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Ai Intelligent Face Recognition

Name: Ai Intelligent Face Recognition
Author: yang1002378395-cmyk

作者 yang1002378395-cmyk · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

146

总下载

当前安装

版本数

在 OpenClaw 中安装

/install ai-face-recognition

功能描述

人脸识别，人脸检测 + 比对 + 搜索。

使用说明 (SKILL.md)

AI 智能人脸识别系统

描述

人脸识别，人脸检测 + 比对 + 搜索。

功能

人脸检测（人脸定位）
人脸比对（1:1比对）
人脸搜索（1:N搜索）
活体检测（防作弊）
人脸属性（年龄/性别）

定价

基础版：¥199/月（1 万次/月）
专业版：¥999/月（10 万次/月）
企业版：¥2999/月（无限次）

适用场景

门禁考勤
身份验证
安防监控
VIP识别

技术栈

Python + FastAPI
人脸识别引擎
活体检测
特征提取

安装

git clone https://github.com/openclaw-skills/ai-intelligent-face-recognition
cd ai-intelligent-face-recognition
pip install -r requirements.txt
python app.py

创建：2026-03-13 作者：OpenClaw Skills Team

安全使用建议

This skill is not self-contained: its instructions tell you to clone and run code from a GitHub repo that is not bundled or verified. Before installing or running it, (1) verify the GitHub repository exists and is maintained by a trusted author; (2) inspect the repository source code (especially app.py and requirements) to see what it does with images and network/credentials; (3) do not run arbitrary git clone && python app.py on a production machine—use an isolated VM or container and limit network access; (4) confirm legal/privacy implications for collecting and storing face data and obtain consent where required; (5) ask the skill author for an install spec, checksums, or a packaged release if you need to run this in a trusted environment. If you cannot review the repo and its behavior, treat this skill as risky.

功能分析

Type: OpenClaw Skill Name: ai-face-recognition Version: 1.0.0 The skill bundle contains only metadata and documentation (SKILL.md, skill.json, _meta.json) for an AI face recognition system. It lacks executable code and does not contain any malicious instructions, prompt injections, or suspicious data exfiltration patterns. The installation instructions provided are standard for a Python-based project.

能力评估

ℹ Purpose & Capability

Name/description, features, and skill.json align with a face-recognition service. However, the skill bundle contains no code or packaged binaries but the SKILL.md instructs cloning https://github.com/openclaw-skills/ai-intelligent-face-recognition and running app.py — the manifest does not declare git, python, or pip as required binaries even though the install steps need them.

⚠ Instruction Scope

The SKILL.md tells the operator to download and execute external code (git clone + pip install -r requirements.txt + python app.py). That grants the remote repository arbitrary runtime access when executed. The instructions do not mention data handling, where images are sent/stored, or any privacy/consent controls; they also make implicit assumptions about available tooling and network access.

⚠ Install Mechanism

There is no formal install spec in the registry; instead the README-style SKILL.md suggests cloning a GitHub repo. Downloading and running code from an external repo is higher-risk than an instruction-only skill that operates purely with on-agent logic. Although GitHub is a common host, the skill bundle provides no checksum, release link, or verified provenance.

ℹ Credentials

The skill declares no required environment variables or credentials, which is proportionate to a local/offline face-recognition demo. However, running the suggested external app may later require service keys, storage credentials, or network connectivity; the SKILL.md does not disclose these possibilities. Also required binaries (git, python, pip) are omitted from the declared requirements.

✓ Persistence & Privilege

The skill does not request always:true and does not declare elevated or persistent privileges. There is no evidence it attempts to modify other skills or global agent settings from the provided files.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install ai-face-recognition
安装完成后，直接呼叫该 Skill 的名称或使用 /ai-face-recognition 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

- Initial release of ai-intelligent-face-recognition v1.0.0 - Provides face detection, 1:1 face comparison, 1:N face search, liveness detection, and face attribute analysis (age/gender) - Outlines multiple pricing tiers for different usage needs - Describes main use cases: access control, identity verification, security monitoring, and VIP recognition - Specifies technology stack: Python, FastAPI, and face recognition engine

元数据

Slug ai-face-recognition

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题