{"url":"/dataset/intel-image-classification","name":"Intel Image Classification","full_name":null,"description_markdown":"Context\r\nThis is image data of Natural Scenes around the world.\r\n\r\nContent\r\nThis Data contains around 25k images of size 150x150 distributed under 6 categories.\r\n{'buildings' -> 0,\r\n'forest' -> 1,\r\n'glacier' -> 2,\r\n'mountain' -> 3,\r\n'sea' -> 4,\r\n'street' -> 5 }\r\n\r\nThe Train, Test and Prediction data is separated in each zip files. There are around 14k images in Train, 3k in Test and 7k in Prediction.\r\nThis data was initially published on https://datahack.analyticsvidhya.com by Intel to host a Image classification Challenge.\r\n\r\nAcknowledgements\r\nThanks to https://datahack.analyticsvidhya.com for the challenge and Intel for the Data\r\n\r\nPhoto by Jan Böttinger on Unsplash\r\n\r\nInspiration\r\nWant to build powerful Neural network that can classify these images with more accuracy.","description_withheld":null,"homepage":"https://www.kaggle.com/puneet6060/intel-image-classification","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Image Augmentation","url":"/task/image-augmentation","datasets_with_task":"/datasets/task/image-augmentation"}],"languages":[],"variants":["Intel Image Classification"],"data_loaders":[{"repo":"https://github.com/luangtatipsy/intel-image-classification","url":"https://github.com/luangtatipsy/intel-image-classification","frameworks":["tf","pytorch"]}],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-classification-on-intel-image","task":"Image Classification","dataset_variant":"Intel Image Classification","rows":2,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"ResNet-18 + Vision Eagle Attention","paper":"/paper/vision-eagle-attention-a-new-lens-for","metrics":{"Accuracy":"92.43"},"code_links":[{"title":"MahmudulHasan11085/Vision-Eagle-Attention","url":"https://github.com/MahmudulHasan11085/Vision-Eagle-Attention"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/image-augmentation-on-intel-image","task":"Image Augmentation","dataset_variant":"Intel Image Classification","rows":1,"metrics":["Balanced Accuracy"],"first_row_in_archive_order":{"model":"Augstatic","paper":"/paper/augstatic-a-light-weight-image-augmentation","metrics":{"Balanced Accuracy":"0"},"code_links":[{"title":"avs-abhishek123/AugStatic","url":"https://github.com/avs-abhishek123/AugStatic"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/vision-eagle-attention-a-new-lens-for","title":"Vision Eagle Attention: a new lens for advancing image classification","date":"2024-11-15","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/augstatic-a-light-weight-image-augmentation","title":"AugStatic - A Light-Weight Image Augmentation Library","date":"2022-05-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}