swarmsort.core module

SwarmSort Core Implementation

This module contains the core SwarmSort multi-object tracking algorithm implementation. SwarmSort combines Kalman filtering, Hungarian algorithm assignment, and deep learning embeddings for robust real-time object tracking.

Classes:

SwarmSortTracker: Main tracking class implementing the full algorithm

class swarmsort.core.SwarmSortTracker(config=None, embedding_type=None, use_gpu=None, **kwargs)[source]

Bases: object

Main SwarmSort multi-object tracker implementation.

This class implements a sophisticated tracking algorithm that combines: - Kalman filtering for motion prediction - Hungarian/Greedy assignment for detection-track matching - Deep learning embeddings for appearance-based matching - Re-identification for recovering lost tracks

__init__(config=None, embedding_type=None, use_gpu=None, **kwargs)[source]

Initialize the SwarmSort tracker with configuration.

Parameters:

  • config (Union[SwarmSortConfig, dict, None]) – Configuration object or dictionary

  • embedding_type (Optional[str]) – Type of embedding extractor to use (overrides config)

  • use_gpu (Optional[bool]) – Whether to use GPU for embeddings (overrides config)

  • **kwargs – Additional keyword arguments (ignored for compatibility)

property frame_count

Get current frame count.

get_state()[source]

Get current tracker state for debugging.

Return type:

dict

get_statistics()[source]

Get tracker statistics for benchmarking and analysis.

Returns:

  • next_id: Next track ID to be assigned (= total tracks created)

  • active_tracks: Number of currently active tracks

  • confirmed_tracks: Number of confirmed tracks

  • pending_detections: Number of pending detections

  • frame_count: Total frames processed

Return type:

Dictionary containing

reset()[source]

Reset the tracker to initial state.

This clears all tracks, pending detections, and resets the embedding scaler statistics. Use when starting a new video or scene.

update(detections)[source]

Main update function for the tracker.

Parameters:

detections (List[Detection]) – List of Detection objects for current frame

Return type:

List[TrackedObject]

Returns:

List of TrackedObject instances representing current tracks

Raises:
class swarmsort.core.Timer[source]

Bases: object

Simple high-resolution timer for performance profiling.

start(key)[source]

Start timing for the given key.

Return type:

None

stop(key, store)[source]

Stop timing for the given key and accumulate the duration.

Return type:

None