You will get real-time face recognition from video or webcam
Top Rated
Project details
This project delivers a real-time face recognition web application using Python, OpenCV, and the face_recognition library. It detects and identifies faces from images, videos, webcams, or IP cameras, with support for user management and live attendance tracking. The system includes a backend built with FastAPI and a simple web interface for uploading media, viewing recognition results, and managing users. Recognized faces are logged with names, timestamps, and attendance status, stored in CSV files. A dashboard displays real-time stats like the number of users recognized. The solution is scalable, secure, and suitable for offices, schools, or access control systems.
AI Development Type
Deep Learning, Model Tuning, Software MaintenanceAI Tools
Azure Machine Learning, Google AutoML, Keras, MLflow, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$250
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | - | - | |
Knowledge Graph | - | - | - |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $300
Additional Revision
+$50
66 reviews
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SK
Samet Can K.
May 8, 2026
30 minute consultation
Meer is a truly outstanding professional. He provided me with a far more detailed and comprehensive work plan than I initially expected. The level of effort and depth he delivered exceeded my expectations. Every single one of my questions was answered clearly and professionally. Highly recommended.
MG
Mohamad G.
Apr 14, 2026
AI COCOA SOLUTIONS
Exceptional work, clear communication, and outstanding results, highly recommend and looking forward to collaborating further
LC
Livia C.
Mar 24, 2026
Text analysis in 4 colab notebooks
SS
Saqib S.
Dec 19, 2025
AI Business Incubator SAAS
Working with Meer on our AI Business Incubator SAAS was an absolute pleasure! He delivered exceptional work from start to finish, demonstrating strong technical skills and excellent communication throughout the project. The end result exceeded our expectations, and I wouldn't hesitate to work with him again. Highly recommended for anyone looking for a reliable and talented developer!
VC
Victor C.
Jul 2, 2025
LLM product developer with experience in RAG
Moazzam was instrumental in the success of our BRAIN project, an advanced virtual analyst powered by AI. He showed deep technical expertise across both backend and frontend development, as well as a strong understanding of machine learning and intelligent agent workflows.
His code was clean, well-structured, and thoughtfully designed. Moazzam consistently contributed beyond expectations — proposing smart architectural decisions, solving complex problems independently, and always delivering on time. His attitude was professional, solution-oriented, and collaborative at all times.
A true asset to any AI or data-intensive development project. We’d gladly work with him again.
His code was clean, well-structured, and thoughtfully designed. Moazzam consistently contributed beyond expectations — proposing smart architectural decisions, solving complex problems independently, and always delivering on time. His attitude was professional, solution-oriented, and collaborative at all times.
A true asset to any AI or data-intensive development project. We’d gladly work with him again.
About Meer
Full Stack AI Engineer | AI Agents, RAG, LLM Apps, Computer Vision
100%
Job Success
Lahore, Pakistan - 5:37 am local time
6+ years, 80+ AI projects delivered off and on Upwork, including the AI layer behind a PropTech platform that raised $2M, work on a portrait product with 25M+ AI headshots generated, and multi-agent systems running live for enterprise clients.
WHAT I BUILD
🤖 AI AGENTS & LLM APPS
Multi-agent systems with LangGraph, CrewAI, and AutoGen. Custom chatbots and AI assistants on GPT-4o, Claude, and Gemini. Every agent ships with evals and observability (LangSmith, Langfuse, RAGAS); if it can't be measured, it isn't done.
📚 RAG & KNOWLEDGE SYSTEMS
RAG pipelines with LangChain and LlamaIndex over Pinecone, Weaviate, FAISS, ChromaDB, Milvus, and pgvector. Grounded answers with citations, not confident hallucinations.
📞 VOICE AI
Real-time phone agents with Twilio, Deepgram, ElevenLabs, and VAPI: reception, booking, support. Voice agents delivered across dental, pest control, plumbing, and vehicle services.
👁️ COMPUTER VISION
YOLOv8/PyTorch detection and segmentation deployed to real cameras and edge hardware (Jetson, DeepStream): 30 FPS pipelines on live industrial and construction sites. Published CV researcher (Sensors, MDPI, 30+ citations).
⚙️ AI AUTOMATION
n8n, Make, and Zapier workflows wired to LLMs: lead qualification, invoice processing, content pipelines, CRM automation.
🏗️ FULL STACK DELIVERY
FastAPI, Django, and Node.js backends; React and Next.js frontends; PostgreSQL, MongoDB, Redis; deployed on AWS, GCP, and Azure with Docker and Kubernetes.
HOW I WORK
Production first: monitoring, evals, and error handling from day one, not after launch
Clear communication: clients tag me "Clear Communicator" and "Committed to Quality" more than any other trait
Fast start: available now, quick responses, honest scoping before you spend a dollar
KEY TECHNOLOGIES
Python · FastAPI · LangGraph · LangChain · LlamaIndex · CrewAI · AutoGen · OpenAI GPT-4o · Anthropic Claude · Google Gemini · RAG · Pinecone · Weaviate · FAISS · ChromaDB · PyTorch · TensorFlow · YOLOv8 · OpenCV · MediaPipe · Twilio · Deepgram · ElevenLabs · VAPI · n8n · Make · Zapier · React · Next.js · Node.js · TypeScript · PostgreSQL · MongoDB · Redis · Docker · Kubernetes · AWS · GCP · Azure
Message me with what you're building. I'll reply with a concrete plan, not a template.
Steps for completing your project
After purchasing the project, send requirements so Meer can start the project.
Delivery time starts when Meer receives requirements from you.
Meer works on your project following the steps below.
Revisions may occur after the delivery date.
Collect Images
Upload multiple face images for each user into folders labeled by name.
Generate Encodings
Run script to detect faces and save encodings in a .pkl file using face_recognition.