Update README.md

README.md

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 ---
-pretty_name: BioDCASE 2026 Bird Counting
-language:
-- en
+license: cc-by-4.0
 task_categories:
-- audio-classification
+  - audio-classification
+language:
+  - en
 tags:
-- audio
-- birds
-- bioacoustics
-- biodiversity
-- ecology
+  - audio
+  - birds
+  - bioacoustics
+  - biodiversity
+  - ecology
+  - population-estimation
+  - bird-counting
+  - zoo
+  - aviary
+  - passive-acoustic-monitoring
+  - biodcase
+  - biodcase2026
+pretty_name: "BioDCASE 2026 - Bird Counting (Task 6)"
+size_categories:
+  - 100K<n<1M
 ---
 
-# BioDCASE 2026 Bird Counting
+# BioDCASE 2026 — Bird Counting (Task 6)
+
+Development dataset for the **Bird Counting** task of the [BioDCASE 2026 Challenge](https://biodcase.github.io/challenge2026/).
+
+## Task overview
+
+Estimating the number of individual birds from acoustic recordings is a fundamental challenge in biodiversity monitoring. This task addresses **bird abundance estimation** in zoo aviaries with known ground-truth population counts.
+
+Participants receive collections of short audio fragments (~3 seconds each) extracted from continuous passive acoustic recordings in multi-species aviaries. Each aviary contains a known number of a target bird species alongside other co-occurring species. The recordings capture birds vocalizing naturally in groups over extended periods, creating realistic acoustic complexity including overlapping vocalizations, environmental noise, and natural behavioral variation.
+
+**The task is to estimate the number of individuals of the target species in each aviary.**
+
+For full task details, timeline, evaluation criteria, and submission instructions, see:
+- **Task page:** [https://www.ml4biodiversity.org/biodcase26_birdcounts/](https://www.ml4biodiversity.org/biodcase26_birdcounts/)
+- **Challenge page:** [https://biodcase.github.io/challenge2026/](https://biodcase.github.io/challenge2026/)
+- **Baseline code:** [https://github.com/ml4biodiversity/biodcase-population-estimation](https://github.com/ml4biodiversity/biodcase-population-estimation)
+
+## Dataset description
+
+The development dataset contains **140,899 audio files** across **6 aviaries** recorded at European zoos using passive acoustic monitoring equipment. Recordings were made during spring and summer 2025. Each aviary was recorded continuously for 7–11 days; this dataset includes a curated subset of **2–3 representative days** per aviary selected to minimize distributional distortion of key acoustic features while keeping the dataset manageable.
+
+### Target species
+
+Three bird species are designated as estimation targets. Population estimation is evaluated only for these species:
+
+| Species | Scientific name | Aviaries | Population range |
+|---|---|---|---|
+| Greater flamingo | *Phoenicopterus roseus* | aviary_2, aviary_4, aviary_5, aviary_6 | 52–161 |
+| Red-billed quelea | *Quelea quelea* | aviary_1, aviary_3 | 61–153 |
+| Hadada ibis | *Bostrychia hagedash* | aviary_2, aviary_4 | 4–6 |
+
+Each aviary also contains additional non-target bird species (2–12 species per aviary, 28 species in total across all aviaries). The complete species inventory with population counts is provided in `metadata/ground_truth.csv`.
+
+### Aviary summary
+
+| Aviary | Days | Audio files | Target species | Target population |
+|---|---|---|---|---|
+| aviary_1 | 3 | 12,627 | Red-billed quelea | 153 |
+| aviary_2 | 3 | 25,569 | Greater flamingo (107), Hadada ibis (6) | 113 |
+| aviary_3 | 3 | 11,879 | Red-billed quelea | 61 |
+| aviary_4 | 3 | 36,340 | Greater flamingo (161), Hadada ibis (4) | 165 |
+| aviary_5 | 2 | 19,363 | Greater flamingo | 52 |
+| aviary_6 | 3 | 35,121 | Greater flamingo | 52 |
+| **Total** | **17** | **140,899** | | |
+
+**Note:** Aviary 5 and aviary 6 are two separate recording sessions from the same physical location with the same bird population, captured on different dates. They are treated as independent data points with different acoustic conditions.
+
+### Audio format
+
+All audio files are single-channel (mono) WAV files, 16-bit PCM, sampled at **48 kHz**, with a duration of approximately **3 seconds** each. The files represent consecutive, non-overlapping segments extracted from continuous recordings.
+
+## Dataset structure
+
+```
+BioDCASE2026_Bird_Counting/
+├── aviary_1/
+│   ├── chunk_000/
+│   │   ├── rec_d1_00_00_45.750000.wav
+│   │   ├── rec_d1_00_01_49.wav
+│   │   └── ...
+│   ├── chunk_001/
+│   │   └── ...
+│   └── ...
+├── aviary_2/
+│   └── ...
+├── aviary_3/
+│   └── ...
+├── aviary_4/
+│   └── ...
+├── aviary_5/
+│   └── ...
+├── aviary_6/
+│   └── ...
+└── metadata/
+    ├── ground_truth.csv
+    └── recording_info.csv
+```
+
+### Filename convention
+
+Audio filenames follow the pattern:
+
+```
+rec_{day}_{HH}_{MM}_{SS}[.ffffff].wav
+```
+
+where `{day}` is a day identifier (`d1`, `d2`, or `d3`) and `{HH}_{MM}_{SS}[.ffffff]` encodes the time of day (hours, minutes, seconds, optional fractional seconds). For example, `rec_d1_19_05_02.500000.wav` is a recording from day 1 at 19:05:02.5.
+
+
+### Chunk subdirectories
+
+Within each aviary, audio files are organized into `chunk_NNN/` subdirectories for practical file management. The chunk boundaries have no acoustic significance — they are simply a way to keep directory sizes manageable. All chunks within an aviary should be treated as a single continuous collection.
+
+## Metadata
+
+### `metadata/ground_truth.csv`
+
+Complete species inventory for all 6 aviaries, including both target and non-target species:
+
+| Column | Description |
+|---|---|
+| `aviary_id` | Aviary identifier (`aviary_1` through `aviary_6`) |
+| `common_name` | English common name of the species |
+| `scientific_name` | Binomial scientific name |
+| `count` | Number of individuals present in the aviary |
+| `is_target` | `1` if the species is evaluated for population estimation, `0` otherwise |
+
+### `metadata/recording_info.csv`
+
+Summary statistics per aviary:
+
+| Column | Description |
+|---|---|
+| `aviary_id` | Aviary identifier |
+| `n_days` | Number of recording days included |
+| `n_files` | Total number of audio files |
+
+## Baseline system
+
+A complete baseline system is available at [https://github.com/ml4biodiversity/biodcase-population-estimation](https://github.com/ml4biodiversity/biodcase-population-estimation). It implements a two-stage pipeline:
+
+1. **Species detection** — Run a bird species detector on each aviary's audio files. Two detection packages are provided:
+   - `pip install aria-inference` (ARIA ensemble detector, recommended)
+   - `pip install aria-inference-birdnet` (BirdNET-based detector)
+
+2. **Feature extraction** — Extract detection-count statistics, temporal bout structure, and optionally scikit-maad acoustic indices from the detection output.
+
+3. **Population estimation** — Fit species-specific regression models using leave-one-out cross-validation.
+
+The baseline achieves a combined MAE of 11.77 (MAPE 11.4%) across all target species using ARIA detections.
+
+## Evaluation
+
+The main leaderboard ranks systems based on population estimation accuracy for the three target species. The primary metric is **Mean Absolute Error (MAE)** computed across all (aviary, target species) data points. Secondary metrics include RMSE, R², and MAPE.
+
+Participants may optionally extend their methods to non-target species for a secondary leaderboard, but this does not affect final rankings.
+
+The evaluation set will be released according to the [challenge timeline](https://biodcase.github.io/challenge2026/).
+
+## Key challenges
+
+- **Flock-calling species:** Greater flamingos vocalize synchronously in large groups, making it difficult to distinguish individual contributions from detection counts alone. Raw detection rates saturate as flock size grows.
+- **Sparse calibration data:** With only 6 aviaries (and 2–4 data points per target species), models must generalize from very few examples.
+- **Multi-species environments:** Each aviary contains 2–12 co-occurring species with overlapping frequency ranges and calling times.
+- **Population range:** Target populations span two orders of magnitude (4 to 161 individuals), requiring methods that work across scales.
+
+## Usage with 🤗 Datasets
+
+```python
+from datasets import load_dataset
+
+# Load the dataset (streams audio on demand)
+ds = load_dataset("Emreargin/BioDCASE2026_Bird_Counting")
+```
+
+Or download directly and process locally:
+
+```bash
+# Clone with git-lfs
+git lfs install
+git clone https://huggingface.co/datasets/Emreargin/BioDCASE2026_Bird_Counting
+
+# Run the baseline
+cd biodcase-population-estimation
+pip install aria-inference # or for faster and simpler detector -> pip install aria-inference-birdnet 
+aria-inference --input ../BioDCASE2026_Bird_Counting/aviary_1/ --output detections/aviary_1_detections.csv
+# ... repeat for aviary_2 through aviary_6
+python feature_builder.py --detections-dir detections/ --audio-root ../BioDCASE2026_Bird_Counting/ --output results/stage2_features.csv
+python estimator.py --features results/stage2_features.csv
+```
+
+## License
+
+This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{biodcase2026_birdcounting,
+  title     = {BioDCASE 2026 Bird Counting: Avian Population Estimation from Passive Acoustic Recordings},
+  author    = {Arg{\i}n, Emre and H{\"a}rm{\"a}, Aki and Arslan-Dogan, Aysenur},
+  year      = {2026},
+  publisher = {Hugging Face},
+  url       = {https://huggingface.co/datasets/Emreargin/BioDCASE2026_Bird_Counting}
+}
+```
+
+## Contact
 
-Curated zoo aviary audio dataset for bird counting.
+For questions about the dataset or the challenge task, please contact:
+- **Emre Argın** — Maastricht University ([challenge task lead](https://biodcase.github.io/challenge2026/))
+- **Aki Härmä** — Maastricht University
+- **Aysenur Arslan-Dogan** — Maastricht University ([main contact person]) 
 
-## Contents
-- `aviary_1/` to `aviary_6/`
-- `metadata/ground_truth.csv`
+Or open a discussion on the [dataset page](https://huggingface.co/datasets/Emreargin/BioDCASE2026_Bird_Counting/discussions).