Discover the art of Container Damage Detection in Computer Vision. Follow our step-by-step tutorial on training YOLOv8 with a custom dataset. Whether you're a beginner or an expert, this guide takes you from dataset preparation to model evaluation.

Table of Contents

Introduction
Dataset Preparation
Model Training
Evaluation
Demo Results
Discussion & Comments

Introduction

Begin your journey into Container Damage Detection with an engaging introduction to the tutorial.
Dataset Preparation

Learn the essentials of preparing a custom dataset for YOLOv8 training.

Model Training

Walk through each step of training YOLOv8 on your custom dataset for optimal results.

from ultralytics import YOLO
import cv2

model = YOLO("last.pt")

demo = "demo.mp4"

results = model.predict(source=demo, show=True)

source.set(3, 1920)
source.set(4, 1080)

print(results)

Evaluation

Evaluate the trained model and ensure its effectiveness in container damage detection.
Demo Results

Witness the impressive results of your trained YOLOv8 model in action.

Discussion & Comments

Don't miss out on this transformative tutorial – watch now to elevate your skills in Computer Vision!