Datasets:
| license: cc-by-nc-4.0 | |
| task_categories: | |
| - image-classification | |
| tags: | |
| - plants | |
| - flowers | |
| - inaturalist | |
| - fine-grained | |
| # Botanical Vision | |
| Fine-grained flowering-plant classification dataset: 407,759 research-grade | |
| iNaturalist photos across 4,094 species (all flowering plants with at least | |
| 2,000 observations). Built for Advanced Computer Vision (UChicago ADSP 32023). | |
| ## Splits | |
| | split | images | | |
| |-------|--------| | |
| | train | 285,136 | | |
| | val | 61,288 | | |
| | test | 61,335 | | |
| Split is stratified within each species (70/15/15). Exact and cross-species | |
| duplicate images were removed before splitting. | |
| ## Fields | |
| - `image` — the photo | |
| - `label` / `species` — species name (the classification target) | |
| - `genus`, `family`, `order`, `class` — taxonomy | |
| - `species_key` — GBIF species key | |
| ## Source | |
| Species were selected from a GBIF occurrence download (iNaturalist Research-grade | |
| Observations, flowering plants with still images); photos were pulled from the | |
| iNaturalist API. Individual photos retain their own iNaturalist licenses. | |
| > GBIF.org (8 July 2026) GBIF Occurrence Download https://doi.org/10.15468/dl.3hragg | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("dbabnigg/botanical-vision") | |
| ``` | |