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LICENSE

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+Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
+
+Copyright (c) 2026 Infactory
+
+This work is licensed under the Creative Commons Attribution-NonCommercial
+4.0 International License. To view a copy of this license, visit:
+https://creativecommons.org/licenses/by-nc/4.0/
+
+You are free to:
+  - Share: copy and redistribute the material in any medium or format
+  - Adapt: remix, transform, and build upon the material
+
+Under the following terms:
+  - Attribution: You must give appropriate credit, provide a link to the
+    license, and indicate if changes were made.
+  - NonCommercial: You may not use the material for commercial purposes
+    without a separate commercial license from Infactory.
+
+For commercial licensing inquiries, contact: info@infactory.ai

README.md

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+---
+version: 1.0.0
+license: cc-by-nc-4.0
+task_categories:
+  - object-detection
+  - video-classification
+tags:
+  - sports
+  - soccer
+  - football
+  - referee-tracking
+  - person-detection
+annotations_creators:
+  - human-verified
+  - machine-generated
+pretty_name: Soccer Referee Tracking Dataset
+size_categories:
+  - 1K<n<10K
+---
+
+# Soccer Referee Tracking Dataset
+
+A curated dataset for detecting and tracking **referees** in professional soccer broadcast footage. This dataset supports the development of models that can distinguish referees from players, staff, and other on-field personnel under varied broadcast conditions.
+
+## Dataset Description
+
+This public sample consists of **1,450 frames** extracted    from **10 video clips** of professional soccer broadcasts. The data is split into two categories based on referee visibility:
+
+- **Visible**: Frames where at least one referee is clearly visible and annotated with a bounding box.
+- **Not Visible**: Frames where no referee is visible in the frame (negative samples).
+
+This is a representative subset of a larger internal dataset, selected to cover diverse match conditions (SD/HD, different teams, mined vs. segmented clips).
+
+### Statistics
+
+| Category | Samples | Description |
+|----------|---------|-------------|
+| **Visible** | 802 | Frames with at least one referee bounding box |
+| **Not Visible** | 648 | Frames with no visible referee (hard negatives) |
+| **Total** | **1,450** | Total frames from 10 clips |
+
+### Source Data
+
+- **Domain**: Professional Soccer Broadcasts
+- **Resolution**: Varied
+- **Annotation Style**: YOLO format (normalized xywh)
+- **Labeling Method**: Active Learning Loop (COCO Pre-labeling -> Manual Verification)
+- **Anonymization**: Source video names have been replaced with UUIDs.
+
+## Dataset Structure
+
+```
+infactory-ai/referee-tracking/
+├── README.md
+├── metadata.csv
+├── dataset_info.json
+└── data/
+    ├── visible/
+    │   ├── {uuid}_{frame}.jpg
+    │   └── {uuid}_{frame}.txt   # YOLO label
+    └── not_visible/
+        └── {uuid}_{frame}.jpg
+```
+
+### Metadata Fields (`metadata.csv`)
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_path` | string | Relative path to the image file |
+| `video_source` | string | UUID of the source video clip |
+| `frame_index` | int | Frame number in the original clip |
+| `visibility` | string | `visible` or `not_visible` |
+| `bboxes_count` | int | Number of bounding boxes in the frame |
+
+## Usage
+
+### Loading with Hugging Face Datasets
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("infactory-ai/referee-tracking", data_dir="data")
+
+# Filter for visible frames
+visible_frames = dataset.filter(lambda x: x["visibility"] == "visible")
+```
+
+### Parsing Labels
+
+Labels are in standard YOLO format:
+`<class_id> <x_center> <y_center> <width> <height>`
+
+*   `class_id`: 0 (referee)
+*   Coordinates are normalized to [0, 1].
+
+## Team
+
+| Name | Role |
+|------|------|
+| **Valentino Constantinou** | Head of Infrastructure |
+| **Dr. Mehdi Iranmanesh** | Applied AI Engineer |
+| **John Kanalakis** | Chief Technology Officer |
+
+## License
+
+This dataset is released under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/).
+
+**You are free to:**
+- **Share** -- copy and redistribute the material in any medium or format
+- **Adapt** -- remix, transform, and build upon the material
+
+**Under the following terms:**
+- **Attribution** -- You must give appropriate credit to Infactory, provide a link to the license, and indicate if changes were made.
+- **Non-Commercial** -- You may not use the material for commercial purposes without a separate commercial license from Infactory.
+
+**Commercial licensing:** For commercial use, contact [hello@infactory.ai](mailto:hello@infactory.ai).
+
+## Citation
+
+```bibtex
+@dataset{referee_tracking_2026,
+  title={Soccer Referee Tracking Dataset},
+  author={Constantinou, Valentino and Iranmanesh, Mehdi and Kanalakis, John},
+  year={2026},
+  publisher={Infactory},
+  url={https://huggingface.co/datasets/infactory-ai/referee-tracking}
+}
+```

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dataset_info.json

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+{
+  "dataset_name": "Soccer Referee Tracking (Public Sample)",
+  "version": "1.0.0",
+  "description": "Public 10-clip sample of the referee tracking dataset.",
+  "statistics": {
+    "total_samples": 1450,
+    "visible_samples": 802,
+    "not_visible_samples": 648,
+    "total_videos": 10
+  }
+}