🖥️ Open Source Visual Computing Project

Welcome to our open-source project! 🚀 This repository was created to encourage collaborative development of a system based on Visual Computing, using Python and some of the main libraries for image processing and graphical interfaces.

📌 Project Objective

Our goal is to develop a robust system that utilizes Computer Vision, Visual Computing, and other technologies for various applications. This project is in its early stages and will evolve with community contributions. Any help is welcome! 🤝

🔍 Use Case

🔍 Use Case

Imagine this scenario: your colleagues leave the office at 1 PM on Monday, and when they return on Tuesday morning, they find the office completely empty because it was robbed. Or perhaps someone accidentally left the coffee machine on, causing a short circuit that burned down the entire office.

These situations could be avoided with a system that connects to any camera and instantly sends an alert message to a WhatsApp group when a change is detected.

This project allows real-time monitoring and can run on a local machine (computer) using a simple webcam.

🛠️ Technologies and Libraries Used

The project is developed in Python and utilizes the following libraries:

• opencv-python - Library for image processing and computer vision.
• opencv-python-headless - Optimized version for environments without a GUI.
• numpy - Library for numerical operations and array manipulation.
• tk - Toolkit for building graphical interfaces.

🚀 How to Run the Project

To run this project locally, follow these steps:

1️⃣ Clone the Repository

 git clone https://github.com/chutzpah-os/image_detection.git
 cd image_detection

2️⃣ Create a Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate  # Linux/macOS
venv\Scripts\activate  # Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the Project

cd ./src
python main.py

cd ./whatsapp_sender 
python monitorar_whatsapp.py

💡 How to Contribute

Want to contribute? Follow these steps:

1. Fork the repository 🍴
2. Create a new branch for your feature or fix 🛠️

   git checkout -b my-new-feature

3. Make changes and commit 📝

   git commit -m "Added a new feature X"

4. Push to your fork 🚀

   git push origin my-new-feature

5. Open a Pull Request ✅

📝 Roadmap and Next Steps

• Improve the graphical interface
• Implement new computer vision algorithms
• Add support for new image formats
• Create detailed documentation for new developers

📜 License

This project is open-source and distributed under the MIT license. Feel free to use, modify, and distribute it!

📢 Contact

Have questions or suggestions? Get in touch or open an issue! 💬

📧 Email: [email protected]
🐙 GitHub: Haniel Rolemberg

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Let's build something amazing together! 🚀🔥