Face++是一套成熟的人臉檢測、識別和跟蹤等視覺技術服務平臺，每個人在Face++的官網註冊賬號後可以申請新建API，隨後會分配API key和 API Secrect，這樣我們就可以使用這些API進行簡單的人臉識別了。

原文連結傳送門

程式碼如下：

# coding=UTF-8
import cv2
import urllib
import urllib2
import time

# 讀取影象
image = cv2.imread('girls.jpg')
# URL
http_url='https://api-cn.faceplusplus.com/facepp/v3/detect'
# 使用者資訊
key = '06LVocdF5FVMyNkMRknGzXYlMf_N-MUA'
secret = 'WAi7gNtc3NPwpf-iHGUk9pxjxyws43aq'
# 圖片儲存路徑
filepath = 'girls.jpg'

# 呼叫API介面
boundary = '----------%s' % hex(int(time.time() * 1000))
data = []
data.append('--%s' % boundary)
data.append('Content-Disposition: form-data; name="%s"\r\n' % 'api_key')
data.append(key)
data.append('--%s' % boundary)
data.append('Content-Disposition: form-data; name="%s"\r\n' % 'api_secret')
data.append(secret)
data.append('--%s' % boundary)
fr=open(filepath,'rb')
data.append('Content-Disposition: form-data; name="%s"; filename=" "' % 'image_file')
data.append('Content-Type: %s\r\n' % 'application/octet-stream')
data.append(fr.read())
fr.close()
data.append('--%s--\r\n' % boundary)

http_body='\r\n'.join(data)
# buld http request
req = urllib2.Request(http_url)
# header
req.add_header('Content-Type', 'multipart/form-data; boundary=%s' % boundary)
req.add_data(http_body)
try:
    # req.add_header('Referer','http://remotserver.com/')
    # post data to server
    resp = urllib2.urlopen(req, timeout=5)
    # get response
    qrcont=resp.read()
    print qrcont        # 打印出得到的結果

except urllib2.HTTPError as e:
    print e.read()

# 進過測試前面的程式會返回一個字典，其中指出了人臉所在的矩形的位置和大小等，所以直接進行標註
mydict = eval(qrcont)
faces = mydict["faces"]
faceNum = len(faces)
print("識別到了%d個人臉"%( faceNum ))

for i in range(faceNum):
    face_rectangle = faces[i]['face_rectangle']
    width =  face_rectangle['width']
    top =  face_rectangle['top']
    left =  face_rectangle['left']
    height =  face_rectangle['height']
    start = (left, top)
    end = (left+width, top+height)
    color = (255,55,55)
    thickness = 5
    cv2.rectangle(image, start, end, color, thickness)

cv2.namedWindow("Detection:")
cv2.imshow("Detection:", image)

cv2.waitKey(0)
cv2.destroyAllWindows()


 

結果如下圖：