UniFace: A Unified Face Analysis Library for Python

UniFace is a lightweight, production-ready Python library for face detection, recognition,
tracking, landmark analysis, face parsing, gaze estimation, and face attributes.

pip install "uniface[cpu]"          # CPU and Apple Silicon
pip install "uniface[gpu]"          # NVIDIA CUDA
pip install --pre "uniface[cpu]"    # latest pre-release

A first script

FaceAnalyzer runs detection, alignment and recognition in one call. Attribute models are opt-in.

import cv2
from uniface import FaceAnalyzer, FairFace

analyzer = FaceAnalyzer(predictors=[FairFace()])

for face in analyzer.analyze(cv2.imread("photo.jpg")):
    print(face.bbox, face.sex, face.age_group, face.embedding.shape)

bbox, confidence, landmarks and embedding are always set. Age, sex, race, emotion, quality and the face states stay None until you pass the predictor that fills them.

All fifteen tasks, and which model does each

Task	Models
Face Detection	RetinaFace, SCRFD, CenterFace, YOLOv5-Face, YOLOv8-Face, BlazeFace
Face Recognition	AdaFace, ArcFace, EdgeFace, MobileFace, SphereFace
Face Tracking	BYTETracker, persistent IDs across video frames
Facial Landmarks	2d106det (106), PIPNet (98 / 68), Face Mesh (468 / 478, 3D)
Face Parsing	BiSeNet (19 classes), XSeg masking
Portrait Matting	MODNet, trimap-free
Gaze Estimation	MobileGaze (ResNet-18 / 34 / 50, MobileNetV2)
Head Pose	6D rotation representation, pitch / yaw / roll
Demographics	AgeGender, FairFace (age group, sex, race)
Emotion	AffectNet-7 and AffectNet-8
Face States	FaceAttribNet: eyes, glasses, sunglasses, mask
Face Quality	eDifFIQA (T / S / M / L)
Anti-Spoofing	MiniFASNet liveness
Anonymization	5 blur methods
Vector Store	FAISS-backed embedding search

Runs on CPU, Apple Silicon and CUDA. Weights download on first use, verified by SHA-256.

Find and measure faces

Face Detection · docs

Facial Landmarks · docs

Face Mesh · docs

Face Quality · docs

Cut faces out

Face Parsing · docs

Face Segmentation · docs

Portrait Matting · docs

Read where a head is pointing

Head Pose · docs

Gaze Estimation · docs

Read a face

Age and Sex · docs

Emotion · docs

Face States · docs

Tell a real face from a replay

Anti-Spoofing · docs

Match a face, or hide one

Face Recognition · docs

Face Anonymization · docs

Get Started · Model Zoo · Notebooks · Model licences · Contributing · Discord · Issues

Runs on CPU, Apple Silicon and CUDA. Weights download on first use, verified by SHA-256.
UniFace is MIT; some pretrained weights are not, so check licences before shipping commercially.
Not affiliated with Uniface by Rocket Software.

Metadata

Release files for uniface 4.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for uniface 4.0.0
File	Size	Uploaded
uniface-4.0.0.tar.gz	134.8 kB	Aug 14, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for uniface 4.0.0
File	Interpreter	ABI	Platform	Reset
uniface-4.0.0-py3-none-any.whl 160.4 kB Aug 14, 2026	Python 3	none	any	Details

Total release size: 295.2 kB

Release files / uniface-4.0.0.tar.gz

Download URL	uniface-4.0.0.tar.gz
Size	134.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`12f90f11b4d921d8a54ce88c698c29c7da373afec465f280c4fc7c2d6a3ae543`
BLAKE2b-256 checksum How to use checksums	`ec37a3362a8e570799ff981bf0410a7492f50447d416b24f6a4da6123fd72312`
Upload date	Aug 14, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.11.15`

Release files / uniface-4.0.0-py3-none-any.whl

Download URL	uniface-4.0.0-py3-none-any.whl
Size	160.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`1dce410a2a1dddaec156b8d279cce5b8814c3e677d199e7d403fd7403852b66b`
BLAKE2b-256 checksum How to use checksums	`2170255794e8040fd9e08068056d1607147d3055b82890d8c95cd600b0eb8f95`
Upload date	Aug 14, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.11.15`