这是一个利用facenet和retinaface实现人脸识别的库，可以进行在线的人脸识别。

Last update: Dec 30, 2022

Overview

Facenet+Retinaface：人脸识别模型在Pytorch当中的实现

注意事项

该库中包含了两个网络，分别是retinaface和facenet。二者使用不同的权值。在使用网络时一定要注意权值的选择，以及主干与权值的匹配。

所需环境

pytorch==1.2.0

文件下载

预测所需的权值文件可以在百度云下载。
链接: https://pan.baidu.com/s/1iTo4_x0DHg0GoTUQWduMZw 提取码: dmw6

预测步骤

本项目自带主干为mobilenet的retinaface模型与facenet模型。可以直接运行，如果想要使用主干为resnet50的retinafa和主干为inception_resnetv1的facenet模型需要。
在retinaface.py文件里面，在如下部分修改model_path和backbone使其对应训练好的文件。

_defaults = {
    "retinaface_model_path" : 'model_data/Retinaface_mobilenet0.25.pth',
    #-----------------------------------#
    #   可选retinaface_backbone有
    #   mobilenet和resnet50
    #-----------------------------------#
    "retinaface_backbone"   : "mobilenet",
    "confidence"            : 0.5,
    "iou"                   : 0.3,
    #----------------------------------------------------------------------#
    #   是否需要进行图像大小限制。
    #   输入图像大小会大幅度地影响FPS，想加快检测速度可以减少input_shape。
    #   开启后，会将输入图像的大小限制为input_shape。否则使用原图进行预测。
    #   会导致检测结果偏差，主干为resnet50不存在此问题。
    #   可根据输入图像的大小自行调整input_shape，注意为32的倍数，如[640, 640, 3]
    #----------------------------------------------------------------------#
    "retinaface_input_shape": [640, 640, 3],
    #-----------------------------------#
    #   是否需要进行图像大小限制
    #-----------------------------------#
    "letterbox_image"       : True,
    
    "facenet_model_path"    : 'facenet_inception_resnetv1.pth',
    #-----------------------------------#
    #   可选facenet_backbone有
    #   mobilenet和inception_resnetv1
    #-----------------------------------#
    "facenet_backbone"      : "inception_resnetv1",
    "facenet_input_shape"   : [160,160,3],
    "facenet_threhold"      : 0.9,

    "cuda"                  : True
}

运行encoding.py，对face_dataset里面的图片进行编码，face_dataset的命名规则为XXX_1.jpg、XXX_2.jpg。最终在model_data文件夹下生成对应的数据库人脸编码数据文件。
运行predict.py，输入下述文字，可直接预测。

img/zhangxueyou.jpg

利用video.py可进行摄像头检测。

Reference

https://github.com/biubug6/Pytorch_Retinaface

这是一个利用facenet和retinaface实现人脸识别的库，可以进行在线的人脸识别。

Related tags

Overview

Facenet+Retinaface：人脸识别模型在Pytorch当中的实现

目录

注意事项

所需环境

文件下载

预测步骤

Reference

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Bubbliiiing

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这是一个利用facenet和retinaface实现人脸识别的库，可以进行在线的人脸识别。

Related tags

Overview

Facenet+Retinaface：人脸识别模型在Pytorch当中的实现

目录

注意事项

所需环境

文件下载

预测步骤

Reference

Owner

Bubbliiiing

Neural Style and MSG-Net

AlphaBot2 Pi Core software for interfacing with the various components.

Code for 'Self-Guided and Cross-Guided Learning for Few-shot segmentation. (CVPR' 2021)'

DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

Official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th ICML Workshop on AutoML)

Sequence-to-Sequence learning using PyTorch

PyTorch implementation for the paper Pseudo Numerical Methods for Diffusion Models on Manifolds

Code for EMNLP 2021 paper: "Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training"

HackBMU-5.0-Team-Ctrl-Alt-Elite - HackBMU 5.0 Team Ctrl Alt Elite

Six - a Python 2 and 3 compatibility library

Implementation of the Swin Transformer in PyTorch.

Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core

最新版本yolov5+deepsort目标检测和追踪，支持5.0版本可训练自己数据集

Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the Machine Learning 4 Health Workshop

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