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FORT (Fisheye Online Realtime Tracking) repository - Tracking algorithm tested on people in top down fisheye images.

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FORT

FORT - Fisheye Online Realtime Tracking

Paper -
Fisheye detection dataset - https://github.com/BenoitFaureIMT/CERIS_FishEye

Structure

Detection.py - Contains detection algorithm objects (YOLOv7)
Filter.py - Contains the Kalman filter logic
ReID.py - Contains ReID algorithm objects (ResNeXt50)
Target.py - Contains the definition of a track object
Utils.py - Utility functions

detect.py - Used to run the code -> Creates the detector -> Creates the tracker -> Reads video -> Feeds images into detector to get detections -> Feeds detections into tracker

Installation

Use the package manager pip to install the required modules.

pip install -r requirements.py

Usage

python detect.py --video <path to video> --show_results --save_results [other args]

All arguments:

Option Description
--wait_screen add a wait screen before tracking starts
--show_results display results on screen
--save_results save display results
--save_MOT save targets to file in MOT format
--video path to video file
--weights path to YoloV7 weights
--filter_weight_path path to weiths of NNFilter
--age_max age max of tracklets
--alpha alpha coeff for EMA
--IoU_threshold IoU threshold for association
--cosine_threshold Cosine threshold for association
--cost_threshold Threshold between high and low score detections
--distance_threshold Distance threshold for association

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FORT (Fisheye Online Realtime Tracking) repository - Tracking algorithm tested on people in top down fisheye images.

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