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Dataset Card for Linnaeus 5
Dataset Details
Dataset Description
Linnaeus 5 dataset contains RGB images (256x256) for classification across 5 categories: berry, bird, dog, flower, and other (negative set). It includes 1200 training images and 400 test images per class.
Dataset Sources
- Homepage: https://chaladze.com/l5/
- Paper: Chaladze, G., & Kalatozishvili, L. (2017). Linnaeus 5 dataset for machine learning. arXiv preprint arXiv:1707.06677.
Dataset Structure
Total images: 8,000
Classes: 5 categories
Splits:
Train: 6,000 images
Test: 2,000 images
Image specs: JPEG format, 256×256 pixels, RGB
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/linnaeus5", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/linnaeus5", split="test", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@article{chaladze2017linnaeus, title={Linnaeus 5 dataset for machine learning}, author={Chaladze, G and Kalatozishvili, L}, journal={arXiv preprint arXiv:1707.06677}, year={2017} }