This repository contains a small learning project created to familiarise myself with YOLO-based object detection and the general workflow involved in training a model on a custom dataset.
Most of the experimentation and training for this project was carried out using Google Colab.
Train a model for object detection using a custom dataset. Work with annotated datasets and udo manual annotation. Learn how datasets,training, and inference fit together.
Using YOLO for object detection Training a model on multiple classes Running inference on sample images Basic structure for ML projects
Python
YOLO (Ultralytics)
OpenCV
This project was created by following and experimenting with the YOLO training workflow demonstrated in the following notebook:
- Train and Deploy YOLO Models – EdjeElectronics
https://github.com/EdjeElectronics/Train-and-Deploy-YOLO-Models
The notebook was used as a learning guide and adapted for a custom candy dataset.