TOF Depth Image Encoding changed from 32FC1 to mono8
I have a TOF sensor.
A little while ago, to see the depth image, I would
rostopic echo /tof/depth. When I did that, the ROS message would be of the type
sensor_imgs/Imageand its encoding would be
Today, with the latest code, I need to use
rostopic echo /mpa/tof_depthto get the depth image. When I do that, the ROS message is still of the type
sensor_imgs/Imagebut its encoding is
Historically, if I wanted to process the depth image in ROS, I would setup a subscriber and use code like that shown below to ingest the data as a depth image. I could then access individual pixels to get the depth (in meters).
I'm now sure how to process a depth image of encoding
mono8. It seems like it would have too few bits to represent the resolution of depths possible.
mono8encoding intentional (with the conversion to the latest mpa_to_ros)? Or is it a bug?
If it's intentional, can you help me understand how to process this new data encoding and extract the distances of individual pixels (similar to the code posted below)?
# get the depth image dep_frame = np.fromstring(tof_depth.data, dtype=np.single) dep_frame = dep_frame.reshape(172, 224) # Get closest value in bounding box object_depth_map = dep_frame[top:bottom,left:right] object_depth_map[object_depth_map == 0] = 9999.00 object_depth = np.min(object_depth_map)
MPA_to_ROS was recently updated to a new architecture, the depth image that we publish was meant to be more of a debug tool where the z value of the pointcloud is scaled from 0-255 for 0-1 meter distance, but it looks like the old mpa to ros instead published the z value of the sensor, which is floating point. To get the same old value that you were looking at, you should access the pointcloud tof message and look at the z value.
For anyone who runs into this same issue, I changed my subscriber to listen to
/map/tof_pc(which has the
PointCloud2type). My code (to extract the z value) is this:
# get the depth image dep_frame = np.fromstring(data.data, dtype=np.single) # get numpy array dep_frame = dep_frame.reshape(172, 224, 3)[:,:,2]