DeepStack GPU Version serves requests 5 - 20 times faster than the CPU version if you have an NVIDIA GPU.
NOTE: THE GPU VERSION IS ONLY SUPPORTED ON LINUX, WINDOWS SUPPORT IS COMING SOON.
Before you install the GPU Version, you need to follow the steps below.
If you already have docker installed, you can skip this step.
sudo apt-get updatesudo apt-get install curlcurl -fsSL get.docker.com -o get-docker.sh && sh get-docker.sh
Install the NVIDIA Driver
The native docker engine does not support GPU access from containers, however nvidia-docker2modifies your docker install to support GPU access.
Run the commands below to modify the docker engine
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \sudo apt-key add -distribution=$(. /etc/os-release;echo $ID$VERSION_ID)curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \sudo tee /etc/apt/sources.list.d/nvidia-docker.listsudo apt-get updatesudo apt-get install -y nvidia-docker2sudo pkill -SIGHUP dockerd
If you run into issues, you can refer to this GUIDE
sudo docker pull deepquestai/deepstack:gpu
If you are running an old system without modern cpu instructions such as AVX, please use the Legacy System Version
Once the above steps are complete, when you run deepstack, add the args –rm –runtime=nvidia
sudo docker run --rm --runtime=nvidia -e VISION-SCENE=True -v localstorage:/datastore \-p 80:5000 deepquestai/deepstack:gpu
--rm --runtime=nvidia This enables gpu access to the DeepStack container
-e VISION-SCENE=True This enables the scene recognition API, all apis are disabled by default.
-v localstorage:/datastore This specifies the local volume where DeepStack will store all data.
-p 80:5000 This makes DeepStack accessible via port 80 of the machine.
The first time you run DeepStack, you need to activate it following the process below.
Once you initiate the run command above, visit localhost:80 in your browser. The interface below will appear.
Get an activation key from DeepStack.cc , paste it in the box and click Activate Now. Once activated, the interface below will appear.
Once installed, run the example scene recognition code to verify your installation is working