Hand Gesture Recognition - Deep Learning Project.

🎯 Goal

Recognize hand gestures using state-of-the-art neural networks to control smart TVs without a remote.

🔍 Problem Statement

As a data scientist at a home electronics company, your mission is to develop an innovative feature for smart TVs that recognizes five distinct hand gestures, enabling users to control their TV without a remote.

🖐️ Gestures and Commands:

• 👍 Thumbs up: Increase volume
• 👎 Thumbs down: Decrease volume
• 👈 Left swipe: Jump backwards 10 seconds
• 👉 Right swipe: Jump forward 10 seconds
• ✋ Stop: Pause the movie

Each gesture is captured as a sequence of 30 frames by a webcam mounted on the TV.

📊 Dataset

• Training data: Hundreds of categorized videos
• Video length: 2-3 seconds
• Frame sequence: 30 frames per video
• Recorded by: Various individuals performing gestures
• Data structure: 'train' and 'val' folders with corresponding CSV files
• Video dimensions: 360x360 or 120x160

Download Dataset

🚀 Challenge

Train a model on the 'train' folder that performs well on the 'val' folder.

🛠️ Technologies Used

• Python
• TensorFlow / PyTorch
• OpenCV
• Numpy
• Pandas

🚀 Getting Started

1. Clone this repository
2. Download and extract the dataset
3. Install required dependencies
4. Run the Jupyter notebook or Python scripts