# Qidian213/deep_sort_yolov3

Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow

Repository: https://github.com/Qidian213/deep_sort_yolov3
Canonical: https://ross.abutalabs.com/products/deep_sort_yolov3
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: yolov3, tracker, pedestrian, real-time, deep-sort
Last push: 2021-03-22T02:56:19+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": 3040, "days_push": 1990, "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 1675, forks 586 (observed 2026-08-28T04:05:20.520434+00:00)

## What it is
A real-time multi-person tracker that combines YOLOv3 object detection with the Deep SORT tracking algorithm, implemented in Python with TensorFlow/Keras. It detects and tracks pedestrians (and optionally other COCO classes) in video streams or from a camera at roughly 11 fps on a GTX 1060.

## Use cases
- track multiple people in a video in real time
- pedestrian tracking with yolo and deep sort
- count and follow people across camera frames
- multi-object tracking demo with tensorflow
- detect and track persons from webcam feed
- build a people tracking pipeline for surveillance video

## When to choose
- you need a simple, ready-to-run YOLOv3 + Deep SORT baseline in TensorFlow 1.x
- you want to track pedestrians in real time on a modest GPU
- you want a reference implementation to swap in a different detector

## When to avoid
- you need a maintained or modern implementation - the author recommends PyTorch alternatives
- you want to train models or use recent TensorFlow/PyTorch versions
- you need high accuracy state-of-the-art MOT performance (FairMOT, CenterTrack, etc.)
- you need to track non-person classes without modifying code

## Facets
- artifact type: application
- maturity: abandoned
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, artificial-intelligence
- platform: python
- tags: object-tracking, multi-object-tracking, yolo, deep-sort, pedestrian-tracking, tensorflow, keras, real-time, video, gpu, linux

## Member repositories
- Qidian213/deep_sort_yolov3 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:20.520434+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 2026-08-30T03:42:28.420413+00:00, confidence not recorded.
  - readme: https://github.com/Qidian213/deep_sort_yolov3 (fetched 2026-08-28T04:05:20.520434+00:00, sha 887f3572d180)
- Data as of 2026-08-30T08:39:29.467469+00:00.