CineMood AI — Emotion-Based Movie Recommendation System with DeepFace Facial Recognition
AI-powered movie recommendation engine that detects your real-time facial emotions using DeepFace and curates perfect films based on your mood. Complete Django project with webcam integration, 84+ curated films, and privacy-first design.
Technology Used
Python 3.10+ | Django 4.1+ | DeepFace | OpenCV (cv2) | NumPy | tf-keras | HTML5 | CSS3 | Vanilla JavaScript | WebRTC | SQLite3 | Google Fonts
CineMood AI — Where Feelings Meet Films
CineMood is a cutting-edge AI-powered movie recommendation system that revolutionizes how users discover films. By leveraging DeepFace facial emotion recognition technology, this intelligent application reads your real-time facial expressions through your webcam and curates personalized film recommendations tailored to your current emotional state. The entire emotion detection and recommendation process completes in under 15 seconds.
Quick Stats
- 7 Emotions Detected: Angry, Disgusted, Fearful, Sad, Happy, Surprised, Neutral
- 84+ Curated Films: 12 hand-picked movies for each emotion
- Zero Data Storage: Complete privacy — no biometric data stored
- Processing Time: Under 15 seconds per scan
Key Features
AI-Powered Emotion Detection
- Real-time Facial Analysis: DeepFace AI reads 10 frames of your face to determine dominant emotion
- Live Confidence Bars: Visual representation of all 7 emotion scores updating in real-time
- Scan Animation: Professional scanner overlay with corner brackets and animated scan line
- Emotion History Log: Live feed displaying every emotion reading captured during the scan
Smart Movie Recommendations
- Emotion-to-Genre Mapping: Intelligent algorithm matches emotions to appropriate film genres
- Movie Cards: Beautiful structured cards with title, year, IMDb rating, genre, description, and direct IMDb links
- Personal Watchlist: Save favorite films to local-storage watchlist with slide-out drawer
- Genre Filter: Filter recommendations by film genre on the movies page
- Share Functionality: Copy shareable movie descriptions to clipboard
Premium UI/UX Design
- Cinematic Dark Theme: Glassmorphism cards with gradient text effects
- Animated Starfield: Immersive background animation on landing page
- Scroll Reveal Animations: Smooth entrance animations on all sections
- Fully Responsive: Optimized for desktop, tablet, and mobile devices
- 5 Complete Pages: Home, Camera, Movies, About, and Contact
Privacy-First Architecture
- No Biometric Storage: Camera frames processed and immediately discarded
- No External Uploads: All analysis runs locally via Django backend
- No Account Required: Watchlist stored only in browser localStorage
- Camera Auto-Release: Stream stopped immediately after 10 readings complete
Emotion → Genre Mapping Philosophy
| Emotion | Recommended Genre | Philosophy |
|---|---|---|
| 😠 Angry | Comedy | Laugh it off |
| 🤢 Disgusted | Animation / Family | Feel pure joy |
| 😨 Fearful | Musical / Comedy | Lighten the mood |
| 😢 Sad | Romance / Drama | Feel the feels |
| 😄 Happy | Thriller / Horror | Channel the energy |
| 😮 Surprised | Action / Sci-Fi | Keep the adrenaline going |
| 😐 Neutral | Award Winners | The greatest films ever made |
Application Pages
Home Page
Cinematic landing page with animated starfield, feature showcase, and emotion cards
Camera Page
Live emotion scanner with confidence bars, scan animation, emotion log, and circular progress
Movies Page
Film card grid with ratings, genres, descriptions, watchlist, genre filter, and IMDb links
About Page
Full tech stack, process timeline, privacy policy, and how-it-works breakdown
Contact Page
Contact form with validation, FAQ accordion, and social media links
Perfect For
- Computer Science Students: Final year projects, semester projects, and capstone submissions
- AI/ML Enthusiasts: Learn facial recognition and recommendation systems
- Web Developers: Full-stack Django project with modern frontend
- Portfolio Builders: Stand out with unique AI-powered applications
- Researchers: Base for emotion-based recommendation research
- Startups: MVP for entertainment and mood-based services
Learning Outcomes
By studying and implementing this project, you'll gain hands-on experience with:
- DeepFace facial emotion recognition library
- OpenCV computer vision operations
- Django web framework architecture
- WebRTC camera access in browsers
- RESTful API design and implementation
- Local storage and session management
- Responsive CSS and JavaScript animations
- Privacy-first application design
Frequently Asked Questions
Extra Add-Ons Available – Elevate Your Project
Add any of these professional upgrades to save time and impress your evaluators.
Live 1-on-1 Mentorship
Personal session with an expert developer
Project Setup
We'll install and configure the project on your PC via remote session (Google Meet, Zoom, or AnyDesk).
Source Code Explanation
1-hour live session to explain logic, flow, database design, and key features.
Want to know exactly how the setup works? Review our detailed step-by-step process before scheduling your session.
₹999
Custom Documents (College-Tailored)
- Custom Project Report: ₹1,500
- Custom Research Paper: ₹1,000
- Custom PPT: ₹800
Fully customized to match your college format, guidelines, and submission standards.
Project Modification
Need feature changes, UI updates, or new features added?
Charges vary based on complexity.
We'll review your request and provide a clear quote before starting work.
Project Files
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