{"url":"/dataset/new-plant-diseases-dataset","name":"New Plant Diseases Dataset","full_name":"Image dataset containing different healthy and unhealthy crop leaves.","description_markdown":"This dataset is recreated using offline augmentation from the original dataset. The original dataset can be found on this github repo. This dataset consists of about 87K rgb images of healthy and diseased crop leaves which is categorized into 38 different classes. The total dataset is divided into 80/20 ratio of training and validation set preserving the directory structure. A new directory containing 33 test images is created later for prediction purpose.","description_withheld":null,"homepage":"https://www.kaggle.com/datasets/kaustubhb999/tomatoleaf","introduced_date":"2022-05-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/meta-heuristic-based-deep-learning-model-for","title":"Meta-Heuristic Based Deep Learning Model for Leaf Diseases Detection.","first_author":"J. Anitha Ruth","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Fine-Grained Visual Recognition","url":"/task/fine-grained-visual-recognition","datasets_with_task":"/datasets/task/fine-grained-visual-recognition"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["New Plant Diseases Dataset"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/fine-grained-visual-recognition-on-new-plant","task":"Fine-Grained Visual Recognition","dataset_variant":"New Plant Diseases Dataset","rows":1,"metrics":["Accuracy (% )"],"first_row_in_archive_order":{"model":"Selfsynthx","paper":"/paper/enhancing-cognition-and-explainability-of","metrics":{"Accuracy (% )":"97.16"},"code_links":[{"title":"sycny/selfsynthx","url":"https://github.com/sycny/selfsynthx"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/image-classification-on-new-plant-diseases","task":"Image Classification","dataset_variant":"New Plant Diseases Dataset","rows":0,"metrics":["Accuracy"],"first_row_in_archive_order":null,"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/enhancing-cognition-and-explainability-of","title":"Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data","date":"2025-02-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":1,"samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":1,"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."}