The minimal opencv for Android, iOS and ARM Linux
✔️ This project provides the minimal build of opencv library for the Android, iOS and ARM Linux platforms.
✔️ We provide prebuild binary packages for opencv 2.4.13.7, 3.4.13 and 4.5.1.
✔️ We also provide prebuild binary package for iOS with bitcode enabled, that the official package lacks.
✔️ All the binaries are compiled from source on github action, no virus, no backdoor, no secret code.
|opencv 4.5.1 android|package size| |---|---| |The official opencv|229MB| |opencv-mobile|15.5MB|
|opencv 4.5.1 ios|package size| |---|---| |The official opencv|173MB| |opencv-mobile|14.8MB|
|opencv 4.5.1 ios with bitcode|package size| |---|---| |The official opencv|missing :(| |opencv-mobile|51.6MB|
(armeabi-v7a arm64-v8a x86 x86_64) build with ndk r21d and android api 24
(armv7 arm64 arm64e i386 x86_64) build with Xcode 12.2
(armv7 arm64 arm64e i386 x86_64) build with Xcode 12.2
(arm-linux-gnueabi arm-linux-gnueabihf aarch64-linux-gnu) build with ubuntu cross compiler
/app/src/main/jni/
/app/src/main/jni/CMakeListst.txtto find and link opencv
set(OpenCV_DIR ${CMAKE_SOURCE_DIR}/opencv-mobile-4.5.1-android/sdk/native/jni) find_package(OpenCV REQUIRED)target_link_libraries(your_jni_target ${OpenCV_LIBS})
opencv2.frameworkinto your project
/
/CMakeListst.txtto find and link opencv
set(OpenCV_DIR ${CMAKE_SOURCE_DIR}/opencv-mobile-4.5.1-armlinux/arm-linux-gnueabihf/lib/cmake/opencv4) find_package(OpenCV REQUIRED)target_link_libraries(your_target ${OpenCV_LIBS})
wget -q https://github.com/opencv/opencv/archive/4.5.1.zip -O opencv-4.5.1.zip unzip -q opencv-4.5.1.zip cd opencv-4.5.1
truncate -s 0 cmake/OpenCVFindLibsGrfmt.cmake rm -rf modules/gapi rm -rf modules/highgui cp -r ../highgui modules/
patch -p1 -i ../opencv-4.5.1-no-rtti.patch
mkdir -p build cd build cmake -DCMAKE_INSTALL_PREFIX=install \ -DCMAKE_BUILD_TYPE=Release \ `cat ../../opencv4_cmake_options.txt` \ -DBUILD_opencv_world=OFF ..
zip -r -9 opencv-mobile-4.5.1.zip install
The minimal opencv build contains most basic opencv operators and common image processing functions, with some handy additions like keypoint feature extraction and matching, image inpainting and opticalflow estimation.
Many computer vision algorithms that reside in dedicated modules are discarded, such as face detection etc. You could try deep-learning based algorithms with nerual network inference library optimized for mobile.
Image IO functions in highgui module, like
cv::imreadand
cv::imwrite, are re-implemented using stb for smaller code size. GUI functions, like
cv::imshow, are discarded.
cuda and opencl are disabled because there is no cuda on mobile, no opencl on ios, and opencl on android is slow. opencv on gpu is not suitable for real productions. Write metal on ios and opengles/vulkan on android if you need good gpu acceleration.
C++ RTTI and exceptions are disabled for minimal build. Be careful when you write
cv::Mat roi = image(roirect);:P
|module|comment| |---|---| |opencvcore|Mat, matrix operations, etc| |opencvimgproc|resize, cvtColor, warpAffine, etc| |opencvhighgui|imread, imwrite| |opencvfeatures2d|keypoint feature and matcher, etc (not included in opencv 2.x package)| |opencvphoto|inpaint, etc| |opencvvideo|opticalflow, etc|
|module|comment| |---|---| |opencvandroidcamera|use android Camera api instead| |opencvcalib3d|camera calibration, rare uses on mobile| |opencvcontrib|experimental functions, build part of the source externally if you need| |opencvdnn|very slow on mobile, try ncnn for nerual network inference on mobile| |opencvdynamicuda|no cuda on mobile| |opencvflann|feature matching, rare uses on mobile, build the source externally if you need| |opencvgapi|graph based image processing, little gain on mobile| |opencvgpu|no cuda/opencl on mobile| |opencvimgcodecs|link with opencvhighgui instead| |opencvjava|wrap your c++ code with jni| |opencvjs|write native code on mobile| |opencvlagacy|various good-old cv routines, build part of the source externally if you need| |opencvml|train your ML algorithm on powerful pc or server| |opencvnonfree|the SIFT and SURF, use ORB which is faster and better| |opencvobjdetect|HOG, cascade detector, use deep learning detector which is faster and better| |opencvocl|no opencl on mobile| |opencvpython|no python on mobile| |opencvshape|shape matching, rare uses on mobile, build the source externally if you need| |opencvstitching|image stitching, rare uses on mobile, build the source externally if you need| |opencvsuperres|do video super-resolution on powerful pc or server| |opencvts|test modules, useless in production anyway| |opencvvideoio|use android MediaCodec or ios AVFoundation api instead| |opencvvideostab|do video stablization on powerful pc or server| |opencv_viz|vtk is not available on mobile, write your own data visualization routines|