YOLOv8 Object Detection Pipeline

YOLOv8 Object Detection Pipeline

Description: A real-time object detection system that uses an ESP32 camera to stream frames over Wi-Fi to a Flask server. The server runs a YOLOv8 model (20 classes) to identify objects (e.g., tables, chairs, whiteboards) and logs results for later analysis.

Tech Stack

• Embedded: ESP32 (MicroPython, HTTP POST)
• Backend: Python Flask (REST API, WebSockets)
• ML: YOLOv8 (Ultralytics), PyTorch
• Frontend (Dashboard): React, Chart.js

Features

1. Real-time capture from ESP32 camera module.
2. HTTP POST & WebSocket streaming to Flask server.
3. On-the-fly inference with YOLOv8 (20 custom classes).
4. Dashboard that visualizes detection counts (React + Chart.js).
5. Automated logging to a PostgreSQL database for historical analysis.

Repo & Live Demo

• Source Code: github.com/alimaqsoodahmed/object-detection
• Live Dashboard: https://smart-home-dashboard.example.com (if available)

Screenshots

---

← Back to Projects