You will get Multi-Camera Video Management System (Linux/Windows)
Project details
Video Management System is a high-performance desktop surveillance application built with Python and PySide6. It utilizes a multi-process architecture with shared memory to decouple heavy video processing from the GUI, ensuring a responsive user experience.
Key Features:
• Universal Connectivity: Supports USB webcams, RTSP streams, and local video files. Includes an ONVIF Discovery tool to automatically find and connect to network cameras.
• AI & Analytics Engine: A modular plugin system powers advanced features like YOLOv8 object detection (identifying people, weapons, etc.), SORT object tracking with visual trails, and Fire/Smoke detection using wavelet analysis.
• Visual Pipeline Editor: A node-based graph editor allows users to dynamically chain processing blocks (e.g., Input → Grayscale → AI → Output) via drag-and-drop.
• Modern GUI: Features a dynamic grid with drag-and-drop camera swapping, focus mode, full-screen support, and custom themes (Dark, Moonlight, etc.).
• System Monitoring: Built-in real-time visualization of CPU, RAM, and NVIDIA GPU/VRAM usage.
• Management: Supports manual recording, snapshots, and saving/loading camera layouts via JSON presets.
Key Features:
• Universal Connectivity: Supports USB webcams, RTSP streams, and local video files. Includes an ONVIF Discovery tool to automatically find and connect to network cameras.
• AI & Analytics Engine: A modular plugin system powers advanced features like YOLOv8 object detection (identifying people, weapons, etc.), SORT object tracking with visual trails, and Fire/Smoke detection using wavelet analysis.
• Visual Pipeline Editor: A node-based graph editor allows users to dynamically chain processing blocks (e.g., Input → Grayscale → AI → Output) via drag-and-drop.
• Modern GUI: Features a dynamic grid with drag-and-drop camera swapping, focus mode, full-screen support, and custom themes (Dark, Moonlight, etc.).
• System Monitoring: Built-in real-time visualization of CPU, RAM, and NVIDIA GPU/VRAM usage.
• Management: Supports manual recording, snapshots, and saving/loading camera layouts via JSON presets.
Programming Languages
PythonOperating System
LinuxDevelopment Technology
QtDesktop App Expertise
App Design, Application Setup & Installation, Development, Software Debugging, Performance Optimization, Security, Localization, Application Review & OptimizationWhat's included
| Service Tiers |
Starter
$450
|
Standard
$750
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 days |
Number of Revisions | 1 | 2 | 2 |
Source Code | |||
Setup File | |||
Detailed Code Comments |
Optional add-ons
You can add these on the next page.
Additional Revision
+$150
Additional Custom Plugin
(+ 10 Days)
+$750
Advanced Alerting Module
(+ 7 Days)
+$250
DAWG Pipeline Creator
(+ 7 Days)
+$250
4 reviews
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KR
Kiran R.
Jun 28, 2023
Json improvements using python
MS
Matthew S.
May 13, 2022
Computer Vision Final project
He was generally unresponsive. He did not respond and it felt like once he logged out of Upwork then I had to wait an entire day or 2 for him to respond to my latest message or give my a status report.
I have never had this experience in all my years of using the Upwork platform
I have never had this experience in all my years of using the Upwork platform
MS
Matthew S.
May 1, 2022
Computer Vision Project
He was very helpful to help my friend meet a crucial deadline. I am very thankful for that! :)
SJ
Stefaan J.
Jun 13, 2020
Developer opencv
great guy, great developer, covid 19 got in the way of his work, understandable
About Anubhav
Computer Vision & Applied Machine Learning Expert
Gurgaon, India - 12:45 pm local time
- Development and implementation of a wide range of image/video processing
algorithms(object detection and classification, tracking)
- Software development under OS Windows and Linux
- Strong experience and skills in using C/C++, Python and Machine Learning libraries
- Deep research and analytic experience
- Project management and technical project coordination
- Micro-services and independent desktop applications.
All my last projects are connected with computer vision and image processing, visualization and control systems. I work autonomously, independently or as part of team.
Coding Language : C++11, Python, JavaScript, HTML/CSS
Machine Learning : Keras, Tensorflow, Scikit-learn, Scikit-image, Tesseract OCR, SpaCy, PyTorch
Image Processing OpenCV, DLIB, ArrayFire, Leptonica
Data Pipeline/ ETL :MySQL, MongoDB, HDFS, Kafka, Hive
Tools & Frameworks : QT, Google Test Suite, Valgrind, GDB, Vim, CMake, GIT, SVN, Docker, Kubernetes
Key Areas - Object Detection & Tracking, Augmented Reality, Pattern Recognition, OCR, Face Recognition & Image Enhancement, Face Recognition, Video analytics, NLP, PDF Data Extraction.
Steps for completing your project
After purchasing the project, send requirements so Anubhav can start the project.
Delivery time starts when Anubhav receives requirements from you.
Anubhav works on your project following the steps below.
Revisions may occur after the delivery date.
Explicitly define requirements in-case of any modifications/revisions