Scuba Cat Gesture Detector 🐱

A real-time gesture detection application that captures camera feed and plays the scuba cat meme when you perform the scuba cat gesture!

Features

• Real-time gesture detection using MediaPipe hand tracking
• Automatic video playback when gesture is detected
• Gesture recognition for scuba cat movement (left hand on face + right hand scooping motion)
• Webcam integration with live feedback
• Cooldown system to prevent multiple rapid triggers

Requirements

• Python 3.8+
• Webcam/Camera
• Scuba cat meme video file (MP4, AVI, MOV, or MKV)

Installation

1. Clone or download this project

2. Install required dependencies:

pip install -r requirements.txt

3. Add your scuba cat meme video:
   • Place your video file in the assets/ folder
   • Name it scuba_cat.mp4 (or edit main.py line 13 with your filename)

Usage

1. Run the application:

python main.py

2. Perform the scuba cat gesture:

   • Put your LEFT hand near your mouth/face area
   • Move your RIGHT hand in a scooping motion
   • Hold the gesture for about 0.3 seconds
   • The scuba cat meme will play!

3. Controls:

   • Press q to quit the application
   • Press p to manually play the video (for testing)

Project Structure

scuba cat/
├── main.py                   # Main application
├── gesture_detector.py       # Hand gesture detection logic
├── video_player.py           # Video playback handler
├── requirements.txt          # Python dependencies
├── README.md                 # This file
└── assets/
    └── scuba_cat.mp4        # Your scuba cat meme video (add this)

How It Works

Gesture Detection Algorithm

The gesture detector uses Google's MediaPipe library to track hand positions in real-time:

1. Left Hand Detection: Checks if left hand is in the face/mouth region
2. Right Hand Movement: Detects motion in the right hand (scooping gesture)
3. Confirmation: Requires the gesture to be held for ~10 frames (~0.3 seconds) before triggering
4. Cooldown: Prevents multiple rapid triggers (2-second cooldown)

System Components

• GestureDetector: Analyzes hand landmarks to identify the scuba cat gesture
• VideoPlayer: Handles video playback in a separate thread for smooth operation
• Main Loop: Captures camera frames, detects gestures, and manages UI

Troubleshooting

Camera not detected

• Check that your webcam is connected and working
• Try changing CAMERA_INDEX in main.py (0 for default, 1, 2, etc. for other cameras)

Gesture not detected

• Ensure good lighting conditions
• The detector works best with clear hand visibility
• Try adjusting the min_detection_confidence in gesture_detector.py (line 14)
• Lower values = more sensitive but less accurate

Video not playing

• Verify the video file exists in assets/ folder
• Check the file format (MP4, AVI, MOV, MKV supported)
• Try using a different video format or converting it

Performance issues

• Reduce camera resolution in main.py
• Comment out the landmark drawing line for better performance
• Close other applications consuming CPU/GPU

Customization

Change the gesture

Edit the detect_scuba_cat_gesture() method in gesture_detector.py to detect different hand movements

Adjust sensitivity

• required_frames in GestureDetector.__init__(): How long gesture must be held (default: 10 frames)
• cooldown_frames in main.py: Delay between consecutive triggers (default: 60 frames)
• min_detection_confidence in gesture_detector.py: Hand detection confidence threshold (0-1)

Use different video

Update VIDEO_PATH in main.py to point to your custom video file

Tips for Best Results

1. Lighting: Good lighting helps hand detection
2. Distance: Keep hands 1-2 feet from camera
3. Movement: Make smooth, deliberate gestures
4. Patience: The gesture needs to be held for a moment (~0.3 seconds)

Credits

• Hand detection: MediaPipe
• Video playback: OpenCV

License

Free to use and modify for personal projects.