Duplicate from perona-lab/cfc26-mini

Co-authored-by: Madison Van Horn Mitchell <madivanhorn@users.noreply.huggingface.co>

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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README.md

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+---
+license: cc-by-4.0
+task_categories:
+- object-detection
+---
+# CFC26-Mini Dataset Card
+
+## Dataset Summary
+
+**CFC26-Mini** is a curated sample of the full **CFC26** dataset — a large-scale benchmark for fish detection and counting in underwater ARIS sonar video collected across 9 field locations in North America. This mini version is intended for demonstration purposes.
+
+> **Note:** This is a sample of the full CFC26 dataset. The full dataset contains thousands of clips and hundreds of thousands of annotated frames across all locations and splits. See [Full Dataset](https://huggingface.co/datasets/perona-lab/cfc26/) for details.
+
+---
+
+## Dataset Details
+
+| Property | Value |
+|---|---|
+| **Task** | Fish detection, counting |
+| **Annotation format** | COCO JSON (bounding boxes + track IDs) |
+| **License** | CC BY 4.0 |
+
+---
+
+## Sampling Methodology
+
+CFC26-Mini is constructed from the full CFC26 dataset using the following procedure:
+
+- **1 clip** sampled per split (train / val / test) per location
+- **10 frames** sampled per clip
+- Only frames containing **at least one fish annotation** are included (positive samples only)
+- Temporal train/val/test splits are inherited from the full CFC26 dataset splits
+
+---
+
+## Dataset Structure
+
+```
+cfc26-mini/
+├── {location}/
+│   └── {clip_name}/
+│       └── *.png / *.jpg          # 3-channel representations (fish-positive only)
+```
+
+Each location directory contains up to 3 clip subdirectories (one per split). Frame filenames encode the clip identity and frame index:
+
+```
+{clip_name}_{frame_index}.png  # png and/or jpg
+```
+
+---
+
+## Locations
+
+The mini dataset includes samples from the following field sites:
+
+| Location | Region |
+|---|---|
+| Chemainus | British Columbia, Canada |
+| Dungeness | Washington, USA |
+| Eel | California, USA |
+| Elwha | Washington, USA |
+| Channel | Alaska, USA |
+| Kenai | Alaska, USA |
+| Rightbank | Alaska, USA |
+| Klamath | California, USA |
+| Mad | California, USA |
+| Nanaimo | British Columbia, Canada |
+| Nushagak | Alaska, USA |
+
+---
+
+## Data Fields
+
+Each frame is a 3-channel representation made up of the raw frame, the background-subtracted frame, and the difference between consecutive background-subtracted frames. Annotations are provided in COCO JSON format alongside the full dataset.
+
+**COCO annotation fields per bounding box:**
+
+| Field | Description |
+|---|---|
+| `bbox` | `[x, y, width, height]` in pixels (top-left origin) |
+| `track_id` | Unique fish identity within a clip |
+| `category_id` | Fish category (FISH) |
+| `image_id` | Links to the corresponding frame |
+
+---
+
+## Full Dataset
+
+The full **CFC26** dataset contains:
+- Locations across Alaska, California, Washington, and British Columbia
+- Thousands of annotated clips spanning multi-week deployments per site
+- Temporal train/val/test splits designed to evaluate generalization across time
+- Complete COCO JSON annotations with bounding boxes and track IDs
+- Per-clip ARIS sonar metadata (frame rate, pixel scale, window parameters)
+
+The full dataset is available at: *(link to be added upon release)*
+
+---
+
+## Limitations
+
+- **Positive samples only.** CFC26-Mini contains exclusively fish-positive frames (frames with at least one fish annotation). Empty frames — which constitute a significant portion of the full dataset — are not included. Models trained or evaluated on this mini dataset will not be exposed to the true class imbalance present in real deployments.
+- **1 clip per split per location.** A single clip is unlikely to be representative of the full temporal and environmental variation within a location.
+- **10 frames per clip.** Frames are randomly sampled for this demonstration and are not sequential. Temporal context (motion, track continuity) is not preserved.
+- **Not for benchmarking.** Results on CFC26-Mini are not comparable to results reported on the full CFC26 dataset. Use the full dataset for all benchmark evaluation.
+
+---
+
+## Citation
+
+*(Citation will be updated with full details upon publication.)*
+
+---
+
+## License
+
+CFC26-mini is released under the Creative Commons Attribution 4.0 International [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/deed.en).

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+  "rai:dataLimitations": "The mini dataset contains locations that have 1 clip per training split. This is for demonstration purposes only. The dataset is limited to sonar-based fish counting in riverine environments and may not generalize to other sensing modalities (e.g., optical video), marine/open-ocean settings, or species with substantially different motion or morphology. While expanded to nine river systems, geographic and ecological coverage remains incomplete (North America only), and certain river conditions (e.g., extreme turbidity, rare seasonal events, or atypical flow regimes) may be underrepresented. Annotation quality may be affected by low signal-to-noise ratios and ambiguity in fish visibility, particularly in dense or occluded scenes. The dataset is not recommended for tasks requiring fine-grained species classification, individual fish re-identification, or appearance-based recognition independent of motion cues.",
+  "rai:dataBiases": "The mini dataset may exhibit selection bias toward rivers and deployment sites where sonar systems and data collection is feasible, potentially over-representing current sites of interest in North America. Environmental conditions (e.g., typical flow, sonar artifacts) and species distributions may be unevenly sampled, leading to skewed representations of fish behavior and density. Label bias may arise from human annotation under low-visibility conditions, where temporal cues are required and ambiguous cases may be inconsistently labeled. These biases may cause models to overfit to common environmental patterns or fish movement dynamics and underperform in rare or extreme conditions.",
+  "rai:personalSensitiveInformation": "The dataset does not contain personal or human-related sensitive information. It consists of sonar imagery of fish in natural river environments.",
+  "rai:dataUseCases": "The mini dataset represents fish passage and abundance as measured through sonar-based observations. It is intended for demonstration purposes only.  Valid use case is visualizing environmental variation. The dataset is not validated for unrelated vision tasks (e.g., generic object detection), nor for ecological inference beyond aggregate counting (e.g., behavioral studies or species classification).",
+  "rai:dataSocialImpact": "Positive impacts include improved accuracy and reliability of fish population estimates, which can support sustainable fisheries management, conservation efforts, and evidence-based environmental policy. By enabling evaluation under distribution shift, the dataset may reduce deployment failures in new locations. Potential risks include over-reliance on automated systems without sufficient human oversight, which could propagate systematic errors into policy decisions. There is also a risk that models trained on this dataset may perform poorly in underrepresented environments, leading to inequities in monitoring quality across regions. No direct risks to individuals or communities are present, and no access restrictions are currently imposed beyond standard research use.",
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