Prerequisite: conda and/or miniconda are already installed
- Create a conda environment.
$ conda create -n dlib python=3.8 cmake ipython- Activate the environment.
$ conda activate dlib- Install CUDA and cuDNN with
condausing nvidia channel
$ conda install cuda cudnn -c nvidiaThen find the path to the nvcc of this environment. We will use this path for the build step below
$which nvcc
/path/to/your/miniconda3/envs/dlib/bin/- Install dlib. Clone and build dlib from source
$ git clone https://github.com/davisking/dlib.git
$ cd dlib
$ mkdir build
$ cd build
$ cmake .. -DDLIB_USE_CUDA=1 -DUSE_AVX_INSTRUCTIONS=1 -DCUDAToolkit_ROOT=/path/to/your/miniconda3/envs/dlib/bin/
$ cmake --build .
$ cd ..
$ python setup.py install --set DLIB_USE_CUDA=1- Test dlib
(dlib) $ ipython
Python 3.8.12 (default, Oct 12 2021, 13:49:34)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.27.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import dlib
In [2]: dlib.DLIB_USE_CUDA
Out[2]: True
In [3]: print(dlib.cuda.get_num_devices())
1
Thank you so much! I was wondering what was going on. Also make sure for anyone getting an error for not being able to find specific header files to ensure that your file paths are easily readable by C++ compilers. For example: If i have a apostrophe in my file path ex. C:\Go'Up, dlib will say it cannot find some header files when compiling for CUDA. But if i have ex. C:Go_Up, the problem is solves