If you compiled using CUDA but want to do CPU computation for whatever reason you can use -nogpu to use the CPU instead. darknet -i 1 imagenet test cfg/alexnet.cfg alexnet.weights If you want to change what card Darknet uses you can give it the optional command line flag -i, like. By default it will run the network on the 0th graphics card in your system (if you installed CUDA correctly you can list your graphics cards using nvidia-smi). Now you can make the project and CUDA will be enabled. Once you have CUDA installed, change the first line of the Makefile in the base directory to read: GPU=1 I won't go into CUDA installation in detail because it is terrifying. Compiling With CUDAĭarknet on the CPU is fast but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA.
Great! Now check out the cool things you can do with darknet here. If you have any errors, try to fix them? If everything seems to have compiled correctly, try running it!. Gcc -I/usr/local/cuda/include/ -Wall -Wfatal-errors -Ofast. If this works you should see a whole bunch of compiling information fly by: mkdir -p obj If it doesn't work for you, email me or something? Installing The Base Systemįirst clone the Darknet git repository here.
#HOW TO INSTALL CODE CHICKEN CORE MAC#
I've only tested this on Linux and Mac computers. OpenCV if you want a wider variety of supported image types.īoth are optional so lets start by just installing the base system.Darknet is easy to install with only two optional dependancies:
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