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Artificial Intelligence · Mini Project
Smile-Triggered Selfie Camera
Takes the photo automatically the moment you smile
1-2 weeks build
Overview
A desktop camera app that watches the webcam, measures the smile from mouth landmarks and snaps a photo once the smile holds for a moment. A short countdown avoids blurry captures, and a gallery shows saved shots. The report compares the landmark approach with a small smile classifier trained on the public GENKI-4K dataset.
What makes it stand up
- 01Smile score from mouth width and lip landmarks
- 02Hold-to-capture timing so half-smiles do not fire
- 03Countdown overlay and shutter sound
- 04Gallery of captured selfies with timestamps
- 05Landmark rule compared with a trained classifier
Module breakdown
- 01
Camera loop
Webcam capture and face landmark tracking.
- 02
Smile metric
Mouth ratios with per-user calibration.
- 03
Trigger
Hold timer, countdown and capture.
- 04
Gallery
Tkinter viewer for saved photos.
- 05
Comparison
Classifier trained on GENKI-4K versus the rule.
After this, you will be able to
- Explain how face landmarks measure a smile
- Defend your trigger timing against false captures
- Demo a selfie captured by smiling at the webcam
Technology stack
- Python
- OpenCV
- MediaPipe
- Tkinter
- Level
- Mini Project
- Domain
- Artificial Intelligence
- Build time
- 1-2 weeks
- Difficulty
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support