If you have AIDE v1 already running and want to upgrade its contents to AIDE v2, see here.
New since AIDE version 2.1: AIDE now offers an interactive installation script (beta) for easy setup that even supports configuring it to launch at system boot!
- Install a Python environment manager, such as Conda (recommended and used below) or Virtualenv.
- Create a new Python environment for AIDE:
conda create -y -n aide python=3.8
conda activate aide
- Clone the AIDE repository:
git clone https://github.com/microsoft/aerial_wildlife_detection.git && cd aerial_wildlife_detection/
- Launch installer and follow the instructions:
./install/install_debian.sh
Tip: the installer also supports more advanced configurations; you can check it out by calling ./install/install_debian.sh --help
.
If you wish to install AIDE in a self-contained environment instead of the host operating system, you can do so with Docker:
- Download and install Docker as well as Docker Compose
- If you want to use a GPU (and only then), you have to install the NVIDIA container toolkit:
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker
- Clone the AIDE repository:
git clone https://github.com/microsoft/aerial_wildlife_detection.git && cd aerial_wildlife_detection/
- Important: modify the
docker/settings.ini
file and replace the default super user credentials (section[Project]
) with new values. Make sure to review and update the other default settings as well, if needed. - Install:
Note: for older versions, you might have to issue
cd docker sudo docker compose build cd ..
sudo docker-compose build
(with a hyphen) instead. - Launch:
- With Docker:
sudo docker/docker_run_cpu.sh # for machines without a GPU sudo docker/docker_run_gpu.sh # for AIWorker instances with a CUDA-enabled GPU (strongly recommended for model training)
- With Docker Compose (note that Docker Compose currently does not provide support for GPUs):
cd docker sudo docker-compose up
See here for instructions on configuring an instance of AIDE.
After that, see here for instructions on launching an instance of AIDE.
Instructions coming soon.