pythonnumpypython-imaging-libraryrosrospy

How can I publish PIL image binary through ROS without OpenCV?


I'm currently trying to write a ROS Publisher/Subscriber setup that passes image binary opened by PIL. I'd like to not have to use OpenCV due to operating restrictions, and I was wondering if there was a way to do so. This is my current code:

#!/usr/bin/env python
import rospy
from PIL import Image
from sensor_msgs.msg import Image as sensorImage
from rospy.numpy_msg import numpy_msg
import numpy

def talker():
    pub = rospy.Publisher('image_stream', numpy_msg(sensorImage), queue_size=10)
    rospy.init_node('image_publisher', anonymous=False)
    rate = rospy.Rate(0.5)
    while not rospy.is_shutdown():
        im = numpy.array(Image.open('test.jpg'))
        pub.publish(im)
        rate.sleep()

if __name__ == '__main__'
    try:
        talker()
    except ROSInterruptException:
        pass

which on pub.publish(im) attempt throws:

TypeError: Invalid number of arguments, args should be ['header', 'height', 'width', 'encoding', 'is_bigendian', 'step', 'data'] args are (array([[[***array data here***]]], dtype=uint8),)

How would I transform the image into the right form, or is there a conversion method/different message type that supports just sending raw binary over the ROS connection?

Thanks


Solution

  • Indeed Mark Setchell's answer works perfectly (ignoring the alpha channel in this example):

    #!/usr/bin/env python
    import rospy
    import urllib2  # for downloading an example image
    from PIL import Image
    from sensor_msgs.msg import Image as SensorImage
    import numpy as np
    
    if __name__ == '__main__':
        pub = rospy.Publisher('/image', SensorImage, queue_size=10)
    
        rospy.init_node('image_publisher')
    
        im = Image.open(urllib2.urlopen('https://cdn.sstatic.net/Sites/stackoverflow/Img/apple-touch-icon.png'))
        im = im.convert('RGB')
    
        msg = SensorImage()
        msg.header.stamp = rospy.Time.now()
        msg.height = im.height
        msg.width = im.width
        msg.encoding = "rgb8"
        msg.is_bigendian = False
        msg.step = 3 * im.width
        msg.data = np.array(im).tobytes()
        pub.publish(msg)