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.