Create YOLO Dataset for Custom Object Detection Using OpenCV, PyTorch, and Python Tutorial

Learn how to create a custom dataset for object detection using YOLOv5 in this comprehensive tutorial. Explore the process of detecting clothing items in images using OpenCV, PyTorch, and Python. Begin by examining the dataset and understanding the YOLO v5 project on GitHub. Set up a Google Colab notebook for hands-on practice. Analyze sample images from the dataset and convert them to the YOLO (darknet) format. Gain insights into the file structure of the custom dataset. Follow along with step-by-step instructions to build your own object detection model for clothing items, complete with source code and a Google Colab notebook for easy implementation.

What are we doing?
Dataset overview - clothing item detection
Look at the YOLO v5 project on GitHub
Google Colab notebook setup
Look at a sample image from the dataset
Convert the dataset to YOLO darknet format
Understanding the file structure of our dataset