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DATASET SAMPLE

Duality.ai 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.

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.

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

Dataset Structure

The dataset has the following structure:

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

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