|
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。
-
#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。
|
客服电话
APP下载
官方微信
请发表评论