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by123\n\nSummary: 专业物体识别，输入图片返回场景描述及物体名称、类别、品牌、材质、价格区间和识别置信度。\n\nTags: latest:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-02-24T08:26:27.351Z | auto\n\nInitial release of ObjectVision 1.0.0\n\n- Provides professional object recognition from images, returning scene description, object names, categories, brands, materials, estimated prices, and confidence scores.\n- Supports variable detection levels: basic, full, and professional.\n- Input: image URL and detection level.\n- Output: detailed JSON with scene and per-object information, including bounding boxes and optional attributes.\n- Example input/output provided for easy integration and understanding.\n- Licensed under MIT.\n\nArchive index:\n\nArchive v1.0.0: 2 files, 1757 bytes\n\nFiles: skills.md (3631b), _meta.json (136b)\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn70mjqe7w5mjenvn0zc23h13h803y0t\",\n  \"slug\": \"objects-detection\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1771921587351\n}\n\nFile v1.0.0:skills.md\n\n# OpenClaw Skill + iOS 集成示例：ObjectVision\n\n## 一、Skill 信息\n\n- **Skill 名称**: ObjectVision\n- **版本**: 1.0.0\n- **类型**: 视觉识别 / 物体识别\n- **作者**: YourName\n- **描述**: 专业物体识别技能。输入图片，返回场景、物体名称、类别、品牌、材质、价格和置信度。\n- **标签**: object recognition, vision, ai, 物体识别\n- **License**: MIT\n\n---\n\n## 二、Skill 配置 JSON\n\n```json\n{\n  \"name\": \"ObjectVision\",\n  \"description\": \"专业物体识别技能。输入图片，返回场景、物体名称、类别、品牌、材质、价格和置信度。\",\n  \"version\": \"1.0.0\",\n  \"input_schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"image_url\": {\n        \"type\": \"string\",\n        \"description\": \"要识别的图片 URL\"\n      },\n      \"detection_level\": {\n        \"type\": \"string\",\n        \"enum\": [\"basic\", \"full\", \"professional\"],\n        \"default\": \"full\",\n        \"description\": \"识别精度等级，basic: 基础物体, full: 品牌材质, professional: 包含小物件/抽屉内部\"\n      }\n    },\n    \"required\": [\"image_url\"]\n  },\n  \"output_schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"scene\": {\n        \"type\": \"string\",\n        \"description\": \"图片场景描述，例如卧室桌面、办公室\"\n      },\n      \"objects\": {\n        \"type\": \"array\",\n        \"description\": \"检测到的物体列表\",\n        \"items\": {\n          \"type\": \"object\",\n          \"properties\": {\n            \"name\": { \"type\": \"string\", \"description\": \"物体名称\" },\n            \"category\": { \"type\": \"string\", \"description\": \"物体类别\" },\n            \"confidence\": { \"type\": \"number\", \"description\": \"识别置信度，0-1\" },\n            \"bounding_box\": {\n              \"type\": \"array\",\n              \"description\": \"[x, y, width, height] 物体框坐标\",\n              \"items\": { \"type\": \"number\" }\n            },\n            \"brand\": { \"type\": \"string\", \"description\": \"品牌，可推理\" },\n            \"material\": { \"type\": \"string\", \"description\": \"材质，可推理\" },\n            \"estimated_price_range\": { \"type\": \"string\", \"description\": \"估算价格区间\" }\n          },\n          \"required\": [\"name\", \"category\", \"confidence\", \"bounding_box\"]\n        }\n      }\n    },\n    \"required\": [\"scene\", \"objects\"]\n  },\n  \"prompt\": \"You are a professional object recognition engine. Analyze the image provided in 'image_url' and return a JSON with the following: 1. Detect all objects. 2. For each object output: name, category, confidence (0-1), bounding_box [x, y, width, height], brand (if identifiable), material (if inferable), estimated_price_range (if known). 3. Provide scene description. 4. Return only JSON, no explanations. 5. If uncertain, lower confidence score instead of hallucinating.\",\n  \"examples\": [\n    {\n      \"input\": {\n        \"image_url\": \"https://example.com/photo.jpg\",\n        \"detection_level\": \"full\"\n      },\n      \"output\": {\n        \"scene\": \"office desk\",\n        \"objects\": [\n          {\n            \"name\": \"iPhone 15 Pro\",\n            \"category\": \"Electronics\",\n            \"confidence\": 0.95,\n            \"bounding_box\": [100, 50, 200, 400],\n            \"brand\": \"Apple\",\n            \"material\": \"Titanium\",\n            \"estimated_price_range\": \"$999-$1299\"\n          },\n          {\n            \"name\": \"MacBook Pro 16\",\n            \"category\": \"Electronics\",\n            \"confidence\": 0.92,\n            \"bounding_box\": [300, 60, 600, 400],\n            \"brand\": \"Apple\",\n            \"material\": \"Aluminum\",\n            \"estimated_price_range\": \"$2499-$2999\"\n          }\n        ]\n      }\n    }\n  ]\n}","readmeExcerpt":"Skill: 专业物体识别技能。输入图片，返回场景、物体名称、类别、品牌、材质、价格和置信度 Owner: by123 Summary: 专业物体识别，输入图片返回场景描述及物体名称、类别、品牌、材质、价格区间和识别置信度。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-02-24T08:26:27.351Z | auto Initial release of ObjectVision 1.0.0 - Provides professional object recognition from images, returning scene description, object names, categories, brands, materials, estimated prices, and confidence scores. - Supports variable d","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn70mjqe7w5mjenvn0zc23h13h803y0t\",\n  \"slug\": \"objects-detection\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1771921587351\n}"},{"path":"skills.md","content":"# OpenClaw Skill + iOS 集成示例：ObjectVision\n\n## 一、Skill 信息\n\n- **Skill 名称**: ObjectVision\n- **版本**: 1.0.0\n- **类型**: 视觉识别 / 物体识别\n- **作者**: YourName\n- **描述**: 专业物体识别技能。输入图片，返回场景、物体名称、类别、品牌、材质、价格和置信度。\n- **标签**: object recognition, vision, ai, 物体识别\n- **License**: MIT\n\n---\n\n## 二、Skill 配置 JSON\n\n```json\n{\n  \"name\": \"ObjectVision\",\n  \"description\": \"专业物体识别技能。输入图片，返回场景、物体名称、类别、品牌、材质、价格和置信度。\",\n  \"version\": \"1.0.0\",\n  \"input_schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"image_url\": {\n        \"type\": \"string\",\n        \"description\": \"要识别的图片 URL\"\n      },\n      \"detection_level\": {\n        \"type\": \"string\",\n        \"enum\": [\"basic\", \"full\", \"professional\"],\n        \"default\": \"full\",\n        \"description\": \"识别精度等级，basic: 基础物体, full: 品牌材质, professional: 包含小物件/抽屉内部\"\n      }\n    },\n    \"required\": [\"image_url\"]\n  },\n  \"output_schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"scene\": {\n        \"type\": \"string\",\n        \"description\": \"图片场景描述，例如卧室桌面、办公室\"\n      },\n      \"objects\": {\n        \"type\": \"array\",\n        \"description\": \"检测到的物体列表\",\n        \"items\": {\n          \"type\": \"object\",\n          \"properties\": {\n            \"name\": { \"type\": \"string\", \"description\": \"物体名称\" },\n            \"category\": { \"type\": \"string\", \"description\": \"物体类别\" },\n            \"confidence\": { \"type\": \"number\", \"description\": \"识别置信度，0-1\" },\n            \"bounding_box\": {\n              \"type\": \"array\",\n              \"description\": \"[x, y, width, height] 物体框坐标\",\n              \"items\": { \"type\": \"number\" }\n            },\n            \"brand\": { \"type\": \"string\", \"description\": \"品牌，可推理\" },\n            \"material\": { \"type\": \"string\", \"description\": \"材质，可推理\" },\n            \"estimated_price_range\": { \"type\": \"string\", \"description\": \"估算价格区间\" }\n          },\n          \"required\": [\"name\", \"category\", \"confidence\", \"bounding_box\"]\n        }\n      }\n    },\n    \"required\": [\"scene\", \"objects\"]\n  },\n  \"prompt\": \"You are a professional object recognition engine. 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