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AkashChitti/memesight has 49 GitHub stars and 11 forks. GitHot measured 0 stars in 24 hours and 0 in 7 days. Last checked 2026-11-10 03:37 UTC. Last push 2026-10-26.

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A real-time computer vision system built with Python, MediaPipe, and OpenCV that tracks facial expressions and hand gestures to trigger instant meme reactions.

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README.md

Original

MemeSight AI — Real-Time Gesture-Controlled Meme Engine

MemeSight AI is an interactive computer-vision application that tracks facial expressions and hand gestures in real time using your webcam, instantly triggering contextual memes (GIFs, videos, or images) based on your live reactions.

Powered by MediaPipe, OpenCV, and Python, MemeSight AI brings computer vision and real-time interaction together into a seamless split-screen experience.

Key Features

Face Gesture Tracking

Tracks up to 468 facial mesh landmarks to trigger instant media responses:

Gesture Movement / Trigger Description Triggered Meme
Tongue Out + Head Shake Sideways head oscillation while sticking tongue out freaky-orca.gif
Head Nod Rapid vertical head movement ishowspeed.gif
Idle Stare Neutral face looking directly at camera monkeytruth.jpg

Hand Gesture Recognition

Tracks 21 key points per hand to recognize multi-hand dynamics:

Gesture Movement / Trigger Description Triggered Meme
Palms Rubbing Rapid horizontal oscillation with close proximity freaky-sonic.mp4
Hands on Head Dual hand placement near top of head ("Oh no" reaction) ishowspeed-wow.gif
Index Up Raised index finger gesture monkeyrealize.jpeg
Hand on Chin Hand proximity to chin / thinking stance monkeythink.jpg
Thumbs Up Positive thumb elevation gesture thumbsupmonkey.png

System Architecture & How It Works

+-----------------------------------+-----------------------------------+
|            Webcam Feed            |      Dynamic Meme / Reaction      |
|    (MediaPipe Mesh Overlay)       |       (GIF / Video / Image)       |
+-----------------------------------+-----------------------------------+
  1. MediaPipe FaceMesh: Evaluates 468 3D facial landmarks for mouth open ratio, eye direction, and head pose angles.
  2. MediaPipe Hands: Tracks 21 3D hand landmarks per hand to compute spatial proximity, finger extension, and rapid hand convergence.
  3. OpenCV Rendering: Captures webcam frames, processes dual inputs, and renders split-screen synchronized video playback.
  4. Custom Gesture Priority Engine: Built-in cooldown, gesture persistence verification, and priority queuing prevent erratic meme switching.

📂 Project Structure

memesight/
├── memesight.py           # Main application loop & gesture engine
├── README.md              # Project documentation
└── memes/                 # Reaction media directory
    ├── freaky-orca.gif
    ├── freaky-sonic.mp4
    ├── ishowspeed.gif
    ├── ishowSpeed-wow.gif
    ├── monkeyrealize.jpeg
    ├── monkeythink.jpg
    ├── monkeytruth.jpg
    └── thumbsupmonkey.png

Quick Start

1️⃣ Clone the Repository

git clone https://github.com/AkashChitti/memesight.git
cd memesight

2️⃣ Install Dependencies

pip install opencv-python mediapipe pillow numpy

(If on older OpenCV versions, install pip install opencv-contrib-python)

3️⃣ Run MemeSight AI

python memesight.py

Note: Ensure your webcam is enabled. Perform gestures in clear lighting for optimal tracking!

Customization

MemeSight AI is built modularly, making it easy to extend:

  • Add Gestures: Define new landmark logic in memesight.py.
  • Custom Meme Packs: Drop your own .gif, .mp4, or .jpg files into /memes/ and update filepath mapping.
  • Sensitivity Tweaks: Adjust cooldown thresholds and landmark distance tolerances in the configuration section.

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests for:

  • Additional face/hand gestures
  • Audio feedback / sound effects
  • Custom GUI interface
  • Multi-person tracking support

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