# ZQPei/deep_sort_pytorch

MOT using deepsort and yolov3 with pytorch

Repository: https://github.com/ZQPei/deep_sort_pytorch
Canonical: https://ross.abutalabs.com/products/deep_sort_pytorch
Language: Python
License: MIT
License Family: permissive
Topics: deepsort, pytorch, yolo3, sort, mot, cnn-model, mot-tracking, yolov3, deep-sort
Last push: 2024-07-16T04:40:59+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2898, "days_push": 778, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3012, forks 726 (observed 2026-08-28T04:07:37.832397+00:00)

## What it is
A PyTorch implementation of the Deep SORT multi-object tracking algorithm, pairing YOLOv3/YOLOv5 (or Mask R-CNN) detectors with a CNN re-identification feature extractor and Kalman filtering. It is a re-implementation of the original TensorFlow Deep SORT code.

## Use cases
- track multiple objects in video with unique IDs
- pedestrian tracking with deep sort
- object detection and tracking with yolov3 in pytorch
- re-identify people across video frames
- count and track people in surveillance footage
- instance segmentation with tracking masks

## When to choose
- you want a PyTorch alternative to the original TensorFlow Deep SORT
- you need detector-agnostic MOT with YOLOv3/v5 or Mask R-CNN
- you want to retrain the REID feature extractor yourself

## When to avoid
- you need state-of-the-art trackers like ByteTrack or BoT-SORT
- you need a production-ready maintained pipeline rather than research code
- you work outside Python/PyTorch ecosystems

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, machine-learning, deep-learning
- domain: computer-vision, deep-learning
- platform: python
- tags: object-tracking, multi-object-tracking, yolov3, yolov5, reid, kalman-filter, pytorch

## Member repositories
- ZQPei/deep_sort_pytorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:37.832397+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:47:01.882999+00:00, confidence not recorded.
  - readme: https://github.com/ZQPei/deep_sort_pytorch (fetched 2026-08-28T04:07:37.832397+00:00, sha 30f68bf18e45)
- Data as of 2026-08-30T08:39:29.467469+00:00.