人脸提供关于情绪的各种信息。微软于2015年12月推出免费服务,分析人脸,进行情绪检测。 检测到的情绪是愤怒,蔑视,厌恶,恐惧,幸福,中立,悲伤和惊喜。 这些情绪被理解为与特定的面部表情跨文化和普遍传达。
Emotion API将图像中的面部表情作为输入,并使用Face API返回图像中每个面部的一组情绪的置信度以及面部的边界框。
在R中的实现允许以结构化的方式分析人脸。 注意,必须创建一个帐户来使用Face API。
该示例引用了一个简单的示例:使用的是现任美国总统奥巴马的照片;如下
需要加载的包有: httr, XML, stringr, ggplot2.
- # 加载相关包
- library("httr")#链接API
- library("XML")#爬取网页数据
- library("stringr")#字符串处理
- library("ggplot2")#绘图使用
-
- # Define image source
- img.url = 'https://www.whitehouse.gov/sites/whitehouse.gov/files/images/first-family/44_barack_obama[1].jpg'
-
- # Define Microsoft API URL to request data
- URL.emoface = 'https://api.projectoxford.ai/emotion/v1.0/recognize'
-
- # Define access key (access key is available via: https://www.microsoft.com/cognitive-services/en-us/emotion-api)
- emotionKEY = 'XXXX' # 在此处输入你获取的key
-
- # Define image
- mybody = list(url = img.url)
-
- # Request data from Microsoft
- faceEMO = POST(
- url = URL.emoface,
- content_type('application/json'), add_headers(.headers = c('Ocp-Apim-Subscription-Key' = emotionKEY)),
- body = mybody,
- encode = 'json'
- )
-
- # Show request results (if Status=200, request is okay)
- faceEMO
-
- # Reuqest results from face analysis
- Obama = httr::content(faceEMO)[[1]]
- Obama
- # Define results in data frame
- o<-as.data.frame(as.matrix(Obama$scores))
-
- # Make some transformation
- o$V1 <- lapply(strsplit(as.character(o$V1 ), "e"), "[", 1)
- o$V1<-as.numeric(o$V1)
- colnames(o)[1] <- "Level"
-
- # Define names
- o$Emotion<- rownames(o)
-
- # Make plot
- ggplot(data=o, aes(x=Emotion, y=Level)) +
- geom_bar(stat="identity")
下面就是对这张照片的情感分析图。
![](//image109.360doc.cn/DownloadImg/2017/08/1819/108735491_2_20170818070624372)
- #人脸检测
- #####################################################################
- # Define image source
- img.url = 'https://www.whitehouse.gov/sites/whitehouse.gov/files/images/first-family/44_barack_obama[1].jpg'
-
- # Define Microsoft API URL to request data
- faceURL = "https://api.projectoxford.ai/face/v1.0/detect?returnFaceId=true&returnFaceLandmarks=true&returnFaceAttributes=age"
-
- # Define access key (access key is available via: https://www.microsoft.com/cognitive-services/en-us/face-api)
- faceKEY = 'a868182e859c4458953f69dab084f5e8'
-
- # Define image
- mybody = list(url = img.url)
-
- # Request data from Microsoft
- faceResponse = POST(
- url = faceURL,
- content_type('application/json'), add_headers(.headers = c('Ocp-Apim-Subscription-Key' = faceKEY)),
- body = mybody,
- encode = 'json'
- )
-
- # Show request results (if Status=200, request is okay)
- faceResponse
-
- # Reuqest results from face analysis
- ObamaR = httr::content(faceResponse)[[1]]
-
- # Define results in data frame
- OR<-as.data.frame(as.matrix(ObamaR$faceLandmarks))
-
- # Make some transformation to data frame
- OR$V2 <- lapply(strsplit(as.character(OR$V1), "\\="), "[", 2)
- OR$V2 <- lapply(strsplit(as.character(OR$V2), "\\,"), "[", 1)
- colnames(OR)[2] <- "X"
- OR$X<-as.numeric(OR$X)
-
- OR$V3 <- lapply(strsplit(as.character(OR$V1), "\\y = "), "[", 2)
- OR$V3 <- lapply(strsplit(as.character(OR$V3), "\\)"), "[", 1)
- colnames(OR)[3] <- "Y"
- OR$Y<-as.numeric(OR$Y)
-
- OR$V1<-NULL
- OR
结果如下:
是他脸部的特征值:
- X Y
- pupilLeft 475.4 158.6
- pupilRight 590.6 157.3
- noseTip 534.4 227.7
- mouthLeft 460.8 273.7
- mouthRight 603.6 268.2
- eyebrowLeftOuter 425.2 154.8
- eyebrowLeftInner 508.4 142.3
- eyeLeftOuter 458.6 162.6
- eyeLeftTop 473.6 153.8
- eyeLeftBottom 475.9 164.9
- eyeLeftInner 492.8 162.0
- eyebrowRightInner 552.3 141.4
- eyebrowRightOuter 636.0 156.2
- eyeRightInner 571.7 159.9
- eyeRightTop 588.1 152.5
- eyeRightBottom 587.4 163.9
- eyeRightOuter 605.5 161.5
- noseRootLeft 511.2 163.4
- noseRootRight 551.2 163.0
- noseLeftAlarTop 503.1 204.6
- noseRightAlarTop 559.2 201.6
- noseLeftAlarOutTip 485.3 226.9
- noseRightAlarOutTip 580.5 224.1
- upperLipTop 530.9 264.3
- upperLipBottom 532.1 272.5
- underLipTop 530.3 305.1
- underLipBottom 532.5 318.6
说明:本人对原博客进行翻译的时候,在某些地方进行了一定修改,与原文并不完全相同。
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