Deploy a Real‑Time Object Detection API with YOLOv8 & FastAPI

📰 Dev.to · Lich Priest

Learn to deploy a real-time object detection API using YOLOv8 and FastAPI for low-latency predictions

intermediate Published 11 May 2026

Action Steps

Train a custom YOLOv8 model using your dataset
Containerize the model with Docker for easy deployment
Create a FastAPI endpoint to serve low-latency predictions
Test the API with sample images to verify its functionality
Deploy the API to a cloud platform or server for real-time object detection

Who Needs to Know This

This tutorial benefits machine learning engineers and software developers who want to deploy AI models as APIs, and DevOps teams who need to containerize and serve models efficiently

Key Insight

💡 YOLOv8 and FastAPI can be used together to create a low-latency object detection API