🎤 Voice Control and 🎯 Computer Vision

📌 Overview

This repository showcases implementations of hand tracking and volume control using computer vision and voice control techniques. The project leverages OpenCV and MediaPipe for real-time hand tracking and gesture recognition.

📂 Contents

🖐 Hand Tracking Module (HandTrackingModule.ipynb)

This Jupyter Notebook provides real-time hand tracking using the MediaPipe library, including: ✅ Detecting hand landmarks in real-time. ✅ Identifying finger positions and gestures. ✅ Visualizing hand tracking results with OpenCV.

🛠 Requirements:

• 🏆 OpenCV (cv2)
• 🔥 MediaPipe (mediapipe)
• ⚡ NumPy (numpy)

🔊 Volume Control with Hand Gestures (VolumeHandcontrol.ipynb)

This Notebook extends the hand tracking module to control system volume using hand gestures: ✅ Detecting hand movements. ✅ Calculating finger distances to adjust volume. ✅ Dynamically controlling system volume.

🛠 Requirements:

• 🎚 pycaw (for audio control)
• 🏆 OpenCV
• 🔥 MediaPipe

📁 Example Files (exemples/)

This directory contains various Python scripts and images for testing and implementing different computer vision functionalities:

📄 PDF File

• 📌 Demande_reservation formation.pdf: Sample PDF for OCR testing.

📝 Python Scripts

• 🏗 exercice.py: Implements an exercise related to image processing.
• 📊 hist.py: Computes and displays an image histogram.
• 🖼 imread_imshow.py: Reads and displays an image using OpenCV.
• 🔍 ocr.py: Performs OCR (Optical Character Recognition) on an image.
• 📜 read.py: Reads and displays an image.
• 🔄 resize.py: Resizes an image with transformations.
• 🖼 seui.py: Applies thresholding techniques to an image and visualizes results.

🖼 Sample Images

• 🖼 im.webp, image.png: Sample images used in the project.

🏗 Installation

To run the notebooks, install the required dependencies using:

pip install opencv-python mediapipe numpy pycaw pytesseract pdf2image

🚀 Usage

1️⃣ Clone the repository:

git clone https://github.com/Code-Crafters-BM/Voice_Controll_And_Computer_Vision.git
cd Voice_Controll_And_Computer_Vision

2️⃣ Open Jupyter Notebook: ( Or navigate on your browerser to google collab : https://colab.research.google.com/ )

jupyter notebook

3️⃣ Run HandTrackingModule.ipynb to test hand tracking. 4️⃣ Run VolumeHandcontrol.ipynb to test volume control.

🤝 Contributors

• Code Crafters Bm – Project development and implementation.

💡 Acknowledgments

• 🎓 Inspired by OpenCV and MediaPipe tutorials.
• 🖥 Based on computer vision techniques for gesture recognition.