You will get real time video surveillance system which detects fight in video input.
Project details
You will get a powerful real-time violence detection system that uses deep learning and computer vision to identify aggressive behavior in surveillance footage. With hands-on experience in AI, video processing, and full-stack integration, I build intelligent systems that prioritize speed, accuracy, and reliability. My solutions are tested across multiple environments and are tailored to your specific use case—be it schools, malls, public areas, or private property. The work I deliver is fully customizable, high performance, and ready for real-world deployment.
Machine Learning Tools
NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQLWhat's included
| Service Tiers |
Starter
$100
|
Standard
$150
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 4 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 1 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 1 | 1 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - | - |
About Umesh
Full Stack Developer | React, Node.js & AI Applications
Dhangadhi, Nepal - 7:49 am local time
With a solid background in machine learning, deep learning, and prompt engineering, I deliver intelligent solutions tailored to clients’ needs. I'm also well-versed in databases (SQL/NoSQL), cloud tools like Firebase, and modern deployment tools like Streamlit. Whether you're looking for AI-powered applications, smart chatbots, or scalable backend systems, I bring a balance of technical skill and project management experience to ensure successful delivery.
Steps for completing your project
After purchasing the project, send requirements so Umesh can start the project.
Delivery time starts when Umesh receives requirements from you.
Umesh works on your project following the steps below.
Revisions may occur after the delivery date.
Understand client requirements and video data scope
I will connect with you to gather details about your use-case, input video formats, environment (indoor/outdoor), and custom needs.
Model selection and initial setup
I will choose an appropriate pre-trained model or architecture (e.g., CNN + LSTM), set up the environment, and begin initial configuration.