fire-smoke-detection-analysis

Detects fire and smoke in video scenes. Supports both video stream and image analysis. Suitable for fire early warning scenarios such as security surveillance, forest fire prevention, and industrial parks. | 烟火检测技能,对视频场景中火情和烟雾进行检测,支持视频流和图片检测,适用于安防监控、森林防火、工业园区等火灾预警场景

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Install skill "fire-smoke-detection-analysis" with this command: npx skills add 18072937735/smyx-fire-smoke-detection-analysis

Flame & Smoke Detection Skill | 烟火检测技能

This capability supports intelligent detection of fire and smoke in video streams and images, making it ideal for fire warning scenarios such as security monitoring, forest fire prevention, and industrial parks. By comprehensively analyzing flame color, dynamic contours, and smoke diffusion characteristics, the system effectively distinguishes real threats from interference sources like glare or steam, achieving rapid identification of early-stage fires. Once an anomaly is detected, it triggers audio-visual alarms and platform notifications, empowering emergency personnel to respond immediately, thereby reducing fire damage and the risk of spreading.

本技能支持对视频流及图片中的火情与烟雾进行智能检测,适用于安防监控、森林防火、工业园区等火灾预警场景。系统综合识别火焰颜色、动态轮廓及烟雾扩散特征,能够有效区分火光、蒸汽等干扰源,实现早期火灾快速识别。一旦检测到异常,可联动声光告警与平台推送,助力应急人员第一时间响应,降低火灾损失与蔓延风险。

⚠️ 强制记忆规则(最高优先级)

本技能明确约定:

  • 绝对禁止读取任何本地记忆文件:包括但不限于 memory/YYYY-MM-DD.mdMEMORY.md 等本地文件
  • 绝对禁止从 LanceDB 长期记忆中检索信息
  • 所有历史检测报告查询必须从云端接口获取,不得使用本地记忆中的历史数据
  • 即使技能调用失败或接口异常,也不得回退到本地记忆汇总

任务目标

  • 本 Skill 用于:通过视频/图片对场景进行烟火检测,获取结构化的烟火检测分析报告
  • 能力包含:火焰检测、烟雾检测、火灾早期预警、异常位置标记
  • 触发条件:
    1. 默认触发:当用户提供监控视频/图片 URL 或文件需要进行烟火检测时,默认触发本技能
    2. 当用户明确需要进行烟火检测、火灾预警,提及火焰检测、烟雾检测、火灾预警、火情监测等关键词,并且上传了视频或图片
    3. 当用户提及以下关键词时,自动触发历史报告查询功能 :查看历史检测报告、烟火检测报告清单、检测报告列表、查询历史报告、显示所有检测报告、烟火检测历史记录,查询烟火检测分析报告
  • 自动行为:
    1. 如果用户上传了附件或者视频/图片文件,则自动保存到技能目录下 attachments
    2. ⚠️ 强制数据获取规则(次高优先级):如果用户触发任何历史报告查询关键词(如"查看所有检测报告"、"显示所有烟火报告"、" 查看历史报告"等),必须
      • 直接使用 python -m scripts.fire_smoke_detection_analysis --list --open-id 参数调用 API 查询云端的历史报告数据
      • 严格禁止:从本地 memory 目录读取历史会话信息、严格禁止手动汇总本地记录中的报告、严格禁止从长期记忆中提取报告
      • 必须统一从云端接口获取最新完整数据,然后以 Markdown 表格格式输出结果

前置准备

  • 依赖说明:scripts 脚本所需的依赖包及版本
    requests>=2.28.0
    

操作步骤

🔒 open-id 获取流程控制(强制执行,防止遗漏)

在执行烟火检测前,必须按以下优先级顺序获取 open-id:

第 1 步:【最高优先级】检查技能所在目录的配置文件(优先)
        路径:skills/smyx_common/scripts/config.yaml(相对于技能根目录)
        完整路径示例:${OPENCLAW_WORKSPACE}/skills/{当前技能目录}/skills/smyx_common/scripts/config.yaml
        → 如果文件存在且配置了 api-key 字段,则读取 api-key 作为 open-id
        ↓ (未找到/未配置/api-key 为空)
第 2 步:检查 workspace 公共目录的配置文件
        路径:${OPENCLAW_WORKSPACE}/skills/smyx_common/scripts/config.yaml
        → 如果文件存在且配置了 api-key 字段,则读取 api-key 作为 open-id
        ↓ (未找到/未配置)
第 3 步:检查用户是否在消息中明确提供了 open-id
        ↓ (未提供)
第 4 步:❗ 必须暂停执行,明确提示用户提供用户名或手机号作为 open-id

⚠️ 关键约束:

  • 禁止自行假设,自行推导,自行生成 open-id 值(如 openclaw-control-ui、default、fire123 等)
  • 禁止跳过 open-id 验证直接调用 API
  • 必须在获取到有效 open-id 后才能继续执行分析
  • 如果用户拒绝提供 open-id,说明用途(用于保存和查询烟火检测报告记录),并询问是否继续

  • 标准流程:
    1. 准备媒体输入
      • 提供监控视频文件路径、网络视频 URL 或现场图片
      • 确保监控画面完整覆盖监测区域,画面稳定
    2. 获取 open-id(强制执行)
      • 按上述流程控制获取 open-id
      • 如无法获取,必须提示用户提供用户名或手机号
    3. 执行烟火检测
      • 调用 -m scripts.fire_smoke_detection_analysis 处理素材(必须在技能根目录下运行脚本
      • 参数说明:
        • --input: 本地视频/图片文件路径(使用 multipart/form-data 方式上传)
        • --url: 网络视频/图片 URL 地址(API 服务自动下载)
        • --media-type: 媒体类型,可选值:video/image,默认 video
        • --sensitivity: 检测灵敏度,越高越容易报警,范围 0.1-0.9,默认 0.5
        • --open-id: 当前用户的 open-id(必填,按上述流程获取)
        • --list: 显示烟火检测历史分析报告列表清单(可以输入起始日期参数过滤数据范围)
        • --api-key: API 访问密钥(可选)
        • --api-url: API 服务地址(可选,使用默认值)
        • --detail: 输出详细程度(basic/standard/json,默认 json)
        • --output: 结果输出文件路径(可选)
    4. 查看分析结果
      • 接收结构化的烟火检测报告
      • 包含:监测基本信息、火焰检测结果、烟雾检测结果、火险等级、预警提示

资源索引

  • 必要脚本:见 scripts/fire_smoke_detection_analysis.py(用途:调用 API 进行烟火检测,本地文件使用 multipart/form-data 方式上传,网络 URL 由 API 服务自动下载)
  • 配置文件:见 scripts/config.py(用途:配置 API 地址、默认参数和媒体格式限制)
  • 领域参考:见 references/api_doc.md(何时读取:需要了解 API 接口详细规范和错误码时)

注意事项

  • 仅在需要时读取参考文档,保持上下文简洁
  • 支持格式:视频支持 mp4/avi/mov 格式,图片支持 jpg/png/jpeg 格式,最大 100MB
  • 本技能仅作火灾预警辅助,发现报警请立即确认并按应急预案处置
  • API 密钥可选,如果通过参数传入则必须确保调用鉴权成功,否则忽略鉴权
  • 禁止临时生成脚本,只能用技能本身的脚本
  • 传入的网络地址参数,不需要下载本地,默认地址都是公网地址,api 服务会自动下载
  • 当显示历史检测报告清单的时候,从数据 json 中提取字段 reportImageUrl 作为超链接地址,使用 Markdown 表格格式输出,包含" 报告名称"、"检测时间"、"火险等级"、"点击查看"四列,其中"报告名称"列使用烟火检测分析报告-{记录id}形式拼接, "点击查看"列使用 [🔗 查看报告](reportImageUrl) 格式的超链接,用户点击即可直接跳转到对应的完整报告页面。
  • 表格输出示例:
    报告名称检测时间火险等级点击查看
    烟火检测分析报告-202603121722000012026-03-12 17:22:00
    高风险🔗 查看报告

使用示例

# 检测本地监控视频(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.fire_smoke_detection_analysis --input /path/to/monitor.mp4 --media-type video --open-id openclaw-control-ui

# 检测现场图片,提高灵敏度(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.fire_smoke_detection_analysis --input /path/to/scene.jpg --media-type image --sensitivity 0.3 --open-id openclaw-control-ui

# 检测网络监控视频(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.fire_smoke_detection_analysis --url https://example.com/monitor.mp4 --media-type video --open-id openclaw-control-ui

# 显示历史检测报告/显示检测报告清单列表/显示历史烟火报告(自动触发关键词:查看历史检测报告、历史报告、检测报告清单等)
python -m scripts.fire_smoke_detection_analysis --list --open-id openclaw-control-ui

# 输出精简报告
python -m scripts.fire_smoke_detection_analysis --input video.mp4 --media-type video --open-id your-open-id --detail basic

# 保存结果到文件
python -m scripts.fire_smoke_detection_analysis --input video.mp4 --media-type video --open-id your-open-id --output result.json

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