Release Info
Release 0.25.1 is a major release with tested functionality and bugs fixed. It can be used in a production environment.
GitHub Page: https://github.com/insight-platform/Similari
About Similari
Similari is a Rust framework with Python bindings that helps build sophisticated tracking systems. With Similari one can develop highly efficient parallelized SORT, DeepSORT, and other sophisticated single observer (e.g. Cam) or multi-observer tracking engines.
The framework helps build various kinds of tracking and similarity search engines - the simplest one that holds vector features and allows comparing new vectors against the ones kept in the database. More sophisticated engines operate over tracks - a series of observations for the same feature collected during the lifecycle. Such systems are often used in video processing or other systems where the observer receives fuzzy or changing observation results.
Out-of-The-Box Stuff
Similari is a framework to build custom trackers, however it provides certain algorithms as an end-user functionality:
Bounding Box Kalman filter, that predicts rectangular bounding boxes axis-aligned to scene, supports the oriented (rotated) bounding boxes as well.
2D Point Kalman filter, that predicts 2D point motion.
2D Point Vector Kalman filter, that predicts the vector of independent 2D points motion (used in the Keypoint Tracker).
Bounding box clipping, that allows calculating the area of intersection for axis-aligned and oriented (rotated) bounding boxes.
Non-Maximum Suppression (NMS) - filters rectangular bounding boxes co-axial to scene, and supports the oriented bounding boxes.
SORT tracking algorithm (axis-aligned and oriented boxes are supported) - IoU and Mahalanobis distances are supported.
Batch SORT tracking algorithm (axis-aligned and oriented boxes are supported) - IoU and Mahalanobis distances are supported. Batch tracker allows passing multiple scenes to tracker in a single batch and get them back. If the platform supports batching (like Nvidia DeepStream or Intel DL Streamer) the batch tracker is more beneficial to use.
VisualSORT tracking - a DeepSORT-like algorithm (axis-aligned and oriented boxes are supported) - IoU and Mahalanobis distances are supported for positional tracking, euclidean, cosine distances are used for visual tracking on feature vectors.
Batch VisualSORT - batched VisualSORT flavor.