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224
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has_groot
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Dataset Card: [BabyGroot-Image]

Purpose

This dataset was created for educational purposes as part of a homework assignment.
It is intended to practice building, augmenting, and publishing datasets on the Hugging Face Hub.

Composition

  • Number of samples:
    • Original: N samples
    • Augmented: M samples
  • Features:
    • [list features/columns here, e.g. CarModel, Year, Mileage... or text, complexity_label... or image, has_groot]

Collection

  • Source:
    • Images (Baby Groot): photos taken with a personal camera/phone (no people, no PII).
  • Size:
    • At least 30 original entries

Preprocessing & Augmentation

  • Preprocessing:
    • Images: resized to 224x224, converted to RGB.
  • Augmentation techniques:
    • Images: flips, rotations, affine transforms, perspective, color jitter, Gaussian blur, noise, cutout.

Labels

  • Images: Target = has_groot (binary, yes/no).

Splits

  • original: manually collected data (30+).
  • augmented: synthetic data (≥300 for images).

Intended Use & Limitations

  • Use: Coursework, experimenting with dataset creation, augmentation, and Hugging Face tools.
  • Limits:
    • Not suitable for production ML training.
    • Synthetic samples may not represent real-world distributions.
    • Small dataset sizes → limited generalization.

Ethical Notes

  • No personally identifiable information (PII) or sensitive content.
  • All images are of inanimate objects (a Baby Groot figure + random desk items).
  • Labels are for demonstration purposes only.

License

MIT License (for educational use).

AI Usage Disclosure

  • No generative AI was used to produce original image samples; only augmentation steps.
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