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✋ Deep Gesture

Industrial-Grade Gesture Control Engine for macOS

Deep Gesture is a high-performance computer vision engine that transforms a standard webcam into a precision neural pointing device. Built from the ground up for the hackathon stage, it moves beyond simple point-tracking by implementing a custom Deep Neural Network (MLP) trained on 65-dimensional geometric invariants.

DEEPGESTURE://NEURAL_LINK v6.0 -- SYSTEM ONLINE


🚀 Key Features

  • Deep ML Engine: A 4-layer MLP (128-64-32) implemented in pure NumPy, featuring Leaky ReLU activation and L2 regularization.
  • Precision Tracking: Uses a 65-d feature vector (finger angles, inter-tip gaps, and palm distances) for ultra-stable, rotation-invariant control.
  • Aggressive Training: Built-in training pipeline with 200x synthetic data augmentation and 1000-epoch gradient-stabilized optimization.
  • Cyberpunk Neon HUD: A hardware-accelerated, gesture-reactive UI that provides real-time feedback with zero latency.
  • Industrial Architecture: Decoupled design with support for headless operation and live camera switching (FaceTime HD vs. Continuity Camera).

🎮 Control Scheme

Gesture Action Description
2 Fingers (Index+Mid) Move Pointer Midpoint-based tracking with 1-Euro smoothing.
1 Finger (Index Tap) Left Click Immediate "air tap" to select applications or buttons.
4 Fingers (Palm) Right Click Brief pose triggers a standard context menu click.
4 Fingers + Motion Swipe Fast horizontal motion switches Spaces or Tabs.
Fist Hold / Drag Closes hand to grab; opens hand to release/drop.

🛠️ Technical Stack

  • Vision: MediaPipe Tasks API (Hand Landmarker)
  • Engine: NumPy (Deep MLP + Linear Algebra)
  • Input Synthesis: PyAutoGUI + Native macOS Automation
  • UI: OpenCV + Neon HUD Animation Layer
  • Environment: Python 3.9+

⚡ Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Launch the Engine

python3 virtual_mouse.py

3. Industrial Training (Highly Recommended)

Since the engine uses high-dimensional geometric features, we recommend a 30-second "Baking" session for your specific hand:

  1. Press t to enter training mode.
  2. Hold a unique pose and press 1 repeatedly (capture 10-20 angles).
  3. Press t again to trigger the 1000-epoch Industrial Training cycle.
  4. The model is now custom-fitted to your hand with 200x synthetic augmentation.

📐 Accuracy Engineering

Deep Gesture minimizes false positives through Temporal Consensus (Voting). The engine maintains a sliding window of predictions and requires a 3/5 majority consensus before any action is fired on the OS bus. This eliminates "flicker" and accidental triggers.


🔗 Repository

https://github.com/saitarrun/DeepGesture

Built with ❤️ for the Hackathon.

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Industrial-grade macOS gesture control engine. Features a custom NumPy-based Deep Neural Network (MLP), 60-dimensional geometric feature engineering, and a hardware-accelerated HUD.

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