license: mit
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: objects
sequence:
- name: bbox
sequence: float64
- name: category
dtype: string
splits:
- name: train
num_bytes: 7697416830.254
num_examples: 2418
download_size: 6432490239
dataset_size: 7697416830.254
Dataset Card for IBBI Out-of-Distribution (OOD) Dataset
Dataset Summary
This dataset contains out-of-distribution (OOD) images of bark and ambrosia beetles, intended for evaluating the robustness and generalization capabilities of models from the ibbi Python package. The 121 species included in this dataset were not part of the original training or in-distribution test sets used for the ibbi package models.
This dataset is crucial for testing how well models can:
- Reject unknown classes (for multi-class classifiers) by assigning low confidence scores.
- Generalize detection to beetle species they have not been explicitly trained on (for single-class detectors).
The dataset can be loaded directly using the ibbi package:
import ibbi
ood_dataset = ibbi.get_dataset(repo_id="IBBI-bio/ibbi_ood_dataset")
Supported Tasks
- Out-of-Distribution Detection: The primary purpose is to evaluate how models respond to unseen species.
- Object Detection: Can be used to benchmark the generalization performance of beetle detectors.
Dataset Structure
Data Instances
Each instance in the dataset consists of an image and a corresponding set of object annotations.
Example:
{
"image": "<PIL.Image.Image image>",
"objects": {
"bbox": [
[656.56, 1335.47, 80.53, 75.35]
],
"category": [
"Dendroctonus_frontalis"
]
}
}
Data Fields
image: A PIL Image object of a beetle specimen.objects: A dictionary containing the annotation information for the image.bbox: A list of bounding boxes. Each box is in the format[x_min, y_min, width, height].category: A list of string labels corresponding to the species in each bounding box.
Data Splits
The dataset contains a single split, named train for compatibility with Hugging Face's default structure. This split serves as the official out-of-distribution evaluation set.
train: 2,880 images.
Dataset Statistics
| Metric | Value |
|---|---|
| Total Images | 2,880 |
| Unique Species | 121 |
| Total Bounding Box Annotations | 12,884 |
| Average Bboxes per Image | 5.33 |
| Average Image Dimensions (WxH) | 2146 x 1702 |
| Species | Annotation Count |
|---|---|
| Pseudopityophthorus_minutissimus | 1220 |
| Dactylotrypes_longicollis | 1090 |
| Carphoborus_bifurcus | 1077 |
| Scolytus_rugulosus | 867 |
| Hypothenemus_seriatus | 840 |
| Anisandrus_maiche | 643 |
| Scolytus_carpini | 620 |
| Cryphalus_mangiferae | 612 |
| Eidophelus_fagi | 611 |
| Cryptocarenus_seriatus | 529 |
| Hylurgus_micklitzi | 423 |
| Pityogenes_hopkinsi | 418 |
| Anisandrus_obesus | 363 |
| Pityophthorus_pityographus | 314 |
| Scolytus_intricatus | 284 |
| Dendroctonus_adjunctus | 274 |
| Pityogenes_japonicus | 218 |
| Ernoporus_tiliae | 213 |
| Hylocurus_langstoni | 169 |
| Tomicus_brevipilosus | 72 |
| Xyleborus_monographus | 58 |
| Tomicus_piniperda | 51 |
| Trypodendron_lineatum | 50 |
| Dendroctonus_frontalis | 44 |
| Xyleborus_bispinatus | 41 |
| Xylocleptes_bispinus | 39 |
| Trypodendron_signatum | 38 |
| Hypothenemus_eruditus | 38 |
| Polygraphus_poligraphus | 36 |
| Hypothenemus_birmanus | 36 |
| Ambrosiodmus_rubricollis | 35 |
| Chaetoptelius_mundulus | 34 |
| Xyleborus_perforans | 34 |
| Euwallacea_kuroshio | 33 |
| Xyleborus_volvulus | 32 |
| Hylastes_ater | 31 |
| Xyleborinus_andrewesi | 29 |
| Euwallacea_interjectus | 29 |
| Xyloterinus_politus | 28 |
| Xyleborus_pubescens | 28 |
| Gnathotrichus_materiarius | 27 |
| Dendroctonus_ponderosae | 25 |
| Xyleborinus_attenuatus | 25 |
| Ambrosiodmus_lewisi | 24 |
| Cyclorhipidion_bodoanum | 23 |
| Xyleborus_horridus | 23 |
| Hylastes_gracilis | 22 |
| Crossotarsus_mnizsechi | 22 |
| Ips_pini | 22 |
| Xyleborinus_schaufussi | 21 |
| Premnobius_cavipennis | 21 |
| Xyleborinus_gracilis | 20 |
| Xyleborinus_artestriatus | 19 |
| Stegomerus_pygmaeus | 19 |
| Truncaudum_agnatum | 19 |
| Euwallacea_funereus | 18 |
| Dinoplatypus_pallidus | 18 |
| Scolytus_ratzeburgi | 18 |
| Euwallacea_wallacei | 18 |
| Dryocoetes_confusus | 18 |
| Pityoborus_comatus | 18 |
| Eccoptopterus_spinosus | 18 |
| Euwallacea_similis | 18 |
| Hypothenemus_obscurus | 17 |
| Hypothenemus_dissimilis | 17 |
| Euwallacea_posticus | 17 |
| Diuncus_justus | 17 |
| Xyleborus_spinulosus | 17 |
| Leptoxyleborus_sordicauda | 17 |
| Ambrosiodmus_hagedorni | 16 |
| Hypothenemus_javanus | 16 |
| Microperus_alpha | 16 |
| Cnestus_bimaculatus | 16 |
| Ambrosiodmus_obliquus | 16 |
| Hadrodemius_globus | 16 |
| Webbia_pabo | 15 |
| Monarthrum_lobatum | 15 |
| Dendroterus_defectus | 15 |
| Ambrosiodmus_devexulus | 15 |
| Heteroborips_seriatus | 15 |
| Diuncus_papatrae | 15 |
| Debus_pumilus | 15 |
| Hypothenemus_atomus | 15 |
| Ambrosiodmus_asperatus | 14 |
| Platypus_selysi | 14 |
| Hylastes_cunicularius | 14 |
| Diuncus_haberkorni | 14 |
| Metacorthylus_velutinus | 14 |
| Monarthrum_laterale | 14 |
| Scolytus_mundus | 14 |
| Coptoborus_pseudotenuis | 14 |
| Monarthrum_dentigerum | 14 |
| Coptoborus_coartatus | 14 |
| Scolytus_aztecus | 14 |
| Truncaudum_impexum | 14 |
| Cnesinus_strigicollis | 13 |
| Tricosa_metacuneolus | 13 |
| Procryphalus_mucronatus | 13 |
| Debus_emarginatus | 13 |
| Xyleborus_bidentatus | 13 |
| Xyleborus_impressus | 13 |
| Scolytus_dimidiatus | 13 |
| Ambrosiodmus_tachygraphus | 13 |
| Crypturgus_hispidulus | 13 |
| Carphoborus_bicornis | 13 |
| Hypothenemus_crudiae | 13 |
| Microperus_diversicolor | 13 |
| Dendroctonus_pseudotsugae | 13 |
| Xyleborus_xylographus | 13 |
| Monarthrum_huachucae | 13 |
| Crossotarsus_lacordairei | 12 |
| Xyleborinus_exiguus | 12 |
| Xyleborus_intrusus | 12 |
| Pycnarthrum_hispidum | 12 |
| Microperus_popondettae | 12 |
| Pseudowebbia_trepanicauda | 12 |
| Pseudopityophthorus_pruinosus | 12 |
| Beaverium_insulindicus | 11 |
| Hylastes_tenuis | 11 |
| Wallacellus_piceus | 10 |
| Euwallacea_destruens | 10 |
Dataset Creation
The images and annotations were curated by the Forest Entomology Lab at the University of Florida. Specifically, this dataset is composed of images that were filtered out during the creation of the primary ibbi multi-class training dataset. The species included here are those that had either fewer than 50 total bounding box annotations or were represented by fewer than 50 images, making them ideal for out-of-distribution testing. Bounding boxes and species labels were provided by expert annotators. The data was originally stored in a format with one JSON file per image, detailing the bounding box coordinates and labels for one or more objects.
Citation
If you use this dataset in your research, please cite the associated paper for the ibbi project:
@article{marais2025progress,
title={Progress in developing a bark beetle identification tool},
author={Marais, G Christopher and Stratton, Isabelle C and Johnson, Andrew J and Hulcr, Jiri},
journal={PLoS One},
volume={20},
number={6},
pages={e0310716},
year={2025},
publisher={Public Library of Science San Francisco, CA USA}
}