Build Object Tracking System
by kandikits Updated: Oct 20, 2022
Real-time object tracking system is a technology used to track objects (from images, videos, and webcam) in real time. It can be used for security purposes or for commercial purposes. Tracking can be done for video formats and live streaming webcam.
The real-time object tracking system has many applications, such as in retail stores, airports, stadiums and other places where security is important. The system can be used to monitor customer activity in stores, track inventory and detect shoplifting. It can also be used to increase safety in public places by monitoring the movements of pedestrians or vehicles.
Object tracking system created using this kit are added in this section. The solution is available as a package to download from the source code repository.
- Download, extract and double-click the kit installer file to install the kit.
- After the successful installation of the kit, press 'Y' to run the kit.
- To run the kit manually, press 'N' and locate the zip file 'Yolov5_DeepSort_Pytorch'.
- Open the command prompt in the 'Yolov5_DeepSort_Pytorch' directory and run the command 'jupyter notebook'
- Locate and open the 'YOLOV5_DEEPSORT_NOTEBOOK.ipynb' notebook from the Jupyter Notebook browser window.
- Execute cells in the notebook.
Click on the button below to download the solution and follow the deployment instructions to begin set-up. This 1-click kit has all the required dependencies and resources you may need to build your Object Tracking App.
For a detailed tutorial on installing & executing the solution as well as learning resources including training & certification opportunities, please visit the OpenWeaver Community
VSCode and Jupyter Notebook can be used for development and debugging. Jupyter Notebook is a web-based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers.
Jupyter metapackage for installation, docs and chat
Python 14197 Version:Current License: Permissive (BSD-3-Clause)
Object Detection and Tracking
The following libraries have a set of pre-trained models which could be used to identify objects and track them from live streaming videos.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Python 36849 Version:v7.0 License: Strong Copyleft (GPL-3.0)
Access dict values as attributes (works recursively)
Python 169 Version:1.7 License: Weak Copyleft (LGPL-3.0)
Tensors and Dynamic neural networks in Python with strong GPU acceleration
C++ 64612 Version:v2.0.0 License: Others (Non-SPDX)
Machine Learning Libraries
The following libraries could be used to create machine learning models which focus on the vision, extraction of data, image processing, and more. Thus making it handy for the users.
The fundamental package for scientific computing with Python.
Python 23036 Version:v1.24.2 License: Permissive (BSD-3-Clause)
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python 37439 Version:v2.0.0rc1 License: Permissive (BSD-3-Clause)
Kit Solution Source
Real-time multi-object tracker using YOLO v5 and deep sort
Python 2442 Version:v5.0 License: Strong Copyleft (GPL-3.0)