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## Example 11
This tutorial highlights how to create a [PointCloud](http://docs.ros.org/en/melodic/api/sensor_msgs/html/msg/PointCloud.html) message from the data of a [PointCloud2](http://docs.ros.org/en/noetic/api/sensor_msgs/html/msg/PointCloud2.html) message type, then transform the PointCloud's reference link to a different frame. The data published by the RealSense is referencing its *camera_color_optical_frame* link, and we will be changing its reference to the *base_link*.
Begin by starting up the stretch driver launch file.
```bash
# Terminal 1
roslaunch stretch_core stretch_driver.launch
```
To activate the RealSense camera and publish topics to be visualized, run the following launch file in a new terminal.
```bash
# Terminal 2
roslaunch stretch_core d435i_low_resolution.launch
```
Then run the `PointCloud` transformer node.
```bash
# Terminal 3
cd catkin_ws/src/stretch_tutorials/src/
python pointcloud_transformer.py
```
Within this tutorial package, there is an RViz config file with the `PointCloud` in the Display tree. You can visualize this topic and the robot model by running the command below in a new terminal.
```bash
# Terminal 4
rosrun rviz rviz -d /home/hello-robot/catkin_ws/src/stretch_tutorials/rviz/PointCloud_transformer_example.rviz
```
The gif below visualizes what happens when running the previous node.
<p align="center">
<img src="images/PointCloud_transformer.gif"/>
</p>
### The Code
```python
#!/usr/bin/env python
import rospy
import tf
import sensor_msgs.point_cloud2 as pc2
from sensor_msgs.msg import PointCloud2, PointCloud
from geometry_msgs.msg import Point32
from std_msgs.msg import Header
class PointCloudTransformer:
"""
A class that takes in a PointCloud2 message and stores its points into a
PointCloud message. Then that PointCloud is transformed to reference the
'base_link' frame.
"""
def __init__(self):
"""
Function that initializes the subscriber, publisher, and other variables.
:param self: The self reference.
"""
self.pointcloud2_sub = rospy.Subscriber("/camera/depth/color/points", PointCloud2, self.callback_pcl2, queue_size=1)
self.pointcloud_pub = rospy.Publisher("/camera_cloud", PointCloud, queue_size=1)
self.pcl2_cloud = None
self.listener = tf.TransformROS(True, rospy.Duration(10.0))
rospy.loginfo('Publishing transformed PointCloud. Use RViz to visualize')
def callback_pcl2(self,msg):
"""
Callback function that stores the PointCloud2 message.
:param self: The self reference.
:param msg: The PointCloud2 message type.
"""
self.pcl2_cloud = msg
def pcl_transformer(self):
"""
A function that extracts the points from the stored PointCloud2 message
and appends those points to a PointCloud message. Then the function transforms
the PointCloud from its the header frame id, 'camera_color_optical_frame'
to the 'base_link' frame.
:param self: The self reference.
"""
temp_cloud = PointCloud()
temp_cloud.header = self.pcl2_cloud.header
for data in pc2.read_points(self.pcl2_cloud, skip_nans=True):
temp_cloud.points.append(Point32(data[0],data[1],data[2]))
transformed_cloud = self.transform_pointcloud(temp_cloud)
self.pointcloud_pub.publish(transformed_cloud)
def transform_pointcloud(self,msg):
"""
Function that stores the PointCloud2 message.
:param self: The self reference.
:param msg: The PointCloud message.
:returns new_cloud: PointCloud message.
"""
while not rospy.is_shutdown():
try:
new_cloud = self.listener.transformPointCloud("/base_link" ,msg)
return new_cloud
if new_cloud:
break
except (tf.LookupException, tf.ConnectivityException,tf.ExtrapolationException):
pass
if __name__=="__main__":
rospy.init_node('pointcloud_transformer',anonymous=True)
PCT = PointCloudTransformer()
rate = rospy.Rate(1)
rospy.sleep(1)
while not rospy.is_shutdown():
PCT.pcl_transformer()
rate.sleep()
```
### The Code Explained
Now let's break the code down.
```python
#!/usr/bin/env python
```
Every Python ROS [Node](http://wiki.ros.org/Nodes) will have this declaration at the top. The first line makes sure your script is executed as a Python script.
```python
import rospy
import tf
import sensor_msgs.point_cloud2 as pc2
from sensor_msgs.msg import PointCloud2, PointCloud
from geometry_msgs.msg import Point32
from std_msgs.msg import Header
```
You need to import `rospy` if you are writing a ROS Node. Import `tf` to utilize the `transformPointCloud` function. Import various the message types from `sensor_msgs`.
```python
self.pointcloud2_sub = rospy.Subscriber("/camera/depth/color/points", PointCloud2, self.callback_pcl2, queue_size=1)
```
Set up a subscriber. We're going to subscribe to the topic */camera/depth/color/points*, looking for `PointCloud2` message. When a message comes in, ROS is going to pass it to the function `callback_pcl2()` automatically.
```python
self.pointcloud_pub = rospy.Publisher("/camera_cloud", PointCloud, queue_size=1)
```
This section of code defines the talker's interface to the rest of ROS. `self.pointcloud_pub = rospy.Publisher("/camera_cloud", PointCloud, queue_size=1)` declares that your node is publishing to the */camera_cloud* topic using the message type `PointCloud`.
```python
self.pcl2_cloud = None
self.listener = tf.TransformListener(True, rospy.Duration(10.0))
```
The first line of code initializes *self.pcl2_cloud* to store the `PointCloud2` message. The second line creates a `tf.TransformListener` object. Once the listener is created, it starts receiving tf transformations over the wire, and buffers them for up to 10 seconds.
```python
def callback_pcl2(self,msg):
"""
Callback function that stores the PointCloud2 message.
:param self: The self reference.
:param msg: The PointCloud2 message type.
"""
self.pcl2_cloud = msg
```
The callback function that stores the the `PointCloud2` message.
```python
temp_cloud = PointCloud()
temp_cloud.header = self.pcl2_cloud.header
```
Create a `PointCloud` for temporary use. Set the temporary PointCloud's header to the stored PointCloud2 header.
```python
for data in pc2.read_points(self.pcl2_cloud, skip_nans=True):
temp_cloud.points.append(Point32(data[0],data[1],data[2]))
```
Use a for loop to extract `PointCloud2` data into a list of x, y, z points and append those values to the `PointCloud` message, *temp_cloud*.
```python
transformed_cloud = self.transform_pointcloud(temp_cloud)
```
Utilize the `transform_pointcloud` function to transform the points in the `PointCloud` message to reference the *base_link*
```python
while not rospy.is_shutdown():
try:
new_cloud = self.listener.transformPointCloud("/base_link" ,msg)
return new_cloud
if new_cloud:
break
except (tf.LookupException, tf.ConnectivityException,tf.ExtrapolationException):
pass
```
Try to look up and transform the `PointCloud` input. Use a try-except block, since it may fail on any single call, due to internal timing issues in the transform publishers. Transform the point cloud data from *camera_color_optical_frame* to *base_link* with the `transformPointCloud()` function.
```python
self.pointcloud_pub.publish(transformed_cloud)
```
Publish the new transformed `PointCloud`.
```python
rospy.init_node('pointcloud_transformer',anonymous=True)
PCT = PointCloudTransformer()
```
The next line, `rospy.init_node(NAME, ...)`, is very important as it tells rospy the name of your node -- until rospy has this information, it cannot start communicating with the ROS Master. In this case, your node will take on the name talker. NOTE: the name must be a base name, i.e. it cannot contain any slashes "/".
Declare object, *PCT*, from the `PointCloudTransformer` class.
```python
rate = rospy.Rate(1)
rospy.sleep(1)
```
The first line gives the listener some time to accumulate transforms. The second line is the rate the node is going to publish information (1 Hz).
```python
# Run while loop until the node is shutdown
while not rospy.is_shutdown():
# Run the pcl_transformer method
PCT.pcl_transformer()
rate.sleep()
```
Run a while loop until the node is shutdown. Within the while loop run the `pcl_transformer()` method.

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