本文基于百度AI进行人脸识别，在众多人脸中匹配人脸库中的人脸。

首先创建百度AI网站帐号：

进入控制台：

创建应用可以在应用中创建自己的人脸库。

#!/usr/bin/env python
import rospy
from PIL import Image
from std_msgs.msg import String
from aip import AipFace
import base64
from sensor_msgs.msg import Image
import cv2
from cv_bridge import CvBridge, CvBridgeError
import PIL.Image

#  def callback(data):
#      rospy.loginfo(rospy.get_caller_id() + "I heard %s", data.data)
APP_ID = '××××××'
API_KEY = '×××××××××××'
SECRET_KEY = '××××××××××××××'

client = AipFace(APP_ID, API_KEY, SECRET_KEY)

def listen():

	filePath = "/home/wly/data/1/wly.jpg"
	with open(filePath,"rb") as f:
		base64_data = base64.b64encode(f.read())
	image = str(base64_data)
	imageType = "BASE64"

	groupIdList = "wangliyuan"

	a = client.search(image, imageType, groupIdList);

	print(a)
	rospy.spin()
if __name__ == '__main__':
	rospy.init_node('listener')
	listen()
	
    

这里

APP_ID = '××××××'
API_KEY = '×××××××××××'
SECRET_KEY = '××××××××××××××'

这些信息可以在刚刚百度ai创建的应用中找到。

把这些改造成ros节点之后你会发现Image中提取到的时RGB图像，但是百度AI不支持RGB图像的识别，我们只能将RGB图形进行转化：

#! /usr/bin/python
# Copyright (c) 2015, Rethink Robotics, Inc.

# Using this CvBridge Tutorial for converting
# ROS images to OpenCV2 images
# http://wiki.ros.org/cv_bridge/Tutorials/ConvertingBetweenROSImagesAndOpenCVImagesPython

# Using this OpenCV2 tutorial for saving Images:
# http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_gui/py_image_display/py_image_display.html

# rospy for the subscriber
import rospy
# ROS Image message
from sensor_msgs.msg import Image
# ROS Image message -> OpenCV2 image converter
from cv_bridge import CvBridge, CvBridgeError
# OpenCV2 for saving an image
import cv2

# Instantiate CvBridge
bridge = CvBridge()

def image_callback(msg):
    print("Received an image!")
    try:
        # Convert your ROS Image message to OpenCV2
        cv2_img = bridge.imgmsg_to_cv2(msg, "bgr8")
    except CvBridgeError, e:
        print(e)
    else:
        # Save your OpenCV2 image as a jpeg 
        cv2.imwrite('/home/wly/catkin_ws/src/face_men/camera_photo/photo.jpeg', cv2_img)

def main():
    rospy.init_node('image_listener')
    # Define your image topic
    image_topic = "/usb_cam/image_raw"
    # Set up your subscriber and define its callback
    rospy.Subscriber(image_topic, Image, image_callback)
    # Spin until ctrl + c
    rospy.spin()

if __name__ == '__main__':
    main()

这里我们将转化后的结果存在文件夹下。

这里可以将两部分整合，让百度AI去调用照片去识别人脸，因为百度AI不限制调用次数但是没秒5次，所以会有一些延迟，所以还是需要进一步改进。