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...You can compile the source code under Windows, Linux, ARM and any platform with a C++ compiler. SIMD instructions are used to speed up the detection. You can enable AVX2 if you use IntelCPU or NEON for ARM. The model file has also been provided in directory ./models/. The file examples/detect-image.cpp and examples/detect-camera.cpp show how to use the library. The library was trained by libfacedetection.train. You can copy the files in directory src/ into your project, and compile them as the other files in your project. ...
...Darknet on the CPU is fast (approximately 1.5 seconds on an Intel Core i7-6700HQ CPU @ 2.60GHz × 8) but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. The CMakeLists.txt file automatically detects if you have CUDA installed or not. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia.