xwMOOC 딥러닝

##==========================================================================================
## 00. 환경설정  
##==========================================================================================
library("httr")
library("XML")
library("ggplot2")
setwd("~/10-microsoft-oxford")

##==========================================================================================
## 01. 마이크로소프트 API 설정  
##==========================================================================================

# 적용할 마이크로소프트 API 지정
URL.emoface = 'https://api.projectoxford.ai/emotion/v1.0/recognize'

# 접속 인증키 설정
# emotionKEY = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXX'
source("private-keys.R") 

##==========================================================================================
## 02. 감정분석할 이미지 지정 및 호출
##==========================================================================================

emotion_fn <- function(img.url){
    mybody = list(url = img.url)
    
    # 마이크로소프트에 API 호출 및 데이터 요청
    faceEMO  <-  POST(
      url = URL.emoface,
      content_type('application/json'), add_headers(.headers = c('Ocp-Apim-Subscription-Key' = emotionKEY)),
      body = mybody,
      encode = 'json'
    )
    
    # 결과값 출력, Status=200 이면 모든 것이 OK!!!
    return(faceEMO)
}

# 이미지 지정
son.url <- 'http://www.jungang.co/news/photo/201509/1051_603_841.jpg'
ban.url <- 'http://img.etoday.co.kr/pto_db/2012/04/20120424082942_194639_500_333.jpg'
moon.url <- 'http://www.hyundaenews.com/imgdata/hyundaenews_com/201601/2016011932479902.jpg'
ahn.url <- 'https://t1.daumcdn.net/thumb/R1280x0/?fname=http://t1.daumcdn.net/brunch/service/user/5ns/image/TtrYI3uNOJCsI-UmswcmJgRm5QQ.jpg'

son <- emotion_fn(son.url)
ban <- emotion_fn(ban.url)
moon <- emotion_fn(moon.url)
ahn <- emotion_fn(ahn.url)

##==========================================================================================
## 03. 감정분석결과 추가분석
##==========================================================================================
# 얼굴 분석결과
Son <-  httr::content(son)[[1]]
Ban <-  httr::content(ban)[[1]]
Moon <-  httr::content(moon)[[1]]
Ahn <-  httr::content(ahn)[[1]]


# 분석을 위해 결과값을 데이터프레임으로 변환
Son.o <-as.data.frame(as.matrix(Son$scores))
Ban.o <-as.data.frame(as.matrix(Ban$scores))
Moon.o <-as.data.frame(as.matrix(Moon$scores))
Ahn.o <-as.data.frame(as.matrix(Ahn$scores))

# Make some transformation
Son.o$V1 <- lapply(strsplit(as.character(Son.o$V1), "e"), "[", 1)
Ban.o$V1 <- lapply(strsplit(as.character(Ban.o$V1), "e"), "[", 1)
Moon.o$V1 <- lapply(strsplit(as.character(Moon.o$V1), "e"), "[", 1)
Ahn.o$V1 <- lapply(strsplit(as.character(Ahn.o$V1), "e"), "[", 1)

Son.o$V1 <-as.numeric(Son.o$V1)
Son.o$V1 <-as.numeric(Son.o$V1)
colnames(Son.o)[1] <- "Son"

Ban.o$V1 <-as.numeric(Ban.o$V1)
Ban.o$V1 <-as.numeric(Ban.o$V1)
colnames(Ban.o)[1] <- "Ban"

Moon.o$V1 <-as.numeric(Moon.o$V1)
Moon.o$V1 <-as.numeric(Moon.o$V1)
colnames(Moon.o)[1] <- "Moon"

Ahn.o$V1 <-as.numeric(Ahn.o$V1)
Ahn.o$V1 <-as.numeric(Ahn.o$V1)
colnames(Ahn.o)[1] <- "Ahn"


# 행명칭으로부터 감정 변수 생성
Son.o$Emotion<- rownames(Son.o)

# 후보데이터 취합
candidate.df <- cbind(Ban.o, Moon.o, Ahn.o, Son.o)

library(reshape2)

candidate.df.m <- melt(candidate.df, id.vars='Emotion')

candidate.df

ggplot(candidate.df.m, aes(Emotion, value)) +   
  geom_bar(aes(fill = variable), position = "dodge", stat="identity")