cv_manual_face-recognition_frfm

iic/cv_manual_face-recognition_frfm

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稳定调用及效果更好的API，详见视觉开放智能平台：人脸比对1:1、口罩人脸比对1:1、人脸搜索1:N、公众人物识别、明星识别。口罩人脸识别模型FRFM基于ArcFace框架，网络结构为NAS搜索出来的large model，训练数据使用了Glint360数据，同时加了数据增强的策略，包括random erasing，cutout策略和以一定概率增加口罩, 大大增强了在口罩数据集上的精度, 在MFR数据集中性能可以在96以上，同时在标准人脸识别任务上的精度也有提高。

Image Analysis

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Model details

模型介绍

中文整理

FRFM模型介绍

稳定调用及效果更好的API，详见视觉开放智能平台：人脸比对1:1、口罩人脸比对1:1、人脸搜索1:N、公众人物识别、明星识别。

口罩人脸识别模型FRFM。

模型描述

口罩人脸识别模型FRFM基于ArcFace框架，网络结构为NAS搜索出来的large model，训练数据使用了Glint360数据，同时加了数据增强的策略，包括random erasing，cutout策略和以一定概率增加口罩, 大大增强了在口罩数据集上的精度, 在MFR数据集中性能可以在**96以上**，同时在标准人脸识别任务上的精度也有提高。

模型结构

模型使用方式和使用范围

本模型可以检测输入图片中带口罩和不戴口罩人脸的特征

代码范例

使用方式

推理：输入经过对齐的人脸图片(112x112)，返回人脸特征向量(1024维)，为便于体验，集成了人脸检测和关键点模型RetinaFace，输入两张图片，各自进行人脸检测选择最大脸并对齐后提取特征，然后返回相似度比分

目标场景

人脸识别应用广泛，如考勤，通行，人身核验，智慧安防等场景

模型局限性及可能偏差

由于模型较大，目前仅支持GPU推理。

当前版本在python 3.7环境测试通过，其他环境下可用性待测试

模型性能指标

Method IJBC(1e-5) IJBC(1e-4) MFR-ALL

----------- ------------ ------------ ------------

FaceMask - - 96+

来源说明

本模型及代码来自达摩院和Insightface联合研发技术

优先采用原作者提供的中文模型卡片；仅有英文说明时由闲社AI翻译整理。重要参数、许可证和商用范围请以原文为准。

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使用前须知

运行环境

运行模型需要的设备、工具与依赖，以原作者说明为准。

授权范围

是否允许商用、修改和分发，请查看模型许可证。

闲社提供资料与镜像下载方法，不代表已运行模型或完成安全审计。下载的代码应先检查，再执行。

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