Face Recognition Attendance System
Marks attendance from a live camera feed — and can explain what an embedding is when asked.
A camera-based attendance system that enrolls students from a few photos, recognises faces in a live feed, and writes attendance to a database with a timestamp. It handles the two things a demo version never does: rejecting an unknown face instead of guessing the closest match, and refusing to mark the same student twice in one session. Examiners always ask how the recognition works — the sessions make sure you can draw it on the board.
- Level
- Intermediate
- Live sessions
- 6
- Seats per college
- 2 / year
What it does
- Enroll a student from a handful of photos and build their face encoding
- Live webcam feed detecting and labelling multiple faces at once
- Unknown faces are rejected, not matched to the nearest student
- Duplicate-entry guard — one mark per student per session
- Attendance dashboard with date filters and per-subject percentage
- CSV export for submission to the department
What the sessions cover
- 01How face recognition actually works — detection, encoding, distance threshold
- 02The enrollment pipeline and where encodings are stored
- 03Live video capture, frame handling, and why you do not process every frame
- 04Matching logic, the unknown-face threshold, and the duplicate guard
- 05Flask app, database schema, and the attendance dashboard
- 06Accuracy limits, lighting failure cases, and mock viva
Stack
Pick what you need
Direct UPI / bank transfer in monthly installments. Sessions start after the first installment; handover is after the final installment. Full terms — including what happens if you stop midway.
Source
₹4,000
single payment
- Full source code
- Local setup guide
- Sample dataset / seed data
- One handover call
Academic
₹7,500
or ₹3,800/month × 2
- Everything in Source
- Project report (synopsis + full document)
- Presentation deck
- ER / DFD / architecture diagrams
- Deployment walkthrough
Mentored
Most picked₹13,000
or ₹4,400/month × 3
- Everything in Academic
- 6 live sessions on Google Meet
- Line-by-line code walkthrough
- Viva question prep + mock viva
- One module varied for you (dataset / domain)
- WhatsApp support until submission
This page has no reviews on it yet. Be the reason it does.
The first 3 students get 40% off in exchange for an honest review and permission to show your finished project here. Same build, same sessions, same handover — the discount is the price of going first, and it is not coming back once those seats are gone.
You are about to send money to a stranger on the internet.
Fair. So here is everything you need to check who I am — all of it public, all of it older than this page.
Two things I hold myself to
- Only 2 students from your college get this project in an academic year. On the Mentored tier one module is varied for you — the dataset, the domain, or a feature — so no two submissions read the same.
- You build nothing. You just have to be able to explain it. The project is delivered finished — code, report, diagrams, deployed. Then daily 60-minute sessions on Google Meet after 8:00 PM IST, walking the code you are submitting, ending in a mock viva. Turn up and you will know it well enough to answer anything the panel asks.
Enquire about this project
Tell me your submission deadline and which tier fits. You get a session schedule and an installment split back — usually within a day.
Questions students ask
- Do I have to build any of it myself?
- No. The project is built, documented, and deployed for you — code, report, deck, diagrams, and the running application. Your only job is to turn up to the sessions and learn what you are submitting.
- Can I get my own idea built instead of picking from the list?
- Yes. Send whatever your guide approved — or an idea you want built from scratch — through the custom build form. Any stack, any domain. Custom projects are quoted between ₹10,000 and ₹50,000 depending on scope, and run on the same sessions and installments.
- Do I get the source code, or only the explanation?
- You get the full source code on every tier. The Mentored tier adds live sessions where the code is walked through line by line so you can defend it in your viva.
- How do the daily sessions work?
- Sessions are live on Google Meet, one per day, starting after 8:00 PM IST so they do not clash with college hours. Each runs about 60 minutes and covers one module of the project.
- Can I pay in installments?
- Yes. Payment is direct — direct upi / bank transfer — split into monthly installments. Sessions start after the first installment; the complete source, report, and deployment handover comes after the final one.
- I can buy a project online for ₹2,000. Why does this cost more?
- Because that ₹2,000 buys a zip file. Nobody explains it to you, the same file has been sold to hundreds of students, and it collapses the moment your examiner asks why you chose that database. What you are paying for here is a project built for you, capped per college, and the sessions that make you able to answer for it. If a zip file is all you need, buy the zip file.
- How do I know you will not disappear after I take money?
- Payment is split across months, so you are never paying for work you have not seen — you watch the code in sessions from the first one. If I fail to deliver what the project page promised, your remaining installments are cancelled and the last one is returned. I also have a name attached to this: the same site carries my portfolio, my published work, and my public repositories. That is not something I would burn for one project.
- What if my guide rejects the project or asks for changes?
- Changes your guide asks for during review are made at no extra cost — that is part of the build, not a new scope. If your guide rejects the topic outright before work begins, you can switch to a different project or stop with nothing further owed.
- Will another student at my college submit the same project?
- No. Each listing is capped to a limited number of students per college per academic year, and the Mentored tier varies one module — the dataset, the domain, or a feature — so two builds are never identical.
- Who actually builds and teaches this?
- Yaseen Khatib — a Senior Full-Stack AI Engineer. The same person writes the code and runs the sessions, so every answer in your viva prep comes from whoever wrote the line you are asked about.