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

Deep Learningfacenet-retinaface-pytorch
Overview

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

目录

  1. 注意事项 Attention
  2. 所需环境 Environment
  3. 文件下载 Download
  4. 预测步骤 How2predict
  5. 参考资料 Reference

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

  1. 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。
  2. 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
}
  1. 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。
  2. 运行predict.py，输入下述文字，可直接预测。
img/zhangxueyou.jpg
  1. 利用video.py可进行摄像头检测。

Reference

https://github.com/biubug6/Pytorch_Retinaface

Owner
Bubbliiiing
Bubbliiiing
GitHub Repository
ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)

This is the project page for the paper: ISTR: End-to-End Instance Segmentation via Transformers, Jie Hu, Liujuan Cao, Yao Lu, ShengChuan Zhang, Yan Wa

Jie Hu 182 Dec 19, 2022
Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.

PAWS-TF 🐾 Implementation of Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples (PAWS)

Sayak Paul 43 Jan 08, 2023
Nsdf: A mesh SDF with just some code we can directly paste into our raymarcher

nsdf Representing SDFs of arbitrary meshes has been a bit tricky so far. Express

Jan Ivanecky 5 Feb 18, 2022
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning

Learning multiple gaits of quadruped robot using hierarchical reinforcement learning We propose a method to learn multiple gaits of quadruped robot us

Yunho Kim 17 Dec 11, 2022
Effect of Different Encodings and Distance Functions on Quantum Instance-based Classifiers

Effect of Different Encodings and Distance Functions on Quantum Instance-based Classifiers The repository contains the code to reproduce the experimen

Alessandro Berti 4 Aug 24, 2022
Vehicle direction identification consists of three module detection , tracking and direction recognization.

Vehicle-direction-identification Vehicle direction identification consists of three module detection , tracking and direction recognization. Algorithm

5 Nov 15, 2022
FAST-RIR: FAST NEURAL DIFFUSE ROOM IMPULSE RESPONSE GENERATOR

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

Anton Jeran Ratnarajah 89 Dec 22, 2022
The Pytorch code of "Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification", CVPR 2022 (Oral).

DeepBDC for few-shot learning        Introduction In this repo, we provide the implementation of the following paper: "Joint Distribution Matters: Dee

FeiLong 116 Dec 19, 2022
Dual Attention Network for Scene Segmentation (CVPR2019)

Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W

Jun Fu 2.2k Dec 28, 2022
This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation".

IR-GAIL This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation". Dependency The experiments are de

Zhao-Heng Yin 1 Jul 14, 2022
Self-Supervised Learning for Domain Adaptation on Point-Clouds

Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from

Idan Achituve 66 Dec 20, 2022
Generalized Proximal Policy Optimization with Sample Reuse (GePPO)

Generalized Proximal Policy Optimization with Sample Reuse This repository is the official implementation of the reinforcement learning algorithm Gene

Jimmy Queeney 9 Nov 28, 2022
Dilated RNNs in pytorch

PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi

Zalando Research 200 Nov 17, 2022
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

Alexander Amini 75 Dec 15, 2022
Wordle-solver - Wordle answer generation program in python

🟨 Wordle Solver 🟩 Wordle answer generation program in python ✔️ Requirements U

Dahyun Kang 4 May 28, 2022
Sequence Modeling with Structured State Spaces

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

HazyResearch 896 Jan 01, 2023
U-Net Implementation: Convolutional Networks for Biomedical Image Segmentation" using the Carvana Image Masking Dataset in PyTorch

U-Net Implementation By Christopher Ley This is my interpretation and implementation of the famous paper "U-Net: Convolutional Networks for Biomedical

Christopher Ley 1 Jan 06, 2022
Representing Long-Range Context for Graph Neural Networks with Global Attention

Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N

UC Berkeley RISE 67 Dec 30, 2022
Code for CPM-2 Pre-Train

CPM-2 Pre-Train Pre-train CPM-2 此分支为110亿非 MoE 模型的预训练代码，MoE 模型的预训练代码请切换到 moe 分支 CPM-2技术报告请参考link。 0 模型下载 请在智源资源下载页面进行申请，文件介绍如下： 文件名 描述 参数大小 100000.tar

Tsinghua AI 136 Dec 28, 2022
DL course co-developed by YSDA, HSE and Skoltech

Deep learning course This repo supplements Deep Learning course taught at YSDA and HSE @fall'21. For previous iteration visit the spring21 branch. Lec

Yandex School of Data Analysis 1.3k Dec 30, 2022