🎯 Object Detection on ESP32-CAM using Python and YOLO

📌 Overview

This project demonstrates a lightweight real-time object detection system using Python and OpenCV on a PC, combined with an ESP32-CAM IoT device. The ESP32-CAM captures images and sends them to the host system, where Python and a YOLO model detect and label objects.

🔧 Technologies Used

• 🐍 Python 3
• 📷 OpenCV (cv2)
• 🧠 YOLOv8 (or YOLOv5)
• 🤖 ESP32-CAM (Arduino IDE for flashing)
• 📡 Serial and Wi-Fi communication (we can use both for image transfer)

💡 How It Works

1. The ESP32-CAM captures an image either on boot or on-demand.
2. The image is transferred to the computer (via serial or Wi-Fi).
3. Python script processes the image using OpenCV and YOLO.
4. Detected objects are labeled and displayed or stored.

📦 Project Goals

• Enable low-cost IoT vision systems using ESP32-CAM.
• Perform object detection without cloud dependency.
• Explore the edge-AI potential of embedded + PC-based hybrid solutions.

🚀 Future Scope

• Automate alerts or actions based on detected objects.
• Integrate with a small display or speaker for real-time feedback.
• Expand to motion detection or face recognition.