face-api.js vs face_recognition
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
JavaScript library that detects faces and recognizes facial features in browsers and Node.js.
Open source · MIT
A Python library and command-line tool for finding and recognizing faces in photos.
The short answer
Choose face-api.js if you need…
- Web developers adding face detection to a browser page
- Developers building webcam demos that track faces or expressions
- Node.js developers who want server-side face detection with tensorflow.js
- Learners exploring face recognition in JavaScript
Choose face_recognition if you need…
- Python developers prototyping photo sorting or face matching
- Hobbyists who want to label people across a folder of personal photos
- Researchers who need a simple baseline face recognition pipeline
- Developers adding face detection to a script or small app
Side-by-side
| face-api.js | face_recognition | |
|---|---|---|
| Type | Library | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 18k | 56.9k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | TypeScript | Python |
| Last code update | 3 years ago | 4 months ago |
What each one is
face-api.js
face-api.js is a JavaScript library for finding faces in images and video and reading facial features from them, such as landmarks, expressions, and estimated age and gender. It runs on top of tensorflow.js, so it can work in a web browser or in Node.js. Developers use it to add face-related features to web pages or server-side scripts without writing their own machine learning code.
face_recognition
face_recognition is a Python library that detects faces in images, locates facial features like eyes and nose, and compares faces to tell whether two images show the same person. It also ships a command-line tool that can match a folder of unknown photos against a folder of labeled people. The README says it is built on dlib's deep-learning face recognition model, which it reports at 99.38% accuracy on the Labeled Faces in the Wild benchmark.
Best for
face-api.js
- Web developers adding face detection to a browser page
- Developers building webcam demos that track faces or expressions
- Node.js developers who want server-side face detection with tensorflow.js
- Learners exploring face recognition in JavaScript
face_recognition
- Python developers prototyping photo sorting or face matching
- Hobbyists who want to label people across a folder of personal photos
- Researchers who need a simple baseline face recognition pipeline
- Developers adding face detection to a script or small app
Strengths
face-api.js
- Runs directly in the browser, so images can stay on the user's device
- Covers several tasks in one API: detection, landmarks, recognition, expressions, age and gender
- MIT licensed with a large community and many tutorials listed in the README
face_recognition
- Very short Python API for detection, landmarks and comparison
- Command-line tools work on whole folders of images
- MIT licensed and widely used, with a large star count
Not ideal for
face-api.js
- Projects needing the latest research models, since the README does not describe model updates and the last push shown is from January 2024
- Teams that need a fully supported commercial product with guaranteed accuracy, since the README makes no such claims
- Anyone who needs face identification at large scale, where a dedicated server-side system would be more appropriate
face_recognition
- Anyone needing official Windows support, since the README says Windows is not officially supported
- Projects that need to run without installing dlib and cmake, since installation is the hardest part according to the README
- Surveillance or identification of people without their consent, which raises serious privacy and legal concerns the README does not address
Trade-offs
face-api.js
- Model files must be downloaded and served alongside the app, which adds load size
- The README notes that installing the optional native tfjs-node binding is recommended for speed in Node.js, which adds setup complexity
- The README is truncated and does not fully describe accuracy or limitations of each model
face_recognition
- Installation requires dlib and cmake, which the README describes as a multi-step process
- Windows is not officially supported and the README notes a silent failure bug on Jetson Nano unless a dlib line is edited
- README examples and install instructions reference older Python versions (3.3+ or 2.7), so modern setup may need checking
Getting started
face_recognition
Install cmake (macOS, per README)
brew install cmakeInstall the library from PyPI
pip3 install face_recognitionFrequently asked questions
What is the difference between face-api.js and face_recognition?
face-api.js: JavaScript library that detects faces and recognizes facial features in browsers and Node.js. face_recognition: A Python library and command-line tool for finding and recognizing faces in photos. face-api.js suits web developers adding face detection to a browser page, while face_recognition suits python developers prototyping photo sorting or face matching.
Are face-api.js and face_recognition free?
face-api.js: Free and open source. face_recognition: Free and open source.
Is face-api.js or face_recognition more popular?
face_recognition has more GitHub stars (56.9k) than face-api.js (18k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to face-api.js and face_recognition?
Other options people compare them with include deepface.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.