@Sn0wbrave: If you're working on Computer Vision projects, this project is worth paying attention to UniFace is an open-source Pyth…

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Summary

UniFace is an open-source Python library that provides a unified API for face detection, recognition, tracking, gaze estimation, and other tasks, designed for computer vision projects.

If you're working on Computer Vision projects, this project is worth paying attention to UniFace is an open-source Python library that combines face detection, recognition, tracking, gaze tracking, and Anti-Spoofing into a single API. https://github.com/yakhyo/uniface :::
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If you’re working on Computer Vision projects, this project is worth paying attention to UniFace is an open-source Python library that combines face detection, recognition, tracking, gaze tracking, and Anti-Spoofing into a single API. https://github.com/yakhyo/uniface :::


yakhyo/uniface

Source: https://github.com/yakhyo/uniface

UniFace: A Unified Face Analysis Library for Python

PyPI Version Python Version License Github Build Status PyPI Downloads Kaggle Badge

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.

Get Started   Model Zoo   Notebooks   Full Docs

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
TaskModels
Face DetectionRetinaFace, SCRFD, CenterFace, YOLOv5-Face, YOLOv8-Face, BlazeFace
Face RecognitionAdaFace, ArcFace, EdgeFace, MobileFace, SphereFace
Face TrackingBYTETracker, persistent IDs across video frames
Facial Landmarks2d106det (106), PIPNet (98 / 68), Face Mesh (468 / 478, 3D)
Face ParsingBiSeNet (19 classes), XSeg masking
Portrait MattingMODNet, trimap-free
Gaze EstimationMobileGaze (ResNet-18 / 34 / 50, MobileNetV2)
Head Pose6D rotation representation, pitch / yaw / roll
DemographicsAgeGender, FairFace (age group, sex, race)
EmotionAffectNet-7 and AffectNet-8
Face StatesFaceAttribNet: eyes, glasses, sunglasses, mask
Face QualityeDifFIQA (T / S / M / L)
Anti-SpoofingMiniFASNet liveness
Anonymization5 blur methods
Vector StoreFAISS-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.

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