This snap uses a MobileNet SSD network to detect vehicles in a video stream, and then tracks them using the CSRT tracker algorithm implemented on OpenCV. The distance from the camera to the vehicles is then estimated by a simple formula using the bounding box for the vehicle and the camera's focal distance. The later is hard-coded in the code, so do not expect anything accurate: it is more of an example application.
The program is able to track multiple vehicles while still running the neural network for detections on the stream. Extensive multi-threading is used to accomplish this while at the same time trying to be as real-time as possible. This means that the trackers are fed with the latest available frames and some times older frames are not processed.
Sources can be found at https://github.com/alfonsosanchezbeato/car-distance-finder
Snaps are applications packaged with all their dependencies to run on all popular Linux distributions from a single build. They update automatically and roll back gracefully.
Snaps are discoverable and installable from the Snap Store, an app store with an audience of millions.
Snap can be installed on Pop!_OS from the command line. Open Terminal from the Applications launcher and type the following:
sudo apt update
sudo apt install snapd
Either log out and back in again, or restart your system, to ensure snap’s paths are updated correctly.
To install car-distance-finder, simply use the following command:
sudo snap install car-distance-finder
Browse and find snaps from the convenience of your desktop using the snap store snap.
Interested to find out more about snaps? Want to publish your own application? Visit snapcraft.io now.
