARTY.txt).

All wheels ship with FFmpeg licensed under the LGPLv2.1.

Linux and MacOS wheels ship with Qt 4.8.7 licensed under the LGPLv2.1.

Versioning

Currently the find_version.py script searches for the version information from OpenCV sources and appends also a revision number specific to this repository to the version string.

Releases

A release is made and uploaded to PyPI when a new tag is pushed to master branch. These tags differentiate packages (this repo might have modifications but OpenCV version stays same) and should be incremented sequentially. In practice, release version numbers look like this:

cv_major.cv_minor.cv_revision.package_revision e.g. 3.1.0.0

Development builds

Every commit to the master branch of this repo will be built. Possible build artifacts use local version identifiers:

cv_major.cv_minor.cv_revision+git_hash_of_this_repo e.g. 3.1.0+14a8d39

These artifacts can’t be and will not be uploaded to PyPI.

Manylinux wheels

Linux wheels are built using manylinux. These wheels should work out of the box for most of the distros (which use GNU C standard library) out there since they are built against an old version of glibc.

Supported Python versions

Python 2.7 is the only supported version in 2.x series. Python 3.x releases follow Numpy releases, for example Python 3.3 is no longer supported by Numpy so the support for it has been dropped in opencv-python too.

Currently, builds for following Python versions are provided:

• 2.7
• 3.4
• 3.5
• 3.6