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Painted butterfly image dataset preview

Painted butterfly Image Classification Dataset

114 labeled images
Free download
114+ labeled painted butterfly images ready for AI and computer vision research. Delivered as an ImageFolder-style ZIP with train / val / test splits and class-labeled folders. Review the source license before use. Compatible with PyTorch, TensorFlow, Keras, and any classification pipeline.

Download dataset · 114 imagesSupport the project

Browse a selection of samples from the Painted butterfly image dataset.

Sample 1 – Painted butterfly
Sample 2 – Painted butterfly
Sample 3 – Painted butterfly
Sample 4 – Painted butterfly
Sample 5 – Painted butterfly
Sample 6 – Painted butterfly
Sample 7 – Painted butterfly
Sample 8 – Painted butterfly
Sample 9 – Painted butterfly
Sample 10 – Painted butterfly
Sample 11 – Painted butterfly
Sample 12 – Painted butterfly
Sample 13 – Painted butterfly
Sample 14 – Painted butterfly
Sample 15 – Painted butterfly
Sample 16 – Painted butterfly
Sample 17 – Painted butterfly
Sample 18 – Painted butterfly
Sample 19 – Painted butterfly
Sample 20 – Painted butterfly
Sample 21 – Painted butterfly
Sample 22 – Painted butterfly
Sample 23 – Painted butterfly
Sample 24 – Painted butterfly

Categories in this dataset

Painted butterfly

Tags

Painted butterfly labeled image dataset
Painted butterfly photos
Painted butterfly pictures
Painted butterfly images
Painted butterfly dataset
Painted butterfly image dataset

Data sources

What you get

Painted butterfly classification dataset, ready to train

Clean folder layout

`train` / `val` / `test` sub-folders per class plus a `meta.json` with label list, split counts, and ImageNet normalization constants — ready for `torchvision.datasets.ImageFolder`.


Your choices, your ZIP

Pick output size, color mode, train/val/test split, and 20 augmentations. The ZIP is built for your exact setup.


Research-friendly

BibTeX citation per dataset and a Colab starter notebook. No signup required to download.


Framework-agnostic

PyTorch, TensorFlow, Ultralytics — pick any. Standard ImageFolder layout works out of the box.

Ready to train?

Configure the split and augmentations, then grab the ZIP.

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