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README.md

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+---
+license: cc-by-nc-4.0
+pretty_name: InsectSpec
+task_categories:
+- image-classification
+- zero-shot-image-classification
+- image-segmentation
+tags:
+- insects
+- biodiversity
+- natural-history-collections
+- taxonomy
+- open-vocabulary-recognition
+- segmentation
+- anatomical-part-segmentation
+configs:
+- config_name: metadata
+  data_files:
+  - split: full
+    path: specimen_benchmark_metadata.csv
+---
+
+# InsectSpec
+
+InsectSpec is a curated natural history collection dataset for visual insect specimen understanding. It contains digitized insect specimen images with aligned crops, hierarchical taxonomy, label-derived structured metadata, and fine-grained anatomical part annotations.
+
+## Files
+
+- `specimen_benchmark_metadata.csv`: main metadata table. Each row corresponds to one specimen image and includes split information, taxonomic labels, image/crop paths, and label-derived structured metadata.
+- `specimen_benchmark_metadata.jsonl`: JSONL version of the metadata table.
+- `final_benchmark_data_crops.zip`: cropped insect images used for recognition and segmentation.
+- `segmentation_images.zip`: images used for the anatomical part segmentation subset.
+- `segmentation_annotations.zip`: COCO-style anatomical part segmentation annotations.
+
+## Dataset Structure
+
+The main metadata file contains the structured records used by the benchmark. The image files and segmentation annotations are provided as compressed archives for download.
+
+Recognition experiments use cropped insect images rather than original full images to avoid direct reading of physical specimen labels. Metadata fields that directly encode taxonomy are removed when evaluating metadata-based recognition.
+
+## Benchmark Tasks
+
+### Open Taxonomic Recognition
+
+Models predict taxon-level labels from cropped insect images. The benchmark includes zero-shot, fine-tuned, and unseen-taxon evaluation, with additional metadata-based settings for probing weak specimen context.
+
+### Fine-grained Anatomical Part Segmentation
+
+Models segment insect anatomical structures such as antennae, legs, wings, head, thorax, and abdomen. The benchmark includes supervised and text-guided open-vocabulary segmentation settings.
+
+## License
+
+This dataset is released for non-commercial research and educational use under the CC BY-NC 4.0 license.