Dirt in paint Image Classification Dataset
5+ labeled dirt in paint 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.
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Our B2B team can deliver a licensed, commercial-ready version of this dataset — with custom labels, QA, and annotation formats.
Browse a selection of samples from the Dirt in paint image dataset.
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Dirt in paint 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.