face_recognition
56,892
Stars
13,656
Forks
1,536
Watchers
833
Open Issues
MIT
许可证
Python
语言
2017-03-03
创建时间
2026-06-25
最近更新
项目能做什么
极为简便的人脸识别 API,支持 Python 和命令行调用。
来源:基于仓库元数据
· 内容以仓库实际 README 为准
使用说明 查看原始 README 原仓库文档
中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
# Face Recognition
_You can also read a translated version of this file [in Chinese 简体中文版](https://github.com/ageitgey/face_recognition/blob/master/README_Simplified_Chinese.md) or [in Korean 한국어](https://github.com/ageitgey/face_recognition/blob/master/README_Korean.md) or [in Japanese 日本語](https://github.com/m-i-k-i/face_recognition/blob/master/README_Japanese.md)._
Recognize and manipulate faces from Python or from the command line with
the world's simplest face recognition library.
Built using [dlib](http://dlib.net/)'s state-of-the-art face recognition
built with deep learning. The model has an accuracy of 99.38% on the
Labeled Faces in the Wild benchmark (see the [LFW paper (PDF)](https://people.cs.umass.edu/~elm/papers/lfw.pdf)).
This also provides a simple `face_recognition` command line tool that lets
you do face recognition on a folder of images from the command line!
[](https://pypi.python.org/pypi/face_recognition)
[](https://github.com/ageitgey/face_recognition/actions?query=workflow%3ACI)
[](http://face-recognition.readthedocs.io/en/latest/?badge=latest)
## Features
#### Find faces in pictures
Find all the faces that appear in a picture:

```python
import face_recognition
image = face_recognition.load_image_file("your_file.jpg")
face_locations = face_recognition.face_locations(image)
```
#### Find and manipulate facial features in pictures
Get the locations and outlines of each person's eyes, nose, mouth and chin.

```python
import face_recognition
image = face_recognition.load_image_file("your_file.jpg")
face_landmarks_list = face_recognition.face_landmarks(image)
```
Finding facial features is super useful for lots of important stuff. But you can also use it for really stupid stuff
like applying [digital make-up](https://github.com/ageitgey/face_recognition/blob/master/examples/digital_makeup.py) (think 'Meitu'):

#### Identify faces in pictures
Recognize who appears in each photo.

```python
import face_recognition
known_image = face_recognition.load_image_file("biden.jpg")
unknown_image = face_recognition.load_image_file("unknown.jpg")
biden_encoding = face_recognition.face_encodings(known_image)[0]
unknown_encoding = face_recognition.face_encodings(unknown_image)[0]
results = face_recognition.compare_faces([biden_encoding], unknown_encodi
阅读完整原文
商业机会分析 规则生成(AI 未配置)
综合评分 46.0 分。该项目在“个人可实施性”维度得 20 分,“付费可能性”维度得 52.0 分,差异化空间 64.0 分(评分依据见评分卡)。
将 face_recognition 改造为垂直场景 SaaS
| 产品构想 | 保留核心能力,针对某一类用户(如某行业团队)做托管版,收取月费。 |
| 目标用户 | 有该需求的中小团队 / 独立站长 |
| 难度/周期 | 较高 · 2~4 周(MVP) |
| 收费模式 | 订阅制(如 ¥29~99/月) |
| 竞争风险 | 需验证付费意愿;注意许可证合规 |
| 依据 | 数据支持的判断:许可证与关键词显示存在商用与付费场景 |
面向细分需求的二次开发产品
| 产品构想 | 基于 face_recognition 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。 |
| 目标用户 | 该细分场景用户 |
| 难度/周期 | 中 · 2~6 周 |
| 收费模式 | 买断制 / 订阅制 / 广告 |
| 竞争风险 | 细分需求规模需验证 |
| 依据 | AI 推测:基于项目主题标签的判断 |
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心
竞品与相似项目 GitHub Search 真实检索
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|---|---|---|---|
| CMU-Perceptual-Computing-Lab/openpose | 中文介绍暂未生成 OpenPose: Real-time multi-person keypoint detection library |
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| deepinsight/insightface | 中文介绍暂未生成 State-of-the-art 2D and 3D Face Analysis Project |
30,192 | Python |
| justadudewhohacks/face-api.js | 中文介绍暂未生成 JavaScript API for face detection and face recognition in th |
17,995 | TypeScript |
| PaddlePaddle/PaddleDetection | 中文介绍暂未生成 Object Detection toolkit based on PaddlePaddle. It supports |
14,469 | Python |
| davidsandberg/facenet | 中文介绍暂未生成 Face recognition using Tensorflow |
14,363 | Python |
| ShiqiYu/libfacedetection | 中文介绍暂未生成 An open source library for face detection in images. The fac |
12,818 | C++ |
以上为通过 GitHub 官方 Search API 检索的相似项目,功能差异与优劣势需进一步人工确认,配置 AI 后可生成对比分析。
项目优势与风险
| 技术成熟度 | 创建于 2017-03-03,最近推送 2026-06-25,发布过 2 个 Release |
| 社区活跃 | Star 56,892 / Fork 13,656 / Issue 833(数据支持,可自行核实) |
| 许可证 | MIT |
| 主要风险 | 上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价 |
安装与使用
快速开始(以仓库 README 为准)
git clone https://github.com/ageitgey/face_recognition.git cd face_recognition # 请阅读仓库 README 获取确切安装步骤(依赖、配置、启动命令)
术语说明:Docker=应用容器(把程序和依赖打包运行);API Key=调用外部服务的密钥;Git Clone=把仓库代码下载到本地。常见错误:API Key 未配置 / 端口占用 / 数据库连接失败,多数项目在 README 的 Troubleshooting 章节有说明。