|  | |
| # ncnn | |
| [![License][badge-license]](LICENSE.txt) | |
| [![Download Total Count][badge-download-count]](https://github.com/Tencent/ncnn/releases) | |
| [![codecov][badge-codecov]](https://codecov.io/gh/Tencent/ncnn) | |
| [![Language grade: C/C++][badge-code-quality]](https://lgtm.com/projects/g/Tencent/ncnn/context:cpp) | |
| [badge-license]: https://img.shields.io/badge/license-BSD--3--Clause-blue.svg | |
| [badge-download-count]: https://img.shields.io/github/downloads/Tencent/ncnn/total.svg | |
| [badge-codecov]: https://codecov.io/gh/Tencent/ncnn/branch/master/graph/badge.svg | |
| [badge-code-quality]: https://img.shields.io/lgtm/grade/cpp/g/Tencent/ncnn.svg?logo=lgtm&logoWidth=18 | |
| ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. | |
| ncnn is deeply considerate about deployment and uses on mobile phones from the beginning of design. | |
| ncnn does not have third party dependencies. It is cross-platform, and runs faster than all known open source frameworks on mobile phone cpu. | |
| Developers can easily deploy deep learning algorithm models to the mobile platform by using efficient ncnn implementation, | |
| create intelligent APPs, and bring the artificial intelligence to your fingertips. | |
| ncnn is currently being used in many Tencent applications, such as QQ, Qzone, WeChat, Pitu and so on. | |
| ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架。 | |
| ncnn 从设计之初深刻考虑手机端的部署和使用。 | |
| 无第三方依赖，跨平台，手机端 cpu 的速度快于目前所有已知的开源框架。 | |
| 基于 ncnn，开发者能够将深度学习算法轻松移植到手机端高效执行， | |
| 开发出人工智能 APP，将 AI 带到你的指尖。 | |
| ncnn 目前已在腾讯多款应用中使用，如：QQ，Qzone，微信，天天 P 图等。 | |
| --- | |
| ## 技术交流 QQ 群：637093648 (超多大佬) 答案：卷卷卷卷卷 （已满） | |
| ## Pocky QQ 群（MLIR YES!）: 677104663(超多大佬) 答案：multi-level intermediate representation | |
| ## Telegram Group <https://t.me/ncnnyes> | |
| ## Discord Channel <https://discord.gg/YRsxgmF> | |
| --- | |
| ## Current building status matrix | |
| | System | CPU (32bit) | CPU (64bit) | GPU (32bit) | GPU (64bit) | | |
| | :---------------- | :------------------------------------------------------------------ | :------------------------------------------------------------------------------ | :-------------------------------------------------------------- | :------------------------------------------------------------------ | | |
| | Linux (GCC) | [![Build Status][pass-linux-x86-cpu-gcc]][ci-linux-x86-cpu-gcc] | [![Build Status][pass-linux-x64-cpu-gcc]][ci-linux-x64-cpu-gcc] | — | [![Build Status][pass-linux-x64-gpu-gcc]][ci-linux-x64-gpu-gcc] | | |
| | Linux (Clang) | [![Build Status][pass-linux-x86-cpu-clang]][ci-linux-x86-cpu-clang] | [![Build Status][pass-linux-x64-cpu-clang]][ci-linux-x64-cpu-clang] | — | [![Build Status][pass-linux-x64-gpu-clang]][ci-linux-x64-gpu-clang] | | |
| | Linux (ARM) | [![Build Status][pass-linux-arm-cpu-gcc]][ci-linux-arm-cpu-gcc] | [![Build Status][pass-linux-aarch64-cpu-gcc]][ci-linux-aarch64-cpu-gcc] | — | — | | |
| | Linux (MIPS) | [![Build Status][pass-linux-mips-cpu-gcc]][ci-linux-mips-cpu-gcc] | [![Build Status][pass-linux-mips64-cpu-gcc]][ci-linux-mips64-cpu-gcc] | — | — | | |
| | Linux (RISC-V) | — | [![Build Status][pass-linux-riscv64-cpu-gcc]][ci-linux-riscv64-cpu-gcc] | — | — | | |
| | Linux (LoongArch) | — | [![Build Status][pass-linux-loongarch64-cpu-gcc]][ci-linux-loongarch64-cpu-gcc] | — | — | | |
| | Windows | [![Build Status][pass-windows-x86-cpu]][ci-windows-x86-cpu] | [![Build Status][pass-windows-x64-cpu]][ci-windows-x64-cpu] | — | [![Build Status][pass-windows-x64-gpu]][ci-windows-x64-gpu] | | |
| | Windows (ARM) | [![Build Status][pass-windows-arm-cpu]][ci-windows-arm-cpu] | [![Build Status][pass-windows-arm64-cpu]][ci-windows-arm64-cpu] | — | — | | |
| | macOS | — | [![Build Status][pass-macos-x64-cpu]][ci-macos-x64-cpu] | — | [![Build Status][pass-macos-x64-gpu]][ci-macos-x64-gpu] | | |
| | macOS (ARM) | — | [![Build Status][pass-macos-arm64-cpu]][ci-macos-arm64-cpu] | — | [![Build Status][pass-macos-arm64-gpu]][ci-macos-arm64-gpu] | | |
| | Android | [![Build Status][pass-android-armv7-cpu]][ci-android-armv7-cpu] | [![Build Status][pass-android-armv8-cpu]][ci-android-armv8-cpu] | [![Build Status][pass-android-armv7-gpu]][ci-android-armv7-gpu] | [![Build Status][pass-android-armv8-gpu]][ci-android-armv8-gpu] | | |
| | Android-x86 | [![Build Status][pass-android-x86-cpu]][ci-android-x86-cpu] | [![Build Status][pass-android-x64-cpu]][ci-android-x64-cpu] | [![Build Status][pass-android-x86-gpu]][ci-android-x86-gpu] | [![Build Status][pass-android-x64-gpu]][ci-android-x64-gpu] | | |
| | iOS | [![Build Status][pass-ios-cpu]][ci-ios-cpu] | [![Build Status][pass-ios-cpu]][ci-ios-cpu] | — | [![Build Status][pass-ios-arm64-gpu]][ci-ios-arm64-gpu] | | |
| | iOS Simulator | [![Build Status][pass-ios-simulator]][ci-ios-simulator] | [![Build Status][pass-ios-simulator]][ci-ios-simulator] | — | [![Build Status][pass-ios-simulator-gpu]][ci-ios-simulator-gpu] | | |
| | WebAssembly | [![Build Status][pass-web-assembly]][ci-web-assembly] | — | — | — | | |
| | RISC-V GCC/Newlib | [![Build Status][pass-elf-riscv32-cpu-gcc]][ci-elf-riscv32-cpu-gcc] | [![Build Status][pass-elf-riscv64-cpu-gcc]][ci-elf-riscv64-cpu-gcc] | — | — | | |
| [pass-android-armv7-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-armv7-cpu.yml?branch=master | |
| [pass-android-armv7-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-armv7-gpu.yml?branch=master | |
| [pass-android-armv8-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-armv8-cpu.yml?branch=master | |
| [pass-android-armv8-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-armv8-gpu.yml?branch=master | |
| [pass-android-x64-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-x64-cpu.yml?branch=master | |
| [pass-android-x64-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-x64-gpu.yml?branch=master | |
| [pass-android-x86-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-x86-cpu.yml?branch=master | |
| [pass-android-x86-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/android-x86-gpu.yml?branch=master | |
| [pass-elf-riscv32-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/elf-riscv32-cpu-gcc.yml?branch=master | |
| [pass-elf-riscv64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/elf-riscv64-cpu-gcc.yml?branch=master | |
| [pass-ios-arm64-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-arm64-gpu.yml?branch=master | |
| [pass-ios-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-cpu.yml?branch=master | |
| [pass-ios-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-cpu.yml?branch=master | |
| [pass-ios-simulator]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-simulator.yml?branch=master | |
| [pass-ios-simulator]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-simulator.yml?branch=master | |
| [pass-ios-simulator-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/ios-simulator-gpu.yml?branch=master | |
| [pass-linux-aarch64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-aarch64-cpu-gcc.yml?branch=master | |
| [pass-linux-arm-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-arm-cpu-gcc.yml?branch=master | |
| [pass-linux-loongarch64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-loongarch64-cpu-gcc.yml?branch=master | |
| [pass-linux-mips-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-mips-cpu-gcc.yml?branch=master | |
| [pass-linux-mips64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-mips64-cpu-gcc.yml?branch=master | |
| [pass-linux-riscv64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-riscv64-cpu-gcc.yml?branch=master | |
| [pass-linux-x64-cpu-clang]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x64-cpu-clang.yml?branch=master | |
| [pass-linux-x64-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x64-cpu-gcc.yml?branch=master | |
| [pass-linux-x64-gpu-clang]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x64-gpu-clang.yml?branch=master | |
| [pass-linux-x64-gpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x64-gpu-gcc.yml?branch=master | |
| [pass-linux-x86-cpu-clang]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x86-cpu-clang.yml?branch=master | |
| [pass-linux-x86-cpu-gcc]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/linux-x86-cpu-gcc.yml?branch=master | |
| [pass-macos-arm64-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/macos-arm64-cpu.yml?branch=master | |
| [pass-macos-arm64-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/macos-arm64-gpu.yml?branch=master | |
| [pass-macos-x64-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/macos-x64-cpu.yml?branch=master | |
| [pass-macos-x64-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/macos-x64-gpu.yml?branch=master | |
| [pass-web-assembly]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/web-assembly.yml?branch=master | |
| [pass-windows-arm-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/windows-arm-cpu.yml?branch=master | |
| [pass-windows-arm64-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/windows-arm64-cpu.yml?branch=master | |
| [pass-windows-x64-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/windows-x64-cpu.yml?branch=master | |
| [pass-windows-x64-gpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/windows-x64-gpu.yml?branch=master | |
| [pass-windows-x86-cpu]: https://img.shields.io/github/actions/workflow/status/Tencent/ncnn/windows-x86-cpu.yml?branch=master | |
| [ci-android-armv7-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-armv7-cpu | |
| [ci-android-armv7-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-armv7-gpu | |
| [ci-android-armv8-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-armv8-cpu | |
| [ci-android-armv8-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-armv8-gpu | |
| [ci-android-x64-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-x64-cpu | |
| [ci-android-x64-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-x64-gpu | |
| [ci-android-x86-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-x86-cpu | |
| [ci-android-x86-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aandroid-x86-gpu | |
| [ci-elf-riscv32-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aelf-riscv32-cpu-gcc | |
| [ci-elf-riscv64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aelf-riscv64-cpu-gcc | |
| [ci-ios-arm64-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-arm64-gpu | |
| [ci-ios-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-cpu | |
| [ci-ios-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-cpu | |
| [ci-ios-simulator]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-simulator | |
| [ci-ios-simulator]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-simulator | |
| [ci-ios-simulator-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aios-simulator-gpu | |
| [ci-linux-aarch64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-aarch64-cpu-gcc | |
| [ci-linux-arm-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-arm-cpu-gcc | |
| [ci-linux-loongarch64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-loongarch64-cpu-gcc | |
| [ci-linux-mips-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-mips-cpu-gcc | |
| [ci-linux-mips64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-mips64-cpu-gcc | |
| [ci-linux-riscv64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-riscv64-cpu-gcc | |
| [ci-linux-x64-cpu-clang]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x64-cpu-clang | |
| [ci-linux-x64-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x64-cpu-gcc | |
| [ci-linux-x64-gpu-clang]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x64-gpu-clang | |
| [ci-linux-x64-gpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x64-gpu-gcc | |
| [ci-linux-x86-cpu-clang]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x86-cpu-clang | |
| [ci-linux-x86-cpu-gcc]: https://github.com/Tencent/ncnn/actions?query=workflow%3Alinux-x86-cpu-gcc | |
| [ci-macos-arm64-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Amacos-arm64-cpu | |
| [ci-macos-arm64-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Amacos-arm64-gpu | |
| [ci-macos-x64-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Amacos-x64-cpu | |
| [ci-macos-x64-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Amacos-x64-gpu | |
| [ci-web-assembly]: https://github.com/Tencent/ncnn/actions?query=workflow%3Aweb-assembly | |
| [ci-windows-arm-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Awindows-arm-cpu | |
| [ci-windows-arm64-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Awindows-arm64-cpu | |
| [ci-windows-x64-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Awindows-x64-cpu | |
| [ci-windows-x64-gpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Awindows-x64-gpu | |
| [ci-windows-x86-cpu]: https://github.com/Tencent/ncnn/actions?query=workflow%3Awindows-x86-cpu | |
| --- | |
| ## Support most commonly used CNN network | |
| ## 支持大部分常用的 CNN 网络 | |
| - Classical CNN: | |
| [VGG](https://github.com/BVLC/caffe/wiki/Model-Zoo#models-used-by-the-vgg-team-in-ilsvrc-2014) | |
| [AlexNet](https://github.com/BVLC/caffe/tree/9b891540183ddc834a02b2bd81b31afae71b2153/models/bvlc_alexnet) | |
| [GoogleNet](https://github.com/BVLC/caffe/tree/9b891540183ddc834a02b2bd81b31afae71b2153/models/bvlc_googlenet) | |
| Inception | |
| ... | |
| - Practical CNN: | |
| [ResNet](https://github.com/tornadomeet/ResNet) | |
| [DenseNet](https://github.com/liuzhuang13/DenseNet) | |
| [SENet](https://github.com/hujie-frank/SENet) | |
| [FPN](https://github.com/unsky/FPN) | |
| ... | |
| - Light-weight CNN: | |
| [SqueezeNet](https://github.com/forresti/SqueezeNet) | |
| [MobileNetV1](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md) | |
| [MobileNetV2/V3](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/README.md) | |
| [ShuffleNetV1](https://github.com/farmingyard/ShuffleNet) | |
| [ShuffleNetV2](https://github.com/opconty/keras-shufflenetV2) | |
| [MNasNet](https://github.com/tensorflow/models/tree/master/research/slim/nets/nasnet) | |
| ... | |
| - Face Detection: | |
| [MTCNN](https://github.com/ipazc/mtcnn) | |
| [RetinaFace](https://github.com/biubug6/Pytorch_Retinaface) | |
| [scrfd](https://github.com/nihui/ncnn-android-scrfd) | |
| ... | |
| - Detection: | |
| [VGG-SSD](https://github.com/lzx1413/CAFFE_SSD) | |
| [MobileNet-SSD](https://github.com/chuanqi305/MobileNet-SSD) | |
| [SqueezeNet-SSD](https://github.com/chuanqi305/SqueezeNet-SSD) | |
| [MobileNetV2-SSDLite](https://github.com/chuanqi305/MobileNetv2-SSDLite) | |
| [MobileNetV3-SSDLite](https://github.com/XiaoyuHuang96/MobilenetV3SSDLite-tfkeras) | |
| ... | |
| - Detection: | |
| [Faster-RCNN](https://github.com/rbgirshick/py-faster-rcnn) | |
| [R-FCN](https://github.com/daijifeng001/R-FCN) | |
| ... | |
| - Detection: | |
| [YOLOv2](https://github.com/longcw/yolo2-pytorch) | |
| [YOLOv3](https://github.com/ultralytics/yolov3) | |
| [MobileNet-YOLOv3](https://github.com/eric612/MobileNet-YOLO) | |
| [YOLOv4](https://github.com/Tianxiaomo/pytorch-YOLOv4) | |
| [YOLOv5](https://github.com/ultralytics/yolov5) | |
| [YOLOv7](https://github.com/WongKinYiu/yolov7) | |
| [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX) | |
| ... | |
| - Detection: | |
| [NanoDet](https://github.com/RangiLyu/nanodet) | |
| - Segmentation: | |
| [FCN](https://github.com/unsky/FPN) | |
| [PSPNet](https://github.com/hszhao/PSPNet) | |
| [UNet](https://github.com/zhixuhao/unet) | |
| [YOLACT](https://github.com/dbolya/yolact) | |
| ... | |
| - Pose Estimation: | |
| [SimplePose](https://github.com/dog-qiuqiu/Ultralight-SimplePose) | |
| ... | |
| --- | |
| ## HowTo | |
| **[how to build ncnn library](https://github.com/Tencent/ncnn/wiki/how-to-build) on Linux / Windows / macOS / Raspberry Pi3, Pi4 / POWER / Android / NVIDIA Jetson / iOS / WebAssembly / AllWinner D1 / Loongson 2K1000** | |
| - [Build for Linux / NVIDIA Jetson / Raspberry Pi3, Pi4 / POWER](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-linux) | |
| - [Build for Windows x64 using VS2017](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-windows-x64-using-visual-studio-community-2017) | |
| - [Build for macOS](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-macos) | |
| - [Build for ARM Cortex-A family with cross-compiling](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-arm-cortex-a-family-with-cross-compiling) | |
| - [Build for Hisilicon platform with cross-compiling](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-hisilicon-platform-with-cross-compiling) | |
| - [Build for Android](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-android) | |
| - [Build for iOS on macOS with xcode](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-ios-on-macos-with-xcode) | |
| - [Build for WebAssembly](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-webassembly) | |
| - [Build for AllWinner D1](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-allwinner-d1) | |
| - [Build for Loongson 2K1000](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-loongson-2k1000) | |
| - [Build for Termux on Android](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-termux-on-android) | |
| - [Build for QNX](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-qnx) | |
| **[download prebuild binary package for android and ios](https://github.com/Tencent/ncnn/releases)** | |
| **[use ncnn with alexnet](https://github.com/Tencent/ncnn/wiki/use-ncnn-with-alexnet) with detailed steps, recommended for beginners :)** | |
| **[ncnn 组件使用指北 alexnet](https://github.com/Tencent/ncnn/wiki/use-ncnn-with-alexnet.zh) 附带详细步骤，新人强烈推荐 :)** | |
| **[use netron for ncnn model visualization](https://netron.app)** | |
| **[out-of-the-box web model conversion](https://convertmodel.com/#outputFormat=ncnn)** | |
| [ncnn low-level operation api](https://github.com/Tencent/ncnn/wiki/low-level-operation-api) | |
| [ncnn param and model file spec](https://github.com/Tencent/ncnn/wiki/param-and-model-file-structure) | |
| [ncnn operation param weight table](https://github.com/Tencent/ncnn/wiki/operation-param-weight-table) | |
| [how to implement custom layer step by step](https://github.com/Tencent/ncnn/wiki/how-to-implement-custom-layer-step-by-step) | |
| --- | |
| ## FAQ | |
| **[ncnn throw error](https://github.com/Tencent/ncnn/wiki/FAQ-ncnn-throw-error)** | |
| **[ncnn produce wrong result](https://github.com/Tencent/ncnn/wiki/FAQ-ncnn-produce-wrong-result)** | |
| **[ncnn vulkan](https://github.com/Tencent/ncnn/wiki/FAQ-ncnn-vulkan)** | |
| --- | |
| ## Features | |
| - Supports convolutional neural networks, supports multiple input and multi-branch structure, can calculate part of the branch | |
| - No third-party library dependencies, does not rely on BLAS / NNPACK or any other computing framework | |
| - Pure C++ implementation, cross-platform, supports Android, iOS and so on | |
| - ARM NEON assembly level of careful optimization, calculation speed is extremely high | |
| - Sophisticated memory management and data structure design, very low memory footprint | |
| - Supports multi-core parallel computing acceleration, ARM big.LITTLE CPU scheduling optimization | |
| - Supports GPU acceleration via the next-generation low-overhead Vulkan API | |
| - Extensible model design, supports 8bit quantization and half-precision floating point storage, can import caffe/pytorch/mxnet/onnx/darknet/keras/tensorflow(mlir) models | |
| - Support direct memory zero copy reference load network model | |
| - Can be registered with custom layer implementation and extended | |
| - Well, it is strong, not afraid of being stuffed with 卷 QvQ | |
| ## 功能概述 | |
| - 支持卷积神经网络，支持多输入和多分支结构，可计算部分分支 | |
| - 无任何第三方库依赖，不依赖 BLAS/NNPACK 等计算框架 | |
| - 纯 C++ 实现，跨平台，支持 Android / iOS 等 | |
| - ARM Neon 汇编级良心优化，计算速度极快 | |
| - 精细的内存管理和数据结构设计，内存占用极低 | |
| - 支持多核并行计算加速，ARM big.LITTLE CPU 调度优化 | |
| - 支持基于全新低消耗的 Vulkan API GPU 加速 | |
| - 可扩展的模型设计，支持 8bit [量化](tools/quantize) 和半精度浮点存储，可导入 caffe/pytorch/mxnet/onnx/darknet/keras/tensorflow(mlir) 模型 | |
| - 支持直接内存零拷贝引用加载网络模型 | |
| - 可注册自定义层实现并扩展 | |
| - 恩，很强就是了，不怕被塞卷 QvQ | |
| --- | |
| ## supported platform matrix | |
| - ✅ = known work and runs fast with good optimization | |
| - ✔️ = known work, but speed may not be fast enough | |
| - ❔ = shall work, not confirmed | |
| - / = not applied | |
| | | Windows | Linux | Android | macOS | iOS | | |
| | ---------- | ------- | ----- | ------- | ----- | --- | | |
| | intel-cpu | ✔️ | ✔️ | ❔ | ✔️ | / | | |
| | intel-gpu | ✔️ | ✔️ | ❔ | ❔ | / | | |
| | amd-cpu | ✔️ | ✔️ | ❔ | ✔️ | / | | |
| | amd-gpu | ✔️ | ✔️ | ❔ | ❔ | / | | |
| | nvidia-gpu | ✔️ | ✔️ | ❔ | ❔ | / | | |
| | qcom-cpu | ❔ | ✔️ | ✅ | / | / | | |
| | qcom-gpu | ❔ | ✔️ | ✔️ | / | / | | |
| | arm-cpu | ❔ | ❔ | ✅ | / | / | | |
| | arm-gpu | ❔ | ❔ | ✔️ | / | / | | |
| | apple-cpu | / | / | / | ✔️ | ✅ | | |
| | apple-gpu | / | / | / | ✔️ | ✔️ | | |
| | ibm-cpu | / | ✔️ | / | / | / | | |
| --- | |
| ## Project examples | |
| - <https://github.com/nihui/ncnn-android-squeezenet> | |
| - <https://github.com/nihui/ncnn-android-styletransfer> | |
| - <https://github.com/nihui/ncnn-android-mobilenetssd> | |
| - <https://github.com/moli232777144/mtcnn_ncnn> | |
| - <https://github.com/nihui/ncnn-android-yolov5> | |
| - <https://github.com/xiang-wuu/ncnn-android-yolov7> | |
| - <https://github.com/nihui/ncnn-android-scrfd> 🤩 | |
| - <https://github.com/shaoshengsong/qt_android_ncnn_lib_encrypt_example> | |
| <img src="https://github.com/nihui/ncnn-assets/raw/master/20181217/ncnn-2.jpg" height ="230"/><img src="https://github.com/nihui/ncnn-assets/raw/master/20181217/4.jpg" height ="230"/><img src="https://github.com/nihui/ncnn-assets/raw/master/20181217/ncnn-33.jpg" height ="230"/><img src="https://github.com/nihui/ncnn-assets/raw/master/20181217/ncnn-m.png" height ="230"/><img src="https://github.com/nihui/ncnn-android-yolov5/raw/master/screenshot.jpg" height ="230"/><img src="https://github.com/nihui/ncnn-android-scrfd/raw/master/screenshot.jpg" height ="230"/><br> | |
| - <https://github.com/magicse/ncnn-colorization-siggraph17><br> | |
| <img src="https://user-images.githubusercontent.com/13585785/189326958-f5a8d6f8-caef-49bf-88da-ae494371195d.jpg" width ="700"/> | |
| - <https://github.com/mizu-bai/ncnn-fortran> Call ncnn from Fortran | |
| - <https://github.com/k2-fsa/sherpa> Use ncnn for real-time speech | |
| recognition (i.e., speech-to-text); also support embedded devices and provide | |
| mobile Apps (e.g., Android App) | |
| --- | |
| ## License | |
| [BSD 3 Clause](LICENSE.txt) | |