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【Python】使用Face++的人脸识别detect API进行本地图片情绪识别并存入excel

时间:2018-05-04 14:23:25      阅读:342      评论:0      收藏:0      [点我收藏+]

标签:主页   write   python2.7   mes   time   ali   stat   img   hot   

准备工作

首先,需要在Face++的主页注册一个账号,在控制台去获取API Key和API Secret。

技术分享图片

然后在本地文件夹准备好要进行情绪识别的图片/相片。

 

代码

介绍下所使用的第三方库

——urllib2是使用各种协议完成打开url的一个库

——time是对时间进行处理的一个库,以下代码中其实就使用了sleep()和localtime()两个函数,sleep()是用来让程序暂停几秒的,localtime()是格式化时间戳为本地的时间

——xlwt是对excel进行写入操作的一个库

——os是操作系统的相关功能的一个库,例如用来处理文件和目录之类的

——json (Emmmmmm……我也不知道该怎么解释这个)

——PIL是Python图像处理库

  1 # -*- coding: utf-8 -*-
  2 # version:python2.7.13
  3 # author:Ivy Wong
  4 
  5 # 导入相关模块
  6 import urllib2
  7 import time, xlwt, os,json
  8 from PIL import Image
  9 
 10 # 使用face++的api识别情绪
 11 def useapi(img):
 12     http_url = https://api-cn.faceplusplus.com/facepp/v3/detect
 13     boundary = ----------%s % hex(int(time.time() * 1000))
 14     data = []
 15     data.append(--%s % boundary)
 16     data.append(Content-Disposition: form-data; name="%s"\r\n % api_key)
 17     data.append(key)
 18     data.append(--%s % boundary)
 19     data.append(Content-Disposition: form-data; name="%s"\r\n % api_secret)
 20     data.append(secret)
 21     data.append(--%s % boundary)
 22     fr = open(img, rb)
 23     data.append(Content-Disposition: form-data; name="%s"; filename=" " % image_file)
 24     data.append(Content-Type: %s\r\n % application/octet-stream)
 25     data.append(fr.read())
 26     fr.close()
 27     data.append(1)
 28     data.append(--%s % boundary)
 29     data.append(Content-Disposition: form-data; name="%s"\r\n % return_attributes)
 30     data.append("gender,age,emotion,ethnicity")# 这里可以还可以返回其他参数,具体可以参看face++的api文档
 31     data.append(--%s--\r\n % boundary)
 32 
 33     http_body = \r\n.join(data)
 34     # build http request
 35     req = urllib2.Request(http_url)
 36     # header
 37     req.add_header(Content-Type, multipart/form-data; boundary=%s % boundary)
 38     req.add_data(http_body)
 39     try:
 40         resp = urllib2.urlopen(req,timeout=5)
 41         qrcont = json.load(resp)
 42     except urllib2.HTTPError as e:
 43         print e.read()
 44     return qrcont
 45 
 46 
 47 # 将json字典写入excel
 48 # 变量用来循环时控制写入单元格,感觉这种方式有点傻,但暂时想不到优化方法
 49 def writeexcel(img, worksheet, row, files_name):
 50     parsed = useapi(img)
 51     if not parsed[faces]:
 52         print This picture do not have any face
 53     else:
 54         if len(parsed[faces])<=5: # 由于免费API限制,只能返回5张人脸信息
 55             for list_item in parsed[faces]:
 56                 # 写入文件名
 57                 filename, extension = os.path.splitext(files_name)
 58                 worksheet.write(row, 0, filename)
 59 
 60                 # 写入时间戳
 61                 daystamp, timestamp, hourstamp = gettimestamp(img)
 62                 worksheet.write(row, 1, label=daystamp)
 63                 worksheet.write(row, 2, label=timestamp)
 64                 worksheet.write(row, 3, hourstamp)
 65 
 66                 # 写入api返回的数据
 67                 emotion = []
 68                 for key1, value1 in list_item.items():
 69                     if key1 == attributes:
 70                         for key2, value2 in value1.items():
 71                             if key2 == age:
 72                                 worksheet.write(row, 5, value2[value])
 73                             elif key2 == emotion:
 74                                 for key3, value3 in value2.items():
 75                                     if key3 == sadness:
 76                                         worksheet.write(row, 8, value3)
 77                                         emotion.append(value3)
 78                                     elif key3 == neutral:
 79                                         worksheet.write(row, 9, value3)
 80                                         emotion.append(value3)
 81                                     elif key3 == disgust:
 82                                         worksheet.write(row, 10, value3)
 83                                         emotion.append(value3)
 84                                     elif key3 == anger:
 85                                         worksheet.write(row, 11, value3)
 86                                         emotion.append(value3)
 87                                     elif key3 == surprise:
 88                                         worksheet.write(row, 12, value3)
 89                                         emotion.append(value3)
 90                                     elif key3 == fear:
 91                                         worksheet.write(row, 13, value3)
 92                                         emotion.append(value3)
 93                                     else:
 94                                         worksheet.write(row, 14, value3)
 95                                         emotion.append(value3)
 96                             elif key2 == gender:
 97                                 worksheet.write(row, 6, value2[value])
 98                             elif key2 == ethnicity:
 99                                 worksheet.write(row, 7, value2[value])
100                             else:
101                                 pass
102                     elif key1 == face_token:
103                         worksheet.write(row, 4, value1)
104                     else:
105                         pass
106                 worksheet.write(row, 15, emotion.index(max(emotion)))
107 
108                 # 写入概率最大的情绪,0-neutral,1-sadness,2-disgust,3-anger,4-surprise,5-fear,6-happiness
109                 row += 1
110         else:
111             for list_item in parsed[faces][0:5]:
112                 # 写入文件名
113                 filename, extension = os.path.splitext(files_name)
114                 worksheet.write(row, 0, filename)
115 
116                 # 写入时间戳
117                 daystamp, timestamp, hourstamp = gettimestamp(img)
118                 worksheet.write(row, 1, label=daystamp)
119                 worksheet.write(row, 2, label=timestamp)
120                 worksheet.write(row, 3, hourstamp)
121 
122                 # 写入api返回的数据
123                 emotion = []
124                 for key1, value1 in list_item.items():
125                     if key1 == attributes:
126                         for key2, value2 in value1.items():
127                             if key2 == age:
128                                 worksheet.write(row, 5, value2[value])
129                             elif key2 == emotion:
130                                 for key3, value3 in value2.items():
131                                     if key3 == sadness:
132                                         worksheet.write(row, 8, value3)
133                                         emotion.append(value3)
134                                         print 1
135                                     elif key3 == neutral:
136                                         worksheet.write(row, 9, value3)
137                                         emotion.append(value3)
138                                         print 2
139                                     elif key3 == disgust:
140                                         worksheet.write(row, 10, value3)
141                                         emotion.append(value3)
142                                         print 3
143                                     elif key3 == anger:
144                                         worksheet.write(row, 11, value3)
145                                         emotion.append(value3)
146                                         print 4
147                                     elif key3 == surprise:
148                                         worksheet.write(row, 12, value3)
149                                         emotion.append(value3)
150                                         print 5
151                                     elif key3 == fear:
152                                         worksheet.write(row, 13, value3)
153                                         emotion.append(value3)
154                                         print 6
155                                     else:
156                                         worksheet.write(row, 14, value3)
157                                         emotion.append(value3)
158                                         print 7
159                             elif key2 == gender:
160                                 worksheet.write(row, 6, value2[value])
161                             elif key2 == ethnicity:
162                                 worksheet.write(row, 7, value2[value])
163                             else:
164                                 pass
165                     elif key1 == face_token:
166                         worksheet.write(row, 4, value1)
167                     else:
168                         pass
169                 worksheet.write(row, 15, emotion.index(max(emotion)))
170                 # 写入概率最大的情绪,0-neutral,1-sadness,2-disgust,3-anger,4-surprise,5-fear,6-happiness
171                 row += 1
172                 print Success! The pic  + str(files_name) +  was detected!
173 
174     return row, worksheet
175 
176 # 获取图片大小
177 def imagesize(img):
178     Img = Image.open(img)
179     w, h = Img.size
180     return w,h
181 
182 # 获取时间戳
183 def gettimestamp(path):
184     statinfo = os.stat(path)
185     timeinfo = time.localtime(statinfo.st_ctime)
186     daystamp = str(timeinfo.tm_year) + - + str(timeinfo.tm_mon) + - + str(timeinfo.tm_mday)
187     timestamp = str(timeinfo.tm_hour) + : + str(timeinfo.tm_min) + : + str(timeinfo.tm_sec)
188     hourstamp = timeinfo.tm_hour + timeinfo.tm_min / 60.0 + timeinfo.tm_sec / 3600.0
189     return daystamp, timestamp, hourstamp
190 
191 
192 key = "your_key"
193 secret = "your_secret"
194 path = r"图片文件夹路径"
195 # 注意:由于我是对同一文件夹下的多个文件夹中的图片进行识别,所以这个path是图片所在文件夹的上一级文件夹。文件夹名尽量使用英文与数字,不然可能因为编码问题报错
196 
197 # 创建excel
198 workbook = xlwt.Workbook(encoding=utf-8)
199 
200 for root, dirs, files in os.walk(path, topdown=False):
201     for folder in dirs:
202         print Let us start dealing with folder  + folder
203 
204         # 创建一个新的sheet
205         worksheet = workbook.add_sheet(folder)
206         # 设置表头
207         title = [PhotoID, daystamp, timestamp, hourstamp,faceID, age, gender, ethnicity, sadness,
208                  neutral,disgust, anger, surprise, fear, happiness, emotion]
209         for col in range(len(title)):
210             worksheet.write(0, col, title[col])
211 
212         # 遍历每个folder里的图片
213         row = 1
214         for root2, dirs2, files2 in os.walk(path + \\ + folder):
215             for files_name in files2:
216                 img = path + \\ + folder + \\ + files_name
217                 try:
218                     print Now, the program is going to deal with  + folder +  pic + str(files_name)
219                     w,h=imagesize(img)
220                     if w<48 or h<48 or w>4096 or h>4096:#API对图片大小的限制
221                         print invalid image size
222                     else:
223                         row, worksheet = writeexcel(img, worksheet, row, files_name)
224 
225                 except:
226                     print 超过了并发数!等一下!
227                     time.sleep(3)
228                     print The program is going to work
229                     print Now, the program is going to deal with  + folder +  pic + str(files_name)
230                     row, worksheet = writeexcel(img, worksheet, row, files_name)
231 
232 
233         workbook.save(detactface_facepp_flickr.xls)
234         print The current folder is done.
235 
236 # 保存文件
237 workbook.save(detectface.xls)
238 print All done!

 

成果

最后生成的excel大概是这个样子。

技术分享图片

其中emotion就是概率最大的情绪,0-neutral,1-sadness,2-disgust,3-anger,4-surprise,5-fear,6-happiness。

 

探讨

在我自己运行过程中发现了一个问题,由于使用的是免费API,有并发限制,多次超过并发数,urlopen就会返回403。于是try失败,运行except,return时无定义的qrcont而报错。

1     try:
2         resp = urllib2.urlopen(req,timeout=5)
3         qrcont = json.load(resp)
4     except urllib2.HTTPError as e:
5         print e.read()
6     return qrcont

这就非常尴尬了,所以目前基本上都是大晚上在用这个代码跑……不知看到的各位有何高见?

【Python】使用Face++的人脸识别detect API进行本地图片情绪识别并存入excel

标签:主页   write   python2.7   mes   time   ali   stat   img   hot   

原文地址:https://www.cnblogs.com/IvyWong/p/8989718.html

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