duality-robotics/YOLOv8-Object-Detection-02-Dataset

Soup Can Object Detection Dataset Sample

Duality.ai just released a 1000 image dataset used to train a YOLOv8 model for object detection -- and it's 100% free!

Just create an EDU account here.

This HuggingFace dataset is a 20 image and label sample, but you can get the rest at no cost by creating a FalconCloud account. Once you verify your email, the link will redirect you to the dataset page.

Dataset Overview

This dataset consists of high-quality images of soup cans captured in various poses and lighting conditions .This dataset is structured to train and test object detection models, specifically YOLO-based and other object detection frameworks.

Why Use This Dataset?

• —Single Object Detection: Specifically curated for detecting soup cans, making it ideal for fine-tuning models for retail, inventory management, or robotics applications.

• —Varied Environments: The dataset contains images with different lighting conditions, poses, and occlusions to help solve traditional recall problems in real world object detection.

• —Accurate Annotations: Bounding box annotations are precise and automatically labeled in YOLO format as the data is created. Create your own specialized data! You can create a dataset like this but with a digital twin of your choosing! Create an account and follow this tutorial to learn how.

Dataset Structure

The dataset is organized as follows:

Object Detection Dataset 02/
|-- images/
|   |-- 000000000.png
|   |-- 000000001.png
|   |-- ...
|-- labels/
|   |-- 000000000.txt
|   |-- 000000001.txt
|   |-- ...

Components

Images: RGB images of the object in .png format.

Labels: Text files (.txt) containing bounding box annotations for each class:

• —0 = soup

Example Annotation (YOLO Format):

0 0.475 0.554 0.050 0.050

• —0 represents the object class (soup can).
• —The next four values represent the bounding box coordinates (normalized xcenter, ycenter, width, height).

Usage

This dataset is designed to be used with popular deep learning frameworks. Run these commands:

from datasets import load_dataset

dataset = load_dataset("your-huggingface-username/YOLOv8-Object-Detection-02-Dataset")

To train a YOLOv8 model, you can use Ultralytics' yolo package:

yolo train model=yolov8n.pt data=soup_can.yaml epochs=50 imgsz=640

Licensing License: Apache 2.0 Attribution: If you use this dataset in research or commercial projects, please provide appropriate credit.