Daemon that receives emails from cameras (with motion detection images attached) and uses Deepstack to identify and tag the presence of people, vehicles, et cetra. If items of interest are located, an alert is sent out via Pushover.
oddspot installs as a Docker Compose stack.
These instructions are for a stock Ubuntu 22.04 LTS system.
Install base dependencies:
sudo apt-get -y install sendemail curl
curl -fsSL get.docker.com -o get-docker.sh && sudo sh get-docker.sh
#add your user to the docker group
sudo adduser $USER docker
#either log out and back in, or run this next command for the group changes to take effect...
su - $USER
If you have a CUDA-capable NVIDIA GPU installed in your system, oddspot will work with it automatically, as long as the drivers are installed.
sudo apt-get -y install ubuntu-drivers-common nvidia-cuda-toolkit
sudo ubuntu-drivers autoinstall
#Then reboot your system for the driver to be properly loaded.
sudo reboot
Note that if you run into an "unmet dependencies" error during running of the ubuntu-drivers autoinstall command, try the following:
sudo apt-get remove --purge nvidia-* -y
sudo apt autoremove
sudo ubuntu-drivers autoinstall
If using a GPU -- Install Nvidia container toolkit as well:
# install nvidia container toolkit
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
&& curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker
# test and make sure the GPU is visible from a docker container
docker run --rm --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi
Copy the conf/oddspot.ini.dist file to conf/oddspot.ini and customize it to your needs.
Once created, set the proper permissions:
sudo chown ${USER}:35501 conf/oddspot.ini
sudo chmod 640 conf/oddspot.ini
If you have a GPU:
docker compose build
docker compose up
If using a CPU:
docker compose build
docker compose -f docker-compose-cpu.yml up
Then, copy a camera capture image to the system, and run the following command in another terminal window to send a test email that oddspot should pick up and process:
sendemail -f test@test.com -t oddspot@localhost -s localhost:10025 -u 'testing 123' -m 'test' -a <TESTIMAGE>.jpg
Tail /home/<USER>/oddspot/logs/oddspot.log to see if processing was successful or not.
Just launch docker compose up -d (or docker compose -f docker-compose-cpu.yml up -d for CPU-only installs). The service will properly launch after a reboot.
Modify your camera setup (via its embedded web configuration page) to send an email to oddspot@<YOURMACHINE>:<YOURPORT> on motion detection events. Make sure it attaches a snapshot of the event in jpeg or png format (and not a video). Also, to avoid flooding the script, you should probably have it so that it will only send repeat emails every minute or more. The oddspot script allows you to further limit continuous emails on a per camera basis via the min_notify_period config setting, but it should get raw emails from the cameras on motion events more frequently than that, to maximize alerting accuracy).