SharpAI
SharpAI/DeepCamera
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/SharpAI/DeepCamera --skill annotation-data命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
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| name | annotation-data |
| description | Dataset annotation management — COCO labels, sequences, export, and Kaggle upload |
| version | 1.0.0 |
| entry | scripts/annotation_manager.py |
| deploy | deploy.sh |
| parameters | [{"name":"datasets_dir","label":"Datasets Directory","type":"string","default":"","description":"Root directory for annotation datasets (auto-detected if empty)","group":"Storage"}] |
| capabilities | {"live_transform":{"script":"scripts/annotation_manager.py","description":"Dataset CRUD, annotation save/load, COCO export"}} |
| ui_unlocks | ["annotation_studio"] |
Manages annotation datasets for Aegis Annotation Studio. Handles dataset CRUD, label management, COCO-format export, and Kaggle upload.
{"command": "list_datasets", "request_id": "req_001"}
{"command": "get_dataset", "name": "my_dataset", "request_id": "req_002"}
{"command": "save_dataset", "name": "my_dataset", "labels": [...], "request_id": "req_003"}
{"command": "delete_dataset", "name": "my_dataset", "request_id": "req_004"}
{"command": "save_annotation", "dataset": "my_dataset", "frame_id": "f1", "annotations": [...], "request_id": "req_005"}
{"command": "list_labels", "dataset": "my_dataset", "request_id": "req_006"}
{"command": "export_coco", "dataset": "my_dataset", "request_id": "req_007"}
{"command": "get_stats", "dataset": "my_dataset", "request_id": "req_008"}
{"command": "stop"}
{"event": "annotation", "type": "ready", "request_id": "", "data": {"version": "1.0.0"}}
{"event": "annotation", "type": "datasets", "request_id": "req_001", "data": [...]}
{"event": "annotation", "type": "dataset", "request_id": "req_002", "data": {...}}
{"event": "annotation", "type": "saved", "request_id": "req_005", "data": {"frame_id": "f1", "count": 3}}
{"event": "annotation", "type": "exported", "request_id": "req_007", "data": {"path": "/path/to/coco.json"}}