ROS填坑记之树莓派图像处理

       我计划从树莓派上的摄像头采集图像数据到笔记本上，tensorflow处理完毕后再向树莓派发送操作指令，控制电机和舵机。ROS的双机连接还是挺简单的，首先树莓派和笔记本设置ssh免密码和用户名登录（具体请百度），从树莓派和笔记本上都可以互相无密码和用户名登录成功后，在树莓派上输入sudo vi ~/.bashrc，在最后增加export ROS_HOSTNAME=树莓派的ip，export ROS_MASTER_URI=http://笔记本的ip:11311，然后source ~/.bashrc；登录笔记本上sudo vi ~/.bashrc，最后增加 export ROS_HOSTNAME=笔记本ip，export ROS_MASTER_URI=http://笔记本ip:11311（我用笔记本当主机，如果用树莓派当主机，ROS_MASTER_URI地址更换就可以了）。然后树莓派、pc上安装opencv，树莓派上安装picamera。在笔记本上启动roscore，在树莓派用以下代码测试双机发送图像：

# -*- encoding:utf-8 -*-

# import the necessary packages

from picamera.array import PiRGBArray

from picamera import PiCamera

import time

import cv2

import sys

import rospy

from std_msgs.msg import String

from sensor_msgs.msg import Image

from cv_bridge import CvBridge, CvBridgeError

import io

import numpy as np

# initialize the camera and grab a reference to the raw camera capture

def talker():

    camera = PiCamera()

    camera.resolution = (320,240)

    time.sleep(1)

    #allow the camera to warmup

    image_pub = rospy.Publisher("image_topic_2",Image,queue_size=10)

    bridge = CvBridge()

    rospy.init_node('image_talker', anonymous=True)

    rate = rospy.Rate(10) # 10hz

    #以上是ros节点初始化完成

    # capture frames from the camera

    stream = io.BytesIO()

    for foo in camera.capture_continuous(stream, format='jpeg', use_video_port=True):

        # grab the raw NumPy array representing the image, then initialize the timestamp

        # and occupied/unoccupied text

        data = np.fromstring(stream.getvalue(), dtype=np.uint8)

        # 转换为CV2的mat格式

        image = cv2.imdecode(data, cv2.IMREAD_COLOR)

        (rows,cols,channels) = image.shape

        if cols > 60 and rows > 60 :

            cv2.circle(image, (50,50), 10, 255)

        image_pub.publish(bridge.cv2_to_imgmsg(image, "bgr8"))

        rate.sleep()

    stream.truncate()

    stream.seek(0)       

if __name__ == '__main__':

    try:

        talker()

    except rospy.ROSInterruptException:

        pass

在/catkin_ws/src/beginner_tutorials/src保存为test.py，chmod +x test.py。运行rosrun beginner_tutorials test.py。在笔记本上运营rqt_image_view查看图像。