DaisyKit C++

Daisykit SDK - C++ is the core of models and algorithms in NCNN deep learning framework. Using C++ code provides often provides the best performance for the algorithms.

1. Environment Setup

Ubuntu

Install packages from Terminal

sudo apt install -y build-essential libopencv-dev
sudo apt install -y libvulkan-dev vulkan-utils
sudo apt install -y mesa-vulkan-drivers # For Intel GPU support

Windows

For Windows, Visual Studio 2019 + Git Bash is recommended.

Download and extract OpenCV from the official website (opens in a new tab), and add OpenCV_DIR to path.
Download precompiled NCNN (opens in a new tab).

2. Build and run C++ examples

Clone the source code:

git clone https://github.com/nrl-ai/daisykit.git --recursive
cd daisykit

Ubuntu

Build Daisykit:

mkdir build
cd build
cmake .. -Dncnn_FIND_PATH="<path to ncnn lib>"
make

Run face detection example:

./bin/demo_face_detector_graph

If you dont specify ncnn_FIND_PATH, NCNN will be built from scratch.

Windows

Build Daisykit:

mkdir build
cd build
cmake -G "Visual Studio 16 2019" -Dncnn_FIND_PATH="<path to ncnn lib>" ..
cmake --build . --config Release

Run face detection example:

./bin/Release/demo_face_detector_graph

3. C++ Coding convention

Read coding convention and contribution guidelines here.

Object Detection Face Detection