---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 14474596.43478261
    num_examples: 20
  download_size: 18278418
  dataset_size: 18275448
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: apache-2.0
language:
- en
task_categories:
- object-detection
tags:
- objectDetection
- ComputerVision
- vision
- synthetic
- syntheticData
- Yolo
- YOLOv8
- multiclass
- multiclassobjectdetection
- training
- free
size_categories:
- 1K<n<10K
---
# DATASET SAMPLE

[Duality.ai ](https://www.duality.ai/edu) just released a 1000 image dataset used to train a YOLOv8 model in multiclass object detection -- and it's 100% free!

Just [create an EDU account here](https://falcon.duality.ai/auth/sign-up). 

This HuggingFace dataset is a 20 image and label sample, but you can get the rest at no cost by [creating a FalconCloud account](https://falcon.duality.ai/auth/sign-up). Once you verify your email, the link will redirect you to the dataset page.

What makes this dataset unique, useful, and capable of bridging the Sim2Real gap?
- The digital twins are not generated by AI, but instead crafted by 3D artists to be INDISTINGUISHABLE to the model from the physical-world objects. This allows the training from this data to transfer into real-world applicability
- The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more. This enables robust model training.
- The labels are created along with the data. This not only saves large amounts of time, but also ensures the labels are incredibly accurate and reliable.


![image/png](https://cdn-uploads.huggingface.co/production/uploads/66c8dc99951843ca6762fe02/08ehub3yPYozSzxNFtVIx.png)
# Dataset Structure
The dataset has the following structure:
```plaintext
Multiclass Object Detection Dataset/
|-- images/
|   |-- 000000000.png
|   |-- 000000001.png
|   |-- ...
|-- labels/
|   |-- 000000000.txt
|   |-- 000000001.txt
|   |-- ...
```

### Components
1. **Images**: RGB images of the object in `.png` format.
2. **Labels**: Text files (`.txt`) containing bounding box annotations for each class
    - 0 = cheerios
    - 1 = soup

## Licensing
license: apache-2.0