CineMood AI — Emotion-Based Movie Recommendation System with DeepFace Facial Recognition

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

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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

Extra Add-Ons Available – Elevate Your Project

Add any of these professional upgrades to save time and impress your evaluators.

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.

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Custom Documents (College-Tailored)

  • Custom Project Report: ₹1,200
  • Custom Research Paper: ₹1000
  • Custom PPT: ₹500

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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  • Documentation
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