IBBI-bio/ibbi_test_data

Dataset Card for IBBI Bark Beetle Testing Dataset

Dataset Summary

This dataset is the primary testing and benchmarking set for the ibbi Python package. It contains images of bark and ambrosia beetles used to evaluate the performance of object detection and classification models.

Note: While this dataset serves as the testing set for the ibbi package's evaluation functions, it is hosted on the Hugging Face Hub as the train split. You can access it using ibbi.get_dataset(split='train').

Dataset Summary

The Intelligent Bark Beetle Identifier (IBBI) testing dataset is a curated collection of 2,031 images of bark and ambrosia beetles, covering 63 distinct species. It was developed to provide a standardized benchmark for evaluating the performance of computer vision models on the challenging task of beetle identification. The dataset is specifically designed for evaluating both localization (finding the beetle) and classification (identifying the species) tasks. All images have been annotated by experts.

Supported Tasks and Leaderboards

This dataset is primarily used for evaluating the following tasks within the ibbi package:

• Object Detection: Models are evaluated on their ability to accurately draw bounding boxes around beetles. The primary metric is mean Average Precision (mAP).
• Object Classification: For models that identify species, performance is measured using metrics like F1-score, accuracy, precision, and recall.
• Embedding Quality: The dataset is used to evaluate the quality of feature embeddings generated by models, assessing how well they separate different species in a high-dimensional space using clustering metrics.

Dataset Structure

Data Instances

A typical data instance consists of an image and a corresponding set of object annotations.

{
  'image': <PIL.Image.Image image>,
  'objects': {
    'bbox': [[217.0, 181.0, 526.0, 631.0]],
    'category': ['Xylosandrus_crassiusculus']
  }
}

Data Fields

• image: A PIL Image object containing the image of a beetle specimen.
• objects: A dictionary containing annotation information.
  • bbox: A list of bounding boxes, where each box is in [x_1, y_1, x_2, y_2] format.
  • category: A list of string labels corresponding to the species of the beetle in each bounding box. There are 63 unique species categories in the dataset.

Data Splits

The dataset contains a single split, which is used for testing and evaluation. Although named train on the Hugging Face Hub, it functions as the official test set for the ibbi package.

• Testing set (train split): 2,031 images.

Dataset Statistics

Metric	Value
Total Images	2,031
Unique Species	63
Total Bounding Box Annotations	16,480
Average Bboxes per Image	8.11
Average Image Dimensions (WxH)	2211 x 1891

Species Distribution

Total Object (Annotation) Count per Class

Xylosandrus_compactus : 1136 objects
Euwallacea_fornicatus : 854 objects
Phloeosinus_dentatus : 770 objects
Pityophthorus_juglandis : 745 objects
Xyleborus_affinis : 739 objects
Hylesinus_varius : 725 objects
Xyleborinus_saxesenii : 637 objects
Xyleborus_glabratus : 556 objects
Ips_typographus : 539 objects
Coccotrypes_dactyliperda : 531 objects
Monarthrum_fasciatum : 521 objects
Cryptocarenus_heveae : 502 objects
Platypus_cylindrus : 480 objects
Coccotrypes_carpophagus : 421 objects
Scolytodes_glaber : 417 objects
Xylosandrus_crassiusculus : 399 objects
Euwallacea_perbrevis : 391 objects
Dendroctonus_valens : 344 objects
Ips_duplicatus : 277 objects
Platypus_koryoensis : 264 objects
Ips_acuminatus : 244 objects
Ctonoxylon_hagedorn : 239 objects
Coptoborus_ricini : 239 objects
Euplatypus_compositus : 237 objects
Dendroctonus_terebrans : 235 objects
Ips_sexdentatus : 228 objects
Pagiocerus_frontalis : 225 objects
Hypothenemus_hampei : 224 objects
Pycnarthrum_hispidium : 214 objects
Hylurgops_palliatus : 207 objects
Monarthrum_mali : 199 objects
Anisandrus_sayi : 195 objects
Ips_avulsus : 193 objects
Myoplatypus_flavicornis : 189 objects
Hylesinus_toranio : 181 objects
Xyleborus_ferrugineus : 177 objects
Cnestus_mutilatus : 166 objects
Ips_calligraphus : 151 objects
Orthotomicus_erosus : 129 objects
Hylastes_salebrosus : 127 objects
Xylosandrus_morigerus : 124 objects
Hylurgus_ligniperda : 122 objects
Taphrorychus_bicolor : 111 objects
Hylastes_porculus : 104 objects
Tomicus_destruens : 100 objects
Anisandrus_dispar : 96 objects
Pityogenes_chalcographus : 96 objects
Cyclorhipidion_pelliculosum : 88 objects
Hylesinus_crenatus : 66 objects
Scolytus_schevyrewi : 61 objects
Xylosandrus_amputatus : 61 objects
Xylosandrus_germanus : 50 objects
Ambrosiophilus_atratus : 41 objects
Trypodendron_domesticum : 16 objects
Xyleborus_celsus : 15 objects
Hylesinus_aculeatus : 13 objects
Dryocoetes_autographus : 12 objects
Ambrosiodmus_minor : 11 objects
Dendroctonus_rufipennis : 10 objects
Scolytus_multistriatus : 9 objects
Orthotomicus_caelatus : 9 objects
Ips_grandicollis : 9 objects
Euwallacea_validus : 9 objects

Unique Image Count per Class

Ambrosiodmus_minor : 11 images
Ambrosiophilus_atratus : 11 images
Anisandrus_dispar : 12 images
Anisandrus_sayi : 7 images
Cnestus_mutilatus : 23 images
Coccotrypes_carpophagus : 8 images
Coccotrypes_dactyliperda : 30 images
Coptoborus_ricini : 10 images
Cryptocarenus_heveae : 16 images
Ctonoxylon_hagedorn : 12 images
Cyclorhipidion_pelliculosum : 7 images
Dendroctonus_rufipennis : 9 images
Dendroctonus_terebrans : 46 images
Dendroctonus_valens : 264 images
Dryocoetes_autographus : 8 images
Euplatypus_compositus : 23 images
Euwallacea_fornicatus : 38 images
Euwallacea_perbrevis : 9 images
Euwallacea_validus : 9 images
Hylastes_porculus : 8 images
Hylastes_salebrosus : 13 images
Hylesinus_aculeatus : 13 images
Hylesinus_crenatus : 9 images
Hylesinus_toranio : 13 images
Hylesinus_varius : 78 images
Hylurgops_palliatus : 15 images
Hylurgus_ligniperda : 25 images
Hypothenemus_hampei : 7 images
Ips_acuminatus : 145 images
Ips_avulsus : 11 images
Ips_calligraphus : 18 images
Ips_duplicatus : 14 images
Ips_grandicollis : 9 images
Ips_sexdentatus : 227 images
Ips_typographus : 314 images
Monarthrum_fasciatum : 42 images
Monarthrum_mali : 14 images
Myoplatypus_flavicornis : 19 images
Orthotomicus_caelatus : 9 images
Orthotomicus_erosus : 7 images
Pagiocerus_frontalis : 11 images
Phloeosinus_dentatus : 38 images
Pityogenes_chalcographus : 11 images
Pityophthorus_juglandis : 22 images
Platypus_cylindrus : 43 images
Platypus_koryoensis : 26 images
Pycnarthrum_hispidium : 11 images
Scolytodes_glaber : 14 images
Scolytus_multistriatus : 8 images
Scolytus_schevyrewi : 8 images
Taphrorychus_bicolor : 9 images
Tomicus_destruens : 9 images
Trypodendron_domesticum : 12 images
Xyleborinus_saxesenii : 41 images
Xyleborus_affinis : 29 images
Xyleborus_celsus : 15 images
Xyleborus_ferrugineus : 13 images
Xyleborus_glabratus : 18 images
Xylosandrus_amputatus : 10 images
Xylosandrus_compactus : 38 images
Xylosandrus_crassiusculus : 60 images
Xylosandrus_germanus : 11 images
Xylosandrus_morigerus : 11 images

Dataset Creation

Curation Rationale

The dataset was created to address the need for a standardized, high-quality benchmark for automated bark beetle identification, a task traditionally reliant on expert taxonomists. The selection of 63 species provides a taxonomically diverse set for robust model evaluation.

Source Data

Images were collected from a variety of sources by the Forest Entomology Lab at the University of Florida to ensure diversity in lighting, background, and specimen condition.

Annotations

The annotation process involved a human-in-the-loop workflow:

1. A zero-shot detection model was used to perform initial localization of beetles in the images.
2. These initial bounding box annotations were then manually verified and corrected by human annotators to ensure accuracy.
3. Species-level classification for each verified bounding box was provided by expert taxonomists to guarantee high-quality labels.

Citation Information

If you use this dataset in your research, please cite the associated paper:

@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}
}