Install
openclaw skills install smyx-uav-farm-health-index-map-analysisUsing multispectral or high-resolution RGB cameras mounted on agricultural UAVs to capture orthophotos or mosaics of farmland, AI models compute vegetation indices (e.g., NDVI, NDRE) and generate a farm health-index heatmap, where colors distinguish crop vigor (red = poor, yellow = medium, green = healthy). This skill quickly identifies problem zones (e.g., nutrient/water deficiency, pests/disease, weeds) and guides precision variable-rate fertilization and crop-protection operations. Application scenarios: large-scale farms, agricultural cooperatives, drone crop-protection services, agricultural research. After the UAV flight uploads imagery, the system automatically produces a health-index map, outputs coordinates and area of problem zones, and pushes suggestions (e.g., 'NDVI is low in the northeast corner, recommend on-site pest inspection'). Skill features: traditional manual field scouting is slow and tends to miss early stress. UAV-based health-index heatmaps drastically improve monitoring efficiency, enable precise variable-rate operations, and save agro-inputs. A core technology of smart agriculture. | 通过农业无人机平台搭载的多光谱或高分辨率RGB相机,采集农田的正射影像或拼接图,利用AI模型计算植被指数(如归一化植被指数NDVI、归一化红边指数NDRE等),生成农田健康指数热力图,用颜色区分作物长势(红色代表健康差、黄色代表中等、绿色代表健康)。该技能可快速识别问题区域(如缺肥、缺水、病虫害、杂草),指导精准变量施肥或植保作业。应用场景:规模化农场、农业合作社、植保无人机服务、农业科研。无人机飞行后上传影像,系统自动生成健康指数图,输出问题区域的坐标和面积,并推送建议(如'东北角区域NDVI偏低,建议实地检查虫害')。技能特点:传统农田巡查依赖人工,效率低且难以发现早期胁迫。通过无人机快速生成健康指数热力图,可大幅提高监测效率,实现精准农业变量作业,节省农药肥料。该技能是智慧农业的核心技术之一。
openclaw skills install smyx-uav-farm-health-index-map-analysisUsing multispectral or high-resolution RGB cameras mounted on agricultural UAVs to capture orthophotos or mosaics of farmland, AI models compute vegetation indices (e.g., NDVI, NDRE) and generate a farm health-index heatmap, where colors distinguish crop vigor (red = poor, yellow = medium, green = healthy). This skill quickly identifies problem zones (e.g., nutrient/water deficiency, pests/disease, weeds) and guides precision variable-rate fertilization and crop-protection operations. Application scenarios: large-scale farms, agricultural cooperatives, drone crop-protection services, agricultural research. After the UAV flight uploads imagery, the system automatically produces a health-index map, outputs coordinates and area of problem zones, and pushes suggestions (e.g., 'NDVI is low in the northeast corner, recommend on-site pest inspection'). Skill features: traditional manual field scouting is slow and tends to miss early stress. UAV-based health-index heatmaps drastically improve monitoring efficiency, enable precise variable-rate operations, and save agro-inputs. A core technology of smart agriculture.
通过农业无人机平台搭载的多光谱或高分辨率RGB相机,采集农田的正射影像或拼接图,利用AI模型计算植被指数(如归一化植被指数NDVI、归一化红边指数NDRE等),生成农田健康指数热力图,用颜色区分作物长势(红色代表健康差、黄色代表中等、绿色代表健康)。该技能可快速识别问题区域(如缺肥、缺水、病虫害、杂草),指导精准变量施肥或植保作业。应用场景:规模化农场、农业合作社、植保无人机服务、农业科研。无人机飞行后上传影像,系统自动生成健康指数图,输出问题区域的坐标和面积,并推送建议(如'东北角区域NDVI偏低,建议实地检查虫害')。技能特点:传统农田巡查依赖人工,效率低且难以发现早期胁迫。通过无人机快速生成健康指数热力图,可大幅提高监测效率,实现精准农业变量作业,节省农药肥料。该技能是智慧农业的核心技术之一。
假设你是一个专业的精准农业 AI。你的任务是接收无人机航拍的多光谱(或高分辨率 RGB)图像,经过拼接和几何校正后,计算植被指数(如 NDVI、NDRE、OSAVI 等),生成农田健康指数热力图,并识别出健康异常区域(如低植被指数区域),输出其位置和面积。不要提供具体的农事操作建议(如施肥量、农药品种),仅输出基于指数的评估结果。
python -m scripts.smyx_uav_farm_health_index_map_analysis --list --open-id 参数调用 API
查询云端的历史报告数据requests>=2.28.0
在执行无人机农田健康指数图生成前,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:
-m scripts.smyx_uav_farm_health_index_map_analysis 处理输入(必须在技能根目录下运行脚本)--input: 本地无人机正射影像/拼接图/视频文件路径--url: 网络无人机正射影像/拼接图/视频 URL 地址(API 服务自动下载)--pet-type: 类别标识,农田航拍场景默认 other--open-id: 当前用户的 open-id(必填,按上述流程获取)--list: 显示农田健康指数图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)无人机农田健康指数图报告-{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。| 报告名称 | 作物种类 | 分析时间 | 点击查看 |
|---|---|---|---|
| 无人机农田健康指数图报告-20260312172200001 | 小麦 | 2026-03-12 17:22:00 | 🔗 查看报告 |
# 分析本地无人机正射影像(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.smyx_uav_farm_health_index_map_analysis --input /path/to/orthomosaic.tif --open-id your-open-id
# 分析网络无人机航拍影像/视频(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.smyx_uav_farm_health_index_map_analysis --url https://example.com/orthomosaic.tif --open-id your-open-id
# 显示历史健康指数图报告/植被指数报告清单(自动触发关键词:查看农田健康指数历史报告、植被指数报告清单等)
python -m scripts.smyx_uav_farm_health_index_map_analysis --list --open-id your-open-id
# 输出精简报告
python -m scripts.smyx_uav_farm_health_index_map_analysis --input ortho.tif --open-id your-open-id --detail basic
# 保存结果到文件
python -m scripts.smyx_uav_farm_health_index_map_analysis --input ortho.tif --open-id your-open-id --output result.json