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README.md

@@ -1,251 +1,250 @@
 ---
-license: mit
+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: cluster_count_prediction/train-*
-- config_name: clustering_supervised
-  data_files:
-  - split: train
-    path: clustering_supervised/train-*
-- config_name: clustering_unsupervised
-  data_files:
-  - split: train
-    path: clustering_unsupervised/train-*
-- config_name: dimensionality_reduction
-  data_files:
-  - split: train
-    path: dimensionality_reduction/train-*
-- config_name: embeddings_bioclip2_vitl14
-  data_files:
-  - split: train
-    path: embeddings_bioclip2_vitl14/train-*
-- config_name: embeddings_clip_vitl14
-  data_files:
-  - split: train
-    path: embeddings_clip_vitl14/train-*
-- config_name: embeddings_dinov2_vitg14
-  data_files:
-  - split: train
-    path: embeddings_dinov2_vitg14/train-*
-- config_name: embeddings_dinov3_vith16plus
-  data_files:
-  - split: train
-    path: embeddings_dinov3_vith16plus/train-*
-- config_name: embeddings_siglip_vitb16
-  data_files:
-  - split: train
-    path: embeddings_siglip_vitb16/train-*
-- config_name: model_comparison
-  data_files:
-  - split: train
-    path: model_comparison/train-*
-- config_name: primary_benchmarking
-  data_files:
-  - split: train
-    path: primary_benchmarking/train-*
-dataset_info:
-- config_name: cluster_count_prediction
-  features:
-  - name: filename
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 2580249
-    num_examples: 2
-  download_size: 755518
-  dataset_size: 2580249
-- config_name: clustering_supervised
-  features:
-  - name: filename
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 10766
-    num_examples: 1
-  download_size: 6185
-  dataset_size: 10766
-- config_name: clustering_unsupervised
-  features:
-  - name: filename
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 6867
-    num_examples: 1
-  download_size: 4042
-  dataset_size: 6867
-- config_name: dimensionality_reduction
-  features:
-  - name: filename
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 6140
-    num_examples: 1
-  download_size: 4403
-  dataset_size: 6140
-- config_name: embeddings_bioclip2_vitl14
-  features:
-  - name: model
-    dtype: string
-  - name: architecture
-    dtype: string
-  - name: taxon_class
-    dtype: string
-  - name: run
-    dtype: int64
-  - name: label
-    dtype: string
-  - name: image_path
-    dtype: string
-  - name: embedding
-    list: float64
-  splits:
-  - name: train
-    num_bytes: 751350000
-    num_examples: 120000
-  download_size: 565974442
-  dataset_size: 751350000
-- config_name: embeddings_clip_vitl14
-  features:
-  - name: model
-    dtype: string
-  - name: architecture
-    dtype: string
-  - name: taxon_class
-    dtype: string
-  - name: run
-    dtype: int64
-  - name: label
-    dtype: string
-  - name: image_path
-    dtype: string
-  - name: embedding
-    list: float64
-  splits:
-  - name: train
-    num_bytes: 750870000
-    num_examples: 120000
-  download_size: 177918154
-  dataset_size: 750870000
-- config_name: embeddings_dinov2_vitg14
-  features:
-  - name: model
-    dtype: string
-  - name: architecture
-    dtype: string
-  - name: taxon_class
-    dtype: string
-  - name: run
-    dtype: int64
-  - name: label
-    dtype: string
-  - name: image_path
-    dtype: string
-  - name: embedding
-    list: float64
-  splits:
-  - name: train
-    num_bytes: 1488390000
-    num_examples: 120000
-  download_size: 1134730246
-  dataset_size: 1488390000
-- config_name: embeddings_dinov3_vith16plus
-  features:
-  - name: model
-    dtype: string
-  - name: architecture
-    dtype: string
-  - name: taxon_class
-    dtype: string
-  - name: run
-    dtype: int64
-  - name: label
-    dtype: string
-  - name: image_path
-    dtype: string
-  - name: embedding
-    list: float64
-  splits:
-  - name: train
-    num_bytes: 1243110000
-    num_examples: 120000
-  download_size: 946309257
-  dataset_size: 1243110000
-- config_name: embeddings_siglip_vitb16
-  features:
-  - name: model
-    dtype: string
-  - name: architecture
-    dtype: string
-  - name: taxon_class
-    dtype: string
-  - name: run
-    dtype: int64
-  - name: label
-    dtype: string
-  - name: image_path
-    dtype: string
-  - name: embedding
-    list: float64
-  splits:
-  - name: train
-    num_bytes: 751110000
-    num_examples: 120000
-  download_size: 566884684
-  dataset_size: 751110000
-- config_name: model_comparison
-  features:
-  - name: filename
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 25506
-    num_examples: 3
-  download_size: 9316
-  dataset_size: 25506
-- config_name: primary_benchmarking
-  features:
-  - name: model
-    dtype: large_string
-  - name: model_short
-    dtype: large_string
-  - name: dim_reduction
-    dtype: large_string
-  - name: clustering
-    dtype: large_string
-  - name: v_measure
-    dtype: float64
-  - name: adjusted_rand_index
-    dtype: float64
-  - name: normalized_mutual_info
-    dtype: float64
-  - name: homogeneity
-    dtype: float64
-  - name: completeness
-    dtype: float64
-  - name: n_clusters_pred
-    dtype: float64
-  - name: n_clusters_true
-    dtype: float64
-  - name: path
-    dtype: large_string
-  splits:
-  - name: train
-    num_bytes: 7046440
-    num_examples: 27600
-  download_size: 1641013
-  dataset_size: 7046440
+  - config_name: primary_benchmarking
+    data_files:
+      - split: train
+        path: "01_primary_benchmarking/*.csv"
+    default: true
+  - config_name: model_comparison
+    data_files:
+      - split: train
+        path: "02_model_comparison/*.json"
+  - config_name: dimensionality_reduction
+    data_files:
+      - split: train
+        path: "03_dimensionality_reduction/*.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: cluster_count_prediction
+    data_files:
+      - split: train
+        path: "06_cluster_count_prediction/*.json"
+  - config_name: scaling_tests
+    data_files:
+      - split: train
+        path: "09_scaling_tests/**/*.json"
 ---
+
+# 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