Platform Support Overview

OpenCV is designed to be cross-platform and runs on a wide variety of operating systems and architectures. This page provides an overview of supported platforms and their requirements.

Supported Platforms

OpenCV supports the following major platforms:

Linux

Native support for x86, x86_64, ARM, and other architectures

Windows

Full support via Visual Studio and MinGW toolchains

macOS

Universal binaries for Intel and Apple Silicon

Android

AAR packages and NDK integration

iOS

XCFramework with Objective-C and Swift support

Architecture Support Matrix

OpenCV supports a wide range of processor architectures across different platforms:

Platform	Architectures	Build System
Linux	x86, x86_64, ARM (v7, v8), RISC-V, PowerPC, MIPS	CMake + Make/Ninja
Windows	x86, x86_64, ARM64	CMake + Visual Studio/Ninja
macOS	x86_64, arm64 (Apple Silicon)	CMake + Xcode
Android	armeabi-v7a, arm64-v8a, x86, x86_64	CMake + Gradle/NDK
iOS	armv7, arm64, i386, x86_64 (simulator)	CMake + Xcode

Minimum Requirements

Build Tools

Linux
Windows
macOS
Android
iOS

GCC 5.x+ or Clang 3.4+
CMake 3.5.1+
Make or Ninja
Git (optional)

Runtime Requirements

Minimum OS versions for running OpenCV applications:

Linux: Kernel 2.6.32+ (older kernels may work with reduced functionality)
Windows: Windows 7 SP1 or later
macOS: macOS 10.12 (Sierra) or later
Android: API Level 21 (Android 5.0 Lollipop) or later
iOS: iOS 9.0 or later

Cross-Compilation Support

OpenCV provides toolchain files for cross-compilation:

# ARM Linux cross-compilation example
cmake -DCMAKE_TOOLCHAIN_FILE=platforms/linux/arm-gnueabi.toolchain.cmake \
      -DCMAKE_BUILD_TYPE=Release \
      ..

Available Toolchains

The platforms/ directory contains toolchain files for:

ARM: arm-gnueabi.toolchain.cmake, aarch64-gnu.toolchain.cmake
RISC-V: riscv64-gcc.toolchain.cmake, riscv64-clang.toolchain.cmake
MIPS: mips32r5el-gnu.toolchain.cmake, mips64r6el-gnu.toolchain.cmake
PowerPC: ppc64-gnu.toolchain.cmake, ppc64le-gnu.toolchain.cmake

Hardware Acceleration

OpenCV leverages platform-specific acceleration technologies:

Platform	Acceleration Technologies
All Platforms	SSE2/3/4, AVX, AVX2, AVX-512, NEON
Linux	OpenCL, CUDA, TBB, OpenMP, VA-API
Windows	OpenCL, CUDA, TBB, OpenMP, DirectX
macOS	OpenCL, TBB, Accelerate Framework
Android	OpenCL, Vulkan, NNAPI, FastCV (Qualcomm)
iOS	Accelerate Framework, Metal, Core ML

GPU acceleration (CUDA, OpenCL) requires compatible hardware and additional setup. Not all modules support all acceleration technologies.

Binary Distributions

Pre-built binaries are available for common configurations:

Windows: Installer packages for Visual Studio 2015-2022 (x86, x64)
Android: AAR packages via Maven Central
iOS: Pre-built frameworks available in releases
Python: pip install opencv-python for major platforms

Building from source gives you more control over enabled features and optimizations for your specific hardware.

Platform-Specific Considerations

Mobile Platforms

For iOS and Android:

Framework/AAR sizes can be large (~50-100MB). Consider using modular builds to reduce size.
Some modules are not available on mobile (e.g., highgui video capture)
Use --without flag when building to exclude unnecessary modules

Embedded Systems

For resource-constrained embedded Linux systems:

# Minimal build for embedded systems
cmake -DBUILD_SHARED_LIBS=OFF \
      -DBUILD_TESTS=OFF \
      -DBUILD_PERF_TESTS=OFF \
      -DBUILD_EXAMPLES=OFF \
      -DWITH_GTK=OFF \
      -DWITH_QT=OFF \
      ..

Getting Started

Core Concepts

Modules

Tutorials

Language Bindings