Giter VIP home page Giter VIP logo

real-world-masked-face-dataset's Introduction

口罩遮挡人脸数据集(Real-World Masked Face Dataset,RMFD)

近期全球新型冠状病毒肆虐,疫情严重地区(如武汉)几乎人人戴口罩,具有海量样本基数。收集样本建立全球最大口罩人脸数据集,并向社会开放,为当前及今后可能的类似公共安全事件智能管控积累数据资源。基于口罩人脸数据,设计相应口罩遮挡人脸检测和识别算法,帮助社区封闭时的人员进出管控,车站、机场的人脸识别闸机以及人脸门禁考勤设备的升级,适应行人口罩蒙面遮挡的应用环境。

发起单位:武汉大学国家多媒体软件工程技术研究中心

联系人:黄宝金,联系邮箱:[email protected]

为了进一步扩充数据集,欢迎大家将个人收集到的戴口罩图片,通过邮件的方式发送到 [email protected],我们会对收到的图片统一处理。

数据集下载

部分原始样本已上传本github站点,RMFD_part_1可直接下载使用,RMFD_part_2 (4个压缩文件) 和RMFD_part_3 (3个压缩文件) 需要下载全部压缩文件后,再进行解压。也可以从下方的地址下载:

https://drive.google.com/open?id=1kZAIiv34Iav9Vt8BB101FXo4KoEClpx9

已标注数据集说明如下:(区别于github中raw samples) 不同于人脸口罩识别(或检测)数据集,口罩人脸识别样本集须得包含同一人的多张戴口罩与未戴口罩的人脸图像,为此,我们建立了两种口罩人脸识别样本集。

(1) 真实口罩人脸识别数据集:从网络爬取样本,经过整理、清洗和标注后,含525人的5千张口罩人脸、9万正常人脸。

下载地址: https://pan.baidu.com/s/1XvGepj84SCA9rlVb9rGhEQ 密码:j3aq

或者 https://drive.google.com/open?id=1UlOk6EtiaXTHylRUx2mySgvJX9ycoeBp

(2) 模拟口罩人脸识别数据集: 给公开数据集中的人脸戴上口罩,得到1万人、50万张人脸的模拟口罩人脸数据集。

WebFace模拟口罩人脸数据集:

下载地址:https://pan.baidu.com/s/1O1lk1Yqp-yao7RTZomuUfw 密码:bts7

LFW模拟口罩人脸数据集:

下载地址:https://pan.baidu.com/s/1ULHV6ShpnPUzn5eqPUYu0w 密码:q7cf

AgeDB-30模拟口罩人脸数据集:

下载地址:https://pan.baidu.com/s/1Eaoc90aoh9vf-8N2c-mv7A 密码: jy5j

CFP-FP模拟口罩人脸数据集:

下载地址:https://pan.baidu.com/s/14py4YFNO6YDhm6_qCaSyuA 密码:ebd8

(3)真实口罩人脸验证数据集,包括426个人的4015张人脸图像,组合成3589对相同身份和3589对不同身份的人脸样本对(口罩人脸/正常人脸)。

下载地址:链接:https://pan.baidu.com/s/1pI6WIvkac74Ec7LfD41LSg 密码:tbe6

口罩人脸识别

基于建立的数据集,设计和训练了面部-眉眼多粒度口罩人脸识别模型,数据集上的识别精度达到95%,部分动态视频演示见:

链接: https://pan.baidu.com/s/1P0PiWFNT1z_TcCj8vo43ow 提取码: acwe

image image image

相关工作

https://arxiv.org/abs/2003.09093

原始样本示例:

image image image image image image image image

Real-World Masked Face Dataset(RMFD)

Because of the recent epidemic of COVID-19 virus around the world, people across the country wear masks and there appear a large number of masked face samples. We thus created the world's largest masked face dataset to accumulate data resources for possible intelligent management and control of similar public safety events in the future. Based on masked face dataset, corresponding masked face detection and recognition algorithms are designed to help people in and out of the community when the community is closed. In addition, the upgrade of face recognition gates, facial attendance machines, and facial security checks at train stations is adapted to the application environment of pedestrian wearing masks.

Sponsor: National Engineering Research Center for Multimedia Software (NERCMS), School of Computer Science, Wuhan University

Contact: Baojin Huang, Email: [email protected]

In order to further expand this dataset, everyone is welcome to send personally collected pictures of masks to [email protected] by email, and we will process the received pictures uniformly.

Download Datasets

Part of the original samples has been uploaded to this github website. RFMD_part_1 can be downloaded directly. RFMD_part_2 (4 compressed files) and RFMD_part_3 (3 compressed files) need to download all compressed files before decompressing them.You can also download these datasets from the link below.

Download link: https://drive.google.com/open?id=1kZAIiv34Iav9Vt8BB101FXo4KoEClpx9

More labeled face samples are illustrated as follows: (different from raw samples in github) Different from the facial mask recognition (or detection) dataset, the masked face recognition dataset must include multiple masked and unmasked face images of the same subject. To this end, we have established two kinds of masked face recognition datasets.

(1) Real-world masked face recognition dataset: We crawled the samples from the website. After cleaning and labeling, it contains 5,000 masked faces of 525 people and 90,000 normal faces.

Download link: https://pan.baidu.com/s/1XvGepj84SCA9rlVb9rGhEQ Password: j3aq

or https://drive.google.com/open?id=1UlOk6EtiaXTHylRUx2mySgvJX9ycoeBp

(2) Simulated masked face recognition datasets: We put on the masks on the faces in the public face datasets, and obtained the simulated masked face dataset of 500,000 faces of 10,000 subjects.

WebFace simulated masked face dataset: https://pan.baidu.com/s/1O1lk1Yqp-yao7RTZomuUfw Password:bts7

LFW simulated masked face dataset: https://pan.baidu.com/s/1ULHV6ShpnPUzn5eqPUYu0w Password:q7cf

AgeDB-30 simulated masked face dataset: https://pan.baidu.com/s/1Eaoc90aoh9vf-8N2c-mv7A Password: jy5j

CFP-FP simulated masked face dataset: https://pan.baidu.com/s/14py4YFNO6YDhm6_qCaSyuA Password:ebd8

(3) Real-world masked face verification dataset contains 4015 face images of 426 people. The dataset is further organized into 7178 masked and non-masked sample pairs, including 3589 pairs of the same identity and 3589 pairs of different identities.

https://pan.baidu.com/s/1pI6WIvkac74Ec7LfD41LSg Password: tbe6

Masked Face Recognition

Based on the constructed datasets, we designed and trained a face-eye-based multi-granularity masked face recognition model. The face identification accuracy on the dataset is over 95%, and some real-time video demos are as follows:

Download link: https://pan.baidu.com/s/1P0PiWFNT1z_TcCj8vo43ow Password: acwe

image image image

Related Work

https://arxiv.org/abs/2003.09093

Examples of Raw Samples

image image image image image image image image

real-world-masked-face-dataset's People

Contributors

x-zhangyang avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

real-world-masked-face-dataset's Issues

Could you please share the link for the version of the CASIA_WebFace without Mask?

Could you please share the link for the version of the CASIA_WebFace without Mask?

Because there are several versions for CASIA_WebFace. As far as I know, one version has only 455594 images, which is usually named 'Clean' version. The other two versions always are named raw_1 and raw_2 versions. For both of them, the number of images is 494414. Which version are you using to generate the simulated Mask database?

Could you please share your database for the original CASIA_WebFace(which has no mask)?

part1口罩人脸识别数据集错误太多,慎用

举几个例子,比如with mask部分的xiaoshenyang、liyifeng、chenweiting等等
如果这个数据作者还维护的话,希望可以清洗后重新发布。
给使用者提个醒,切勿直接拿来训练。

how to run this code?

Hi,

I download this code with the help of one of my Chinese friend, but how to run this, also downloaded dlib dependencies, please tell me what arguments to pass and other dependencies.

Thank you for beautiful work

Bug in Rotation in wearmask.py

In line 188 of wearmask.py, PIL's rotate function expects the rotation angle to be in degrees, but as np.arctan2 returns in units of radians, there is almost no rotation applied any time. This makes the code not work properly for tilted faces. Please look into it.

How to align the Masked LFW and Masked CASIA-WebFace database?

As we all know, the original LFW and CASIA-WebFace datasets have a dimension of 250*250.

Before carrying out the face recognition task, we should always perform face alignment on the original LFW and CACIA-WebFace dataset. For example, after face alignment, we obtained the alignment version datasets (the dimension of 112112) which have been aligned if I need to feed 112112 to neural network architecture.

I found that your Masked LFW and Masked CASIA-WebFace database have a dimension of 128*128.

Could you please explain more details about the detection and alignment you performed during the process of wearing the mask?

Do we still need to align again for masked face data? Or I do not need to perform face alignment again?

MFDD Dataset

I am only interested in Face Mask Detection not recognition, so Where can i find the MFDD Dataset mentioned in the research paper along with the labels for the bounding box of the mask?

测试协议

请问是否有提供统一的测试协议和测试脚本呢?LFW-Mask这类测试集,比对的是真是人脸和口罩人脸吗?

License of the datasets for commercial purpose (COVID usecases)

As per the paper, "These datasets are freely available to industry and academia, based on which various applications on masked faces can be developed."

Could you please add a license file (MIT) or mention in readme about the license (CC0).

Thanks in advance for any response from you.

MFDD 数据集

你好,请问MFDD数据集的下载连接在哪里?

What is the difference of database between download link1 and link2?

Firstly, thanks a lot for your amazing work.

But I feel some confusion about the dataset differences.

Could you please tell me what is the difference between dataset from link1 and dataset from link2?

Additionally, you have mentioned that for the Real-world masked face recognition dataset, the number of identities is 525. But I find that the number of identities in decompressed RWMFD(which is downloaded by cloning the GitHub repository) is 537. That is what makes me confused.

By the way, the Webface you used here refers to the CASIA-WebFace dataset, right?

webface lfw

webface lfw 模拟的戴口罩数据,戴的都是同一种口罩,这样数据训练的模型,会不会过分关注这种口罩,影响佩戴其他口罩的检测呢?您有验证过效果吗?

I wonder if I could ask some details about mask face detection and recognition

About This Dataset

Thank you for offering the informative dataset for mask face recognition; it helps the developers like me save too much time collecting data.I've stared your project once I read the description just to show my support.

About the demonstration video

I have seen the demonstration video you put on GitHub, and it seems the accuracy of recognition is pretty high, so I wonder if I could ask for some details about the face detection and face recognition you used on this dataset, Maybe the name of the algorithm or framework, and if you've happened to have an open source project that implemented this function ,that would be great!

So, could you help me with that? anything helpful will be appreciated!

can find Labels / markup

Hello!
Excuse me, but I can not find bounding boxes for detection dataset, could you please point on them.

How to align the real world masked face recognition dataset?

I downloaded Real-world masked face recognition dataset from https://drive.google.com/open?id=1UlOk6EtiaXTHylRUx2mySgvJX9ycoeBp.
However, I can't find the annotation labels of the face dataset. So I tried some regular face detection method such as MTCNN, dlib to dectect face and align face. But there are many wrong or missed detection probably due to the mask.
I wonder what kind of face detector you used to detect and align face with Real-world masked face recognition dataset. Thanks in advance.

License of the dataset

Hi, thanks for the contribution. May I know the license of this dataset? It would be great if you could add license in.

真实口罩人脸数据集图像有半张人脸的问题

您好,首先非常感谢您的工作!但是我发现真实口罩人脸数据集中有一些图像质量不高,例如有半张人脸的情况,请问这种情况是由于检测器导致的吗?可否将检测器检测到的区域适当外扩再做crop呢?

Incorrect images

The folders contain few non-mask images in the folder of with-mask. Please clean your dataset.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.