Vaas is a video analytics system for large-scale video datasets. It provides a web interface that incorporates a query composition tool and data exploration tool to accelerate the development of complex query pipelines. Vaas also provides a human-in-the-loop query optimization framework to accelerate query execution.
Website: https://vaas.csail.mit.edu
The fastest way to get started is with Docker. First, install nvidia-docker; on Ubuntu (tested on 16.04):
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
distribution=$(. /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 update && sudo apt install -y docker-ce docker-ce-cli containerd.io nvidia-container-toolkit
sudo systemctl restart docker
Then:
git clone https://github.com/mit-vaas/vaas.git
cd vaas
docker build -t mit-vaas/vaas .
docker container create -p 8080:8080 --gpus all mit-vaas/vaas
Access your Vaas deployment at http://localhost:8080.
If you want to run it without Docker, first install CUDA 10.0 and cuDNN 7.6, then follow the RUN commands in Dockerfile.
- VLDB 2020 demo paper and video
- Website: https://vaas.csail.mit.edu