Object Detection And Tracking

One-line version: YOLOv11 object detection notebooks plus OpenCV tracking demos in one clean computer vision repo.

What It Does

This repo combines two things that usually work together:

• Object detection: YOLOv11 notebooks for finding objects in images.
• Object tracking: OpenCV scripts for following a selected object frame by frame.

It is useful as a learning and showcase repo because it shows both sides of the workflow: first detect the object, then track where it goes. A camera sees chaos; this repo tries to give it a job description.

Demo Preview

Quick Start

Clone the repo:

git clone https://github.com/Siddharth-k7/Object-detection-and-tracking.git
cd Object-detection-and-tracking

Install the basics:

pip install -r tracking/opencv_trackers/requirements.txt
pip install ultralytics jupyter

Open the notebooks:

jupyter notebook

Run a tracker demo:

python tracking/opencv_trackers/kcf.py

Some trackers need opencv-contrib-python, which is already listed in the tracking requirements. If OpenCV complains anyway, it is doing its traditional warm-up routine.

Repo Structure

.
├── assets/                       # banner, GIF, and notebook preview images
├── docs/                         # extra project notes
├── notebooks/object_detection/   # YOLOv11 detection notebooks
├── tests/                        # lightweight repository tests
├── tracking/opencv_trackers/     # OpenCV tracker demos
├── .github/workflows/ci.yml      # CI for compile checks and tests
├── CHANGELOG.md
├── CONTRIBUTING.md
├── LICENSE.md
└── README.md

Topics And Files

Topic	File
Getting started with YOLOv11 object detection	notebooks/object_detection/Getting_Started_with_Yolov11__Object_Detection.ipynb
Custom dataset training with YOLOv11	notebooks/object_detection/Custom_Dataset_Training_with_YOLOv11.ipynb
BOOSTING tracker	tracking/opencv_trackers/boosting.py
CSRT tracker	tracking/opencv_trackers/csrt.py