dataset-annotation
starsforks
How to install dataset-annotation?
sharpai/deepcamera/dataset-annotation
$npx -y skills add SharpAI/DeepCamera --skill dataset-annotationAI-assisted dataset annotation with COCO export — bbox, SAM2, DINOv3 methods
SKILL.md
| 1 | # Dataset Annotation |
| 2 | |
| 3 | AI-assisted dataset creation for training custom detection models. Supports three annotation methods with COCO format export. |
| 4 | |
| 5 | ## What You Get |
| 6 | |
| 7 | - **BBox annotation** — draw bounding boxes, AI auto-suggests |
| 8 | - **SAM2 annotation** — click to segment, get pixel-perfect masks |
| 9 | - **DINOv3 annotation** — click a patch, find similar objects across frames via visual grounding |
| 10 | - **Object tracking** — annotate keyframes, DINOv3 interpolates across the video |
| 11 | - **COCO export** — standard `images[]`, `annotations[]`, `categories[]` format |
| 12 | - **Kaggle/HuggingFace upload** — push datasets directly to platforms |
| 13 | |
| 14 | ## Annotation Loop |
| 15 | |
| 16 | ``` |
| 17 | 1. Feed frames from clips → auto-detect objects |
| 18 | 2. Human reviews → corrects bboxes, adds labels |
| 19 | 3. Save as COCO dataset |
| 20 | 4. Train improved model |
| 21 | 5. Repeat with better auto-detection |
| 22 | ``` |
| 23 | |
| 24 | ## Protocol |
| 25 | |
| 26 | ### Aegis → Skill (stdin) |
| 27 | ```jsonl |
| 28 | {"event": "frame", "camera_id": "...", "frame_path": "/tmp/frame.jpg", "frame_number": 0, "width": 1920, "height": 1080} |
| 29 | {"event": "detections", "frame_number": 0, "detections": [{"class": "person", "bbox": [100, 50, 200, 350], "confidence": 0.9, "track_id": "t1"}]} |
| 30 | {"event": "save_dataset", "name": "front_door_people", "format": "coco"} |
| 31 | ``` |
| 32 | |
| 33 | ### Skill → Aegis (stdout) |
| 34 | ```jsonl |
| 35 | {"event": "ready", "methods": ["bbox", "sam2", "dinov3"], "export_formats": ["coco", "yolo", "voc"]} |
| 36 | {"event": "annotation", "frame_number": 0, "annotations": [{"category": "person", "bbox": [100, 50, 200, 350], "track_id": "t1", "is_keyframe": true}]} |
| 37 | {"event": "dataset_saved", "format": "coco", "path": "~/datasets/front_door_people/", "stats": {"images": 150, "annotations": 423, "categories": 5}} |
| 38 | ``` |
| 39 | |
| 40 | ## Setup |
| 41 | |
| 42 | ```bash |
| 43 | python3 -m venv .venv && source .venv/bin/activate |
| 44 | pip install -r requirements.txt |
| 45 | ``` |
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