| ---
|
| license: cc-by-4.0
|
| task_categories:
|
| - image-classification
|
| - zero-shot-classification
|
| tags:
|
| - biology
|
| - ecology
|
| - wildlife
|
| - camera-traps
|
| - vision-transformers
|
| - clustering
|
| - zero-shot-learning
|
| - biodiversity
|
| - reproducibility
|
| - benchmarking
|
| - embeddings
|
| - dinov3
|
| - dinov2
|
| - bioclip
|
| - clip
|
| - siglip
|
| language:
|
| - en
|
| pretty_name: HUGO-Bench Paper Reproducibility Data
|
| size_categories:
|
| - 100K<n<1M
|
| source_datasets:
|
| - AI-EcoNet/HUGO-Bench
|
| configs:
|
| - config_name: cluster_count_prediction
|
| data_files:
|
| - split: train
|
| path: 06_cluster_count_prediction/*.json
|
| - config_name: clustering_supervised
|
| data_files:
|
| - split: train
|
| path: 04_clustering_supervised/*.json
|
| - config_name: clustering_unsupervised
|
| data_files:
|
| - split: train
|
| path: 05_clustering_unsupervised/*.json
|
| - config_name: dimensionality_reduction
|
| data_files:
|
| - split: train
|
| path: 03_dimensionality_reduction/*.json
|
| - config_name: intra_species_variation
|
| data_files:
|
| - split: train
|
| path: intra_species_variation/train-*
|
| - config_name: model_comparison
|
| data_files:
|
| - split: train
|
| path: 02_model_comparison/*.json
|
| - config_name: primary_benchmarking
|
| data_files:
|
| - split: train
|
| path: 01_primary_benchmarking/*.csv
|
| default: true
|
| - config_name: scaling_tests
|
| data_files:
|
| - split: train
|
| path: scaling_tests/train-*
|
| - config_name: subsample_definitions
|
| data_files:
|
| - split: train
|
| path: subsample_definitions/train-*
|
| - config_name: uneven_distribution
|
| data_files:
|
| - split: train
|
| path: uneven_distribution/train-*
|
| dataset_info:
|
| - config_name: intra_species_variation
|
| features:
|
| - name: filename
|
| dtype: string
|
| - name: content
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_bytes: 64315
|
| num_examples: 11
|
| download_size: 11487
|
| dataset_size: 64315
|
| - config_name: scaling_tests
|
| features:
|
| - name: filename
|
| dtype: string
|
| - name: content
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_bytes: 5754770
|
| num_examples: 1205
|
| download_size: 1304695
|
| dataset_size: 5754770
|
| - config_name: subsample_definitions
|
| features:
|
| - name: filename
|
| dtype: string
|
| - name: content
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_bytes: 3038864
|
| num_examples: 10
|
| download_size: 643403
|
| dataset_size: 3038864
|
| - config_name: uneven_distribution
|
| features:
|
| - name: filename
|
| dtype: string
|
| - name: content
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_bytes: 1914245
|
| num_examples: 410
|
| download_size: 374649
|
| dataset_size: 1914245
|
| ---
|
|
|
| # HUGO-Bench Paper Reproducibility
|
|
|
| **Supplementary data and reproducibility materials for the paper:**
|
|
|
| > **Vision Transformers for Zero-Shot Clustering of Animal Images: A Comparative Benchmarking Study**
|
| >
|
| > Hugo Markoff, Stefan Hein Bengtson, Michael Ørsted
|
| >
|
| > Aalborg University, Denmark
|
|
|
| ## Dataset Description
|
|
|
| This repository contains complete experimental results, pre-computed embeddings, and execution logs from our comprehensive benchmarking study evaluating Vision Transformer models for zero-shot species-level clustering of camera trap images.
|
|
|
| ### Relationship to HUGO-Bench
|
|
|
| This dataset is derived from [HUGO-Bench](https://huggingface.co/datasets/AI-EcoNet/HUGO-Bench), which provides the source images and species annotations. While HUGO-Bench contains the **validated image crops** (139,111 images across 60 species), this repository provides:
|
|
|
| - **Clustering results** from all 27,600 experimental configurations
|
| - **Pre-computed embeddings** enabling reproduction without image access
|
| - **Execution logs** for full experimental traceability
|
|
|
| | Dataset | Content | Purpose |
|
| |---------|---------|---------|
|
| | [HUGO-Bench](https://huggingface.co/datasets/AI-EcoNet/HUGO-Bench) | 139,111 validated camera trap images | Source images for experiments |
|
| | **This repository** | Results, embeddings, logs | Paper reproducibility |
|
|
|
| ## Repository Structure
|
|
|
| ```
|
| ├── 01_primary_benchmarking/ # Full 27,600 configuration results
|
| │ ├── clustering_analysis_complete.csv
|
| │ ├── clustering_analysis_with_ami.csv
|
| │ ├── comprehensive_vmeasure_by_class.json
|
| │ └── images_run_*.json # Subsample definitions (10 runs)
|
| │
|
| ├── 02_model_comparison/ # 5 ViT model comparison
|
| │ ├── dinov3_all_combinations_results.json
|
| │ ├── dinov3_bioclip_siglip_all_methods_results.json
|
| │ └── dinov3_comparison_results.json
|
| │
|
| ├── 03_dimensionality_reduction/ # t-SNE, UMAP, PCA, Isomap, KPCA
|
| │ └── dimensionality_comparison.json
|
| │
|
| ├── 04_clustering_supervised/ # K-variation experiments (K=15,30,45,90,180)
|
| │ ├── k30_metrics_by_class.json
|
| │ └── k_variation_by_dimred_class.json
|
| │
|
| ├── 05_clustering_unsupervised/ # HDBSCAN vs DBSCAN
|
| │ └── unsupervised_metrics_by_class.json
|
| │
|
| ├── 06_cluster_count_prediction/ # Progressive species testing (1,200 runs)
|
| │ ├── progressive_species_testing_results.json
|
| │ └── progressive_species_testing_results_expanded.json
|
| │
|
| ├── 07_intra_species_variation/ # Age, sex, pelage detection
|
| │ ├── wolf_dbscan_clusters/
|
| │ └── intra_cluster/
|
| │
|
| ├── 08_uneven_distribution/ # Long-tailed distribution tests
|
| │ ├── extreme_20_max_test/
|
| │ ├── original_config_extreme_uneven_test/
|
| │ └── even_distribution_results.json
|
| │
|
| ├── 09_scaling_tests/ # 5-60 species scaling behavior
|
| │ ├── scaling_test_results/
|
| │ └── different_n_test/
|
| │
|
| ├── 10_embeddings/ # Pre-computed embeddings
|
| │ ├── embeddings/ # Standard benchmarking embeddings
|
| │ ├── extreme_uneven_embeddings/
|
| │ └── extreme_uneven_image_lists/
|
| │
|
| └── execution_logs/ # Complete execution logs
|
| ├── clustering_dimred_log.txt
|
| ├── clustering_complete_log.txt
|
| └── ...
|
| ```
|
|
|
| ## Key Results Summary
|
|
|
| Our benchmarking evaluated **27,600 configurations** across:
|
| - **5 ViT Models**: DINOv3, DINOv2, BioCLIP 2, CLIP, SigLIP
|
| - **5 Dimensionality Reduction**: t-SNE, UMAP, PCA, Isomap, Kernel PCA
|
| - **4 Clustering Algorithms**: Hierarchical, GMM, HDBSCAN, DBSCAN
|
| - **60 Species**: 30 mammals + 30 birds from camera trap imagery
|
|
|
| ### Top Performing Configuration
|
|
|
| | Component | Best Choice | V-Measure |
|
| |-----------|-------------|-----------|
|
| | Model | DINOv3 | 0.958 |
|
| | Dim. Reduction | t-SNE | +26-38pp vs others |
|
| | Clustering (supervised) | Hierarchical K=30 | 0.958 |
|
| | Clustering (unsupervised) | HDBSCAN | 0.943 |
|
|
|
| ## Usage
|
|
|
| ### Loading Results with Python
|
|
|
| ```python
|
| import pandas as pd
|
| import json
|
|
|
| # Load primary benchmarking results
|
| results = pd.read_csv("01_primary_benchmarking/clustering_analysis_complete.csv")
|
|
|
| # Filter for best model
|
| dinov3_results = results[results['model'] == 'dinov3']
|
|
|
| # Load JSON metrics
|
| with open("05_clustering_unsupervised/unsupervised_metrics_by_class.json") as f:
|
| unsupervised = json.load(f)
|
| ```
|
|
|
| ### Using Pre-computed Embeddings
|
|
|
| The `10_embeddings/` folder contains pre-computed embeddings that allow running clustering experiments **without needing the original images**:
|
|
|
| ```python
|
| import numpy as np
|
| import json
|
|
|
| # Load embeddings
|
| embeddings = np.load("10_embeddings/embeddings/dinov3_embeddings.npy")
|
|
|
| # Load corresponding image list
|
| with open("01_primary_benchmarking/images_run_1.json") as f:
|
| image_list = json.load(f)
|
| ```
|
|
|
| ### Reproducing Paper Tables
|
|
|
| Each folder corresponds to specific paper sections:
|
|
|
| | Paper Section | Data Folder |
|
| |--------------|-------------|
|
| | Table 3 (V-measure by model) | `01_primary_benchmarking/` |
|
| | Table 4 (Dim. reduction comparison) | `03_dimensionality_reduction/` |
|
| | Table 5 (Supervised K variation) | `04_clustering_supervised/` |
|
| | Table 6 (Unsupervised comparison) | `05_clustering_unsupervised/` |
|
| | Figure 5 (Cluster count prediction) | `06_cluster_count_prediction/` |
|
| | Table 7 (Intra-species traits) | `07_intra_species_variation/` |
|
| | Table 8 (Uneven distribution) | `08_uneven_distribution/` |
|
| | Figure 8 (Scaling behavior) | `09_scaling_tests/` |
|
|
|
| ## File Formats
|
|
|
| | Extension | Description | How to Load |
|
| |-----------|-------------|-------------|
|
| | `.csv` | Tabular results | `pandas.read_csv()` |
|
| | `.json` | Structured metrics | `json.load()` |
|
| | `.npy` | NumPy embeddings | `numpy.load()` |
|
| | `.txt`/`.log` | Execution logs | Plain text |
|
|
|
| ## Citation
|
|
|
| If you use this data, please cite both the paper and HUGO-Bench:
|
|
|
| ```bibtex
|
| @article{markoff2025vit_clustering,
|
| title={Vision Transformers for Zero-Shot Clustering of Animal Images: A Comparative Benchmarking Study},
|
| author={Markoff, Hugo and Bengtson, Stefan Hein and {\O}rsted, Michael},
|
| journal={TBD},
|
| year={2025}
|
| }
|
|
|
| @dataset{hugo_bench,
|
| title={HUGO-Bench: A Benchmark Dataset for Camera Trap Species Clustering},
|
| author={AI-EcoNet},
|
| year={2025},
|
| url={https://huggingface.co/datasets/AI-EcoNet/HUGO-Bench}
|
| }
|
| ```
|
|
|
| ## License
|
|
|
| This dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
|
|
|
| ## Contact
|
|
|
| - **Hugo Markoff** - khbm@bio.aau.dk
|
| - Department of Chemistry and Bioscience, Aalborg University
|
|
|
| ## Related Resources
|
|
|
| - 📊 [HUGO-Bench Dataset](https://huggingface.co/datasets/AI-EcoNet/HUGO-Bench) - Source images (139,111 validated crops)
|
| - 💻 [GitHub Repository](https://github.com/HugoMarkoff/animal_visual_transformer) - Code and scripts
|
| - 🌐 [Interactive Visualization](https://hugomarkoff.github.io/animal_visual_transformer/) - Explore clustering results
|
|
|
