Experimental Rust bindings for OpenCV 3 and 4.
The API is usable, but unstable and not very battle-tested; use at your own risk.
Make sure the supported OpenCV version (3.4 or 4.x) and Clang (part of LLVM, needed for automatic binding generation) are installed in your system.
Update your Cargo.toml
opencv = "0.76.4"
Import prelude
use opencv::prelude::*;
OpenCV package in Arch is suitable for this:
pacman -S clang qt5-base opencv
and additionally to support more OpenCV modules:
pacman -S vtk glew fmt openmpi
apt install libopencv-dev clang libclang-dev
You have several options of getting the OpenCV library:
-
install it from the repository, make sure to install
-dev
packages because they contain headers necessary for the crate build (also check that your package containspkg_config
orcmake
files). -
build OpenCV manually and set up the following environment variables prior to building the project with
opencv
crate:PKG_CONFIG_PATH
for the location of*.pc
files orOpenCV_DIR
for the location of*.cmake
filesLD_LIBRARY_PATH
for where to look for the installed*.so
files during runtime
Additionally, please make sure to install clang
package or its derivative that contains libclang.so
and
clang
binary.
- Gentoo, Fedora:
clang
- Debian, Ubuntu:
clang
andlibclang-dev
Installing OpenCV is easy through the following sources:
-
from chocolatey, also install
llvm
package, it's required for building:choco install llvm opencv
also set
OPENCV_LINK_LIBS
,OPENCV_LINK_PATHS
andOPENCV_INCLUDE_PATHS
environment variables (see below for details). -
from vcpkg, also install
llvm
package, necessary for building:vcpkg install llvm opencv4[contrib,nonfree]
You most probably want to set environment variable
VCPKGRS_DYNAMIC
to "1" unless you're specifically targeting a static build.
Get OpenCV from homebrew:
- homebrew:
You will also need a working C++ compiler and libclang, you can install Command Line Tools (
brew install opencv
xcode-select --install
), XCode (from AppStore) orllvm
(from Brew). You most probably need to also check the item 6 of the troubleshooting below.
You can of course always compile OpenCV of the version you prefer manually. This is also supported, but it requires some additional configuration.
You need to set up the following environment variables to point to the installed files of your OpenCV build:
OPENCV_LINK_LIBS
, OPENCV_LINK_PATHS
and OPENCV_INCLUDE_PATHS
(see below for details).
Static linking to OpenCV is supported and tested at least on Linux. For some hints on building OpenCV statically
please check this comment. Also,
you can get some information on how to perform the build in CI scripts:
install-focal.sh and
script.sh, search for non_static_version
variable.
-
One of the common problems is link errors in the end of the build.
Be sure to set up the relevant environment variables that will allow the linker to find the libraries it needs (see below).
-
You're getting runtime errors like:
thread 'main' panicked at 'called `Result::unwrap()` on an `Err` value: Error { code: -215, message: "OpenCV(4.2.0) /build/opencv/src/opencv-4.2.0/modules/highgui/src/window.cpp:384: error: (-215:Assertion failed) size.width>0 && size.height>0 in function \'imshow\'\n" }', src/libcore/result.rs:1188:5
thread 'extraction::tests::test_contour_matching' panicked at 'called `Result::unwrap()` on an `Err` value: Error { code: -215, message: "OpenCV(4.1.1) /tmp/opencv-20190908-41416-17rm3ol/opencv-4.1.1/modules/core/src/matrix_wrap.cpp:79: error: (-215:Assertion failed) 0 <= i && i < (int)vv.size() in function \'getMat_\'\n" }', src/libcore/result.rs:1165:5
These errors (note the .cpp source file and
Error
return value) are coming from OpenCV itself, not from the crate. It means that you're using the OpenCV API incorrectly, e.g. passing incompatible or unexpected arguments. Please refer to the OpenCV documentation for details. -
You're getting errors that methods don't exist or not implemented for specific
struct
s, but you can see them in the documentation and in the crate source.Be sure to import
use opencv::prelude::*;
. The crate contains a lot of traits that need to be imported first. -
On Windows, you're getting the
(exit code: 0xc0000135, STATUS_DLL_NOT_FOUND)
error when running the compiled binary.That often means that Windows can't find the OpenCV library dll. Be sure to set up
PATH
environment variable correctly or copy the dll next to the binary you're trying to run. Check that guide too. -
On Windows with VCPKG you're getting a lot of linking errors in multiple files like in this issue.
Unless you're doing a very specific build, you want to have environment variable
VCPKGRS_DYNAMIC
set to "1". -
On Windows with OpenCV 4.6.0 you're getting linking errors related to
img_hash
module like in this issue.Be sure to add
opencv_img_hash460
to yourOPENCV_LINK_LIBS
environment variable because it's being built as a separate file. -
On macOS you're getting the
dyld: Library not loaded: @rpath/libclang.dylib
error during the build process.OS can't find
libclang.dylib
dynamic library because it resides in a non-standard path, set up theDYLD_FALLBACK_LIBRARY_PATH
environment variable to point to the path where libclang.dylib can be found, e.g. for Command Line Tools:export DYLD_FALLBACK_LIBRARY_PATH="$(xcode-select --print-path)/usr/lib/"
or XCode:
export DYLD_FALLBACK_LIBRARY_PATH="$(xcode-select --print-path)/Toolchains/XcodeDefault.xctoolchain/usr/lib/"
You might be running into the issue on the recent macOS versions where this environment variable remains empty after setting, please check this issue for some workarounds.
-
You're getting the panic:
a `libclang` shared library is not loaded on this thread
.Enable the
clang-runtime
feature or use crate version0.66
and newer. The reason for the issue is that some crates (likebindgen
) depend onclang-sys
with hard-enabledruntime
feature and because of that cargo makes this feature also enabled for every other crate that depends onclang-sys
(opencv
in this case). During binding generation phaseopencv
crate tries to use multiple threads andclang-sys
withruntime
feature enabled doesn't like that (hence the panic). Enablingclang-runtime
feature switches to using multiple processes instead of multiple threads. This makes the build a bit longer because of the need to build the helper binary, but the end result is the same. Additionally since crate version0.66
this behavior is now the default. -
You're getting
'limits' file not found
error during crate build.This error is caused by the missing/invalid installation of C++ standard library (e.g. libstdc++ for GCC). To fix this make sure that the toolchain you're using has the corresponding C++ standard library. The toolchain is used through
libclang
, so to get useful diagnostic info run:clang -E -x c++ - -v
Look for
Selected GCC installation
and#include <...> search starts here
to get the sense of what system toolchain is used by clang. Refer to this issue for more fixes and workarounds.
If you still have trouble using the crate after going through the Troubleshooting steps please fill free to report it to the bugtracker.
When reporting an issue please state:
- Operating system
- The way you installed OpenCV: package, official binary distribution, manual compilation, etc.
- OpenCV version
- Attach the full output of the following command from your project directory:
RUST_BACKTRACE=full cargo build -vv
The following variables must be set when building without pkg_config
, cmake
or vcpkg
. You can set them
on any platform, the specified values will override those automatically discovered.
-
OPENCV_LINK_LIBS
Comma separated list of library names to link to..lib
,.so
or.dylib
extension is optional. If you specify the ".framework" extension then build script will link a macOS framework instead of plain shared library. E.g. "opencv_world411".If this list starts with '+' (plus sign) then the specified items will be appended to whatever the system probe returned. E.g. a value of "+dc1394" will do a system discovery of the OpenCV library and its linked libraries and then will additionally link
dc1394
library at the end. Can be useful if the system probe produces a mostly working setup, but has incomplete link list, or the order is wrong (especially important during static linking). -
OPENCV_LINK_PATHS
Comma separated list of paths to search for libraries to link. E.g. "C:\tools\opencv\build\x64\vc15\lib". The path list can start with '+', seeOPENCV_LINK_LIBS
for a detailed explanation (e.g. "+/usr/local/lib"). -
OPENCV_INCLUDE_PATHS
Comma separated list of paths to search for system include files during compilation. E.g. "C:\tools\opencv\build\include". One of the directories specified therein must contain "opencv2/core/version.hpp" or "core/version.hpp" file, it's used to detect the version of the headers. The path list can start with '+', seeOPENCV_LINK_LIBS
for a detailed explanation (e.g. "+/opt/cuda/targets/x86_64-linux/include/").
The following variables are rarely used, but you might need them under some circumstances:
-
OPENCV_PACKAGE_NAME
In some cases you might want to override the pkg-config, cmake or vcpkg package name, you can use this environment variable for that. If you set it pkg-config will expect to find the file with that name and.pc
extension in the package directory. Cmake will look for that file with.cmake
extension. And vcpkg will use that name to try to find package inpackages
directory underVCPKG_ROOT
. You can also use separate environment variables to set different package names for different package systems:OPENCV_PKGCONFIG_NAME
OPENCV_CMAKE_NAME
OPENCV_VCPKG_NAME
-
OPENCV_CMAKE_BIN
Path to cmake binary (used in OpenCV discovery process using cmake). If not set then just "cmake" will be used. For example, you can set something like "/usr/local/bin/cmake" here. -
OPENCV_DISABLE_PROBES
Comma separated list of OpenCV package auto-discovery systems to exclude from running. Might be useful if one of the higher priority systems is producing incorrect results. Can contain the following values:- environment - reads data only from the
OPENCV_LINK_LIBS
,OPENCV_LINK_PATHS
andOPENCV_INCLUDE_PATHS
environment variables - pkg_config
- cmake
- vcpkg_cmake - like vcpkg, but only uses vcpkg for path discovery, the actual OpenCV probe is done using cmake (cmake related environment variables are applicable with this probe)
- vcpkg
- environment - reads data only from the
-
OPENCV_MODULE_WHITELIST
andOPENCV_MODULE_BLACKLIST
Not used anymore. These used to be used to select modules that get their binding generated. We have switched to using cargo features for module selection. Please see the section on features to learn how to switch.
The following variables affect the building the of the opencv
crate, but belong to external components:
-
PKG_CONFIG_PATH
Where to look for*.pc
files see the man pkg-config Path specified here must containopencv.pc
(pre OpenCV 4) oropencv4.pc
(OpenCV 4 and later). -
VCPKG_ROOT
andVCPKGRS_DYNAMIC
The root ofvcpkg
installation and flag allowing use of*.dll
libraries, see the documentation forvcpkg
crate -
OpenCV_DIR
The directory that contains OpenCV package cmake files. Usually there areOpenCVConfig.cmake
,OpenCVConfig-version.cmake
andOpenCVModules.cmake
in it. -
LD_LIBRARY_PATH
On Linux it sets the list of directories to look for the installed*.so
files during runtime. Linux documentation has more info. Path specified here must containlibopencv_*.so
files. -
DYLD_LIBRARY_PATH
andDYLD_FALLBACK_LIBRARY_PATH
Similar toLD_LIBRARY_PATH
, but for loading*.dylib
files on macOS, see man dyld and this SO answer for more info. Path specified here must contain*.dylib
files. -
PATH
Windows searches for*.dll
s inPATH
among other places, be sure to set it up, or copy required OpenCV*.dll
s next to your binary. Be sure to specify paths in UNIX style (/C/Program Files/Dir) because colon inPATH
might be interpreted as the entry separator. Summary here. -
clang crate environment variables See crate's README
- There is a feature named after each OpenCV module (e.g.
imgproc
,highgui
, etc.). They are all enabled by default, but if a corresponding module is not found then it will silently be ignored. If you need to select a specific set of modules be sure to disable the default features and provide the required feature set:opencv = { version = ..., default-features = false, features = ["calib3d", "features2d", "flann"]}
rgb
- allow usingrgb
crate types asMat
elements
API Documentation is automatically translated from OpenCV's doxygen docs. Most likely you'll still want to refer to the official OpenCV C++ documentation as well.
The following OpenCV versions are supported at the moment:
- 3.4
- 4.x
Currently, version 1.59.0 or later is required.
Currently, the main development and testing of the crate is performed on Linux, but other major platforms are also supported: macOS and Windows.
For some more details please refer to the CI build scripts: Linux OpenCV install, macOS OpenCV install as framework, macOS OpenCV install via brew, Windows OpenCV install via Chocolatey, Windows OpenCV install via vcpkg, Test runner script.
Generally the crate tries to only wrap OpenCV API and provide some convenience functions to be able to use it in Rust easier. We try to avoid adding any functionality besides that.
Most functions return a Result
to expose a potential C++ exception. Although some methods like property reads
or functions that are marked CV_NOEXCEPT in the OpenCV headers are infallible and return a naked value.
CV_MAKETYPE
and related CV_MAT_DEPTH
constant functions are available to replace the corresponding OpenCV macros.
Yet it's usually easier to call ::opencv_type()
function on the corresponding Rust type. E.g.:
let t = u16::opencv_type(); // equivalent to CV_MAKETYPE(CV_16U, 1)
let t = Vec2f::opencv_type(); // equivalent to CV_MAKETYPE(CV_32F, 2)
Some C++ operators are supported, they are converted to the corresponding functions on Rust side. Here is the list with the corresponding function name:
[]
→get()
orget_mut()
+
,-
→add()
,sub()
*
,/
→mul()
,div()
()
(function call) →apply()
*
(deref) →try_deref()
ortry_deref_mut()
==
,!=
→equals()
,not_equals()
>
,>=
→greater_than()
,greater_than_or_equal()
<
,<=
→less_than()
,less_than_or_equal()
++
,--
→incr()
,decr()
&
,|
,^
→and()
,or()
,xor()
!
→negate()
Fields of OpenCV classes are accessible through setters and getters. Those functions are infallible, they
return the value directly instead of Result
.
For infallible functions (like setters) that accept &str
values the following logic applies: if a Rust
string passed as argument contains null byte then this string will be truncated up to that null byte. So if
for example you pass "123\0456" to the setter, the property will be set to "123".
Some API functions accept callbacks, e.g. set_mouse_callback
. While currently it's possible to successfully
use those functions there are some limitations to keep in mind. Current implementation of callback handling
leaks the passed callback argument. That means that the closure used as a callback will never be freed during
the lifetime of a program and moreover Drop will not be called for it. There is a plan to implement possibility
to be able to free at least some closures.
Although the crate tries to provide an ergonomic Rust interface for OpenCV, don't expect
Rust safety guarantees at this stage. It's especially true for the borrow-checking and the
shared mutable ownership. Notable example would be Mat
which is a reference counted
object in its essence. You can own a seemingly separate Mat
in Rust terms, but
it's going to be a mutable reference to the other Mat
under the hood. Treat safety
of the crate's API as you would treat one of C++, use clone()
when needed.
To be able to use some modules you need to have opencv_contrib
installed. You can find the full list of contrib modules here.
While most of the API is covered, for various reasons (that might no longer hold) there are modules and functions that are not yet implemented. If a missing module/function is near and dear to you, please file an issue (or better, open a pull request!).
This crate works similar to the model of python and java's OpenCV wrappers - it uses libclang to parse the OpenCV C++ headers, generates a C interface to the C++ API, and wraps the C interface in Rust.
All the major modules in the C++ API are merged together in a huge cv::
namespace. We instead made one rust
module for each major OpenCV module. So, for example, C++ cv::Mat
is opencv::core::Mat
in this crate.
The methods and field names have been snake_cased. Methods arguments with default value lose these default values, but they are reported in the API documentation.
Overloaded methods have been mostly manually given different names or automatically renamed to *_1, *_2, etc.
If you can't use OpenCV 3.x or higher, the (no longer maintained) 0.2.4
version of this crate is known to
work with OpenCV 2.4.7.13
(and probably other 2.4 versions). Please refer to the README.md file for that
version because the crate has gone through the considerable rewrite since.
The last version with confirmed OpenCV 3.2 support is 0.75.0, after that this branch of OpenCV is no longer tested and supported. It may still work though.
The binding generator code lives in a separate crate under binding-generator. During the build phase it creates bindings from the header files and puts them into bindings directory. Those are then transferred to src for the consumption by the crate users.
The crate itself, as imported by users, consists of generated rust code in src committed to the repo.
This way, users don't have to handle the code generation overhead in their builds. When developing this crate,
you can test changes to the binding generation using cargo build -vv
. When changing the binding-generator
,
be sure to push changes to the generated code!
If you're looking for things to improve be sure to search for todo
and fixme
labels in the project
source, those usually carry the comment of what exactly needs to be fixed.
The license for the original work is MIT.
Special thanks to ttacon for yielding the crate name.