# wy1iu/sphereface

Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.

Repository: https://github.com/wy1iu/sphereface
Canonical: https://ross.abutalabs.com/products/sphereface
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: face-recognition, caffe, sphereface, cvpr-2017, face-detection, angular-softmax, deep-learning
Last push: 2022-07-24T04:34:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3332, "days_push": 1501, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1606, forks 530 (observed 2026-08-28T04:05:10.440049+00:00)

## What it is
Official implementation of SphereFace (Deep Hypersphere Embedding for Face Recognition, CVPR 2017), built on Caffe with a full face recognition pipeline including face detection, alignment, and recognition. It introduces the A-Softmax (angular softmax) loss for learning discriminative angular face embeddings.

## Use cases
- train a face recognition model with angular margin loss
- reproduce SphereFace results on MegaFace and LFW benchmarks
- build a face verification pipeline with detection and alignment
- research angular margin loss functions for face embeddings
- extract face embeddings for identity matching
- compare A-Softmax against softmax for face recognition

## When to choose
- you need the original reference implementation of SphereFace/A-Softmax for research or paper reproduction
- you work with Caffe and want the complete detection-alignment-recognition pipeline
- you are studying angular margin losses in metric learning

## When to avoid
- you want a modern, easy-to-use PyTorch implementation (use OpenSphere instead)
- you need production face recognition with maintained dependencies
- you cannot build Caffe or lack GPU infrastructure

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, computer-vision, image-processing, machine-learning
- domain: computer-vision, deep-learning, image-processing, artificial-intelligence
- platform: python, cpp
- tags: face-recognition, sphereface, angular-softmax, caffe, cvpr-2017, face-detection, face-alignment, research-code, gpu, linux

## Member repositories
- wy1iu/sphereface (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:10.440049+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:52:15.414777+00:00, confidence not recorded.
  - readme: https://github.com/wy1iu/sphereface (fetched 2026-08-28T04:05:10.440049+00:00, sha bec0d0573878)
- Data as of 2026-08-30T08:39:29.467469+00:00.