Using the new ScanSource interface

In this example we are going to demonstrate the use of the new ScanSource API.

Using the open_source method

The new API introduces a new method name open_source which allows users to handle different source types using the same API. Current supported source types are live sensor, pcap file, or osf file. For example, to open the same pcap file referenced in the main Quick Start using the simplified API can be accomplished as follows:

>>> pcap_path = '<SAMPLE_DATA_PCAP_PATH>'
>>> metadata_path = '<SAMPLE_DATA_JSON_PATH>'
>>> from ouster.sdk import open_source
>>> source = open_source(pcap_path, meta=[metadata_path])

The source handle here acts the same as the handle returned by the pcap.Pcap constructor, with some extra capabilities that we will cover later.

Notice here that rather than we try to load and parse the metadata ourselves we only need to pass to metadata to the method through meta parameter and the method will take care of loading it and associating it with the source object. The meta parameter however is optional and can be omitted. When the meta parameter is not set explicity the open_source method will attempt to locate the metadata automatically for us and we can reduce the call to:

However if metadata file is not in the same folder as the pcap and don’t have a shared name prefix the method will fail.

Note

Another optional but important parameter for the open_source method is sensor_idx. This paramter is to zero by default, which should always be the case unless the pcap file that you are using (or osf or any LidarScan storage) contains scans from more than one sensor, in this case, users can set the sensor_idx to a any value between zero and sensors_count -1 to access and manipulate scans from a specific sensor by the order they appear in the file. Alternatively, if users set the value of sensor_idx to -1 then open_source will return a slightly differnt interface from ScanSource which is the MultiScanSource this interface and as the name suggests allows users to work with sensor data collected from multiple sensors at the same time.

The main different between the MultiScanSource and the ScanSource is the expected return of some of the object methods. For example, when creating an iterator for a ScanSource object, the user would get a single LidarScan object per iteration. Iterating over the contents of a MultiScanSource object always yields a list of LidarScan(s) per iteration corresponding to the number of sensors stored in the pcap file or whatever source type is being used. This is true even when the pcap file contains data for a single sensor.

On the other hand, if the user wants to open an osf file or access the a live sensor, all that changes is url of the source. For example, to interact with a live sensor the user can execute the following snippet:

>>> sensor_url = '<SENSOR-HOSTNAME-OR-IP>'
>>> from ouster.sdk import open_source
>>> source = open_source(sensor_url)

Obtaining sensor metadata

Every ScanSource holds a reference to the sensor metadata, which has crucial information that is important when when processing the invidivual scans. Continuing the example, a user this can access the metadata through the metadata property of a ScanSource object:

>>> print(source.metadata)

Iterating over Scans

Once we have successfully obtain a handle to the ScanSource we can iterate over LidarScan objects stored in the pcap file and manipulate each one individually. For example, let’s say we want to print the frame id of the first 10 scans. We can achieve that using:

>>> ctr = 0
>>> source_iter = iter(source)
>>> for scan in source_iter:
...     print(scan.frame_id)
...     ctr += 1
...     if ctr == 10:
...         break

As we noted earlier, if we set sensor_idx=-1 when invoking open_source method, the method will construct a MultiScanSource, which always addresses a group of sensors. Thus, when iterating over the source the user receives a collated set of scans from the addressed sensors per iteration. The MultiScanSource examines the timestamp of every scan from every sensor and returns a list of scans that fit within the same time window as single batch. The size of the batch is fixed corresponding to how many sensors contained in the pcap or osf file. However, the collation could yield a null value if one or more of the sensors didn’t produce a LidarScan object that fits within the time frame of current batch or iteration. Thus, depending on the operation at hand it is crticial to check if we got a valid LidarScan object when examining the iteration output of a MultiScanSource. If we are to perform the same example as above when source is a handle to MultiScanSource and display the frame_id of LidarScan objects the belongs to the same batch on the same line the code needs to updated to the following:

>>> ctr = 0
>>> source_iter = iter(source)
>>> for scans in source_iter:
...     for scan in scans:    # source_iter here returns a list of scans
...         if scan:          # check if invidiual scan object is valid
...             print(scan.frame_id, end=', ')
...     print()   # new line for next batch
...     ctr += 1
...     if ctr == 10:
...         break

Note that when iterating over a MultiScanSource object, it always a list of scans, even when the underlying scan source has only a single sensor. In this case, the iterator will yield a list with a single element per iteration.

Using indexing and slicing capabilities of a ScanSource

One of the most prominent new features of the ScanSource API, (besides being able to address multi sensors), is the ability to use indexing and slicing when accessing the stored scans within the LidarScan source. Currently, this capability is only supported for non-live sources. That is to say, the functionality we are discussing can only be used when accessing a pcap or an osf file. To enable this functionality we need to indicate that we want to manipulate the source as an indexed one upon opening. Revisitng the previous pcap open example, that would be achieved as follows: :

>>> pcap_path = '<SAMPLE_DATA_PCAP_PATH>'
>>> from ouster.sdk import open_source
>>> source = open_source(pcap_path, index=True)

First note that we omitted the meta parameter since it can be populated automatically as we explained earlier. Second you will noticed that we introduced a new parameter index with its value set to True (default is false), The same parameter can be applied to when dealing with an osf file but not a live sensor.

Depending on the file size and the underlying file format there can be some delay before the file is fully indexed (OSF file take much less time than pcap file to index). A progress bar will appear to indicate progress of the indexing.

Once the index is built up, then we can start using utilizing and interact with the ScanSource object to access scans in the same manner we are dealing with a python list that holds reference to LidarScan objects.

For example to access the 10th LidarScan and print its frame id, we can do the following:

>>> print(source[10].frame_id)

Similarly we can access the last LidarScan object and print its frame_id using:

>>> print(source[-1].frame_id)

Alternatively we can instead request a range of scans using the python slice operator. For example, to request the first 10 scans from a ScanSource and print their frame ids, we can do the following:

>>> for scan in source[0:10]:
...     print(scan.frame_id)

Note we don’t need to add any break here since the operation source[0:10] will only yield the first 10 LidarScan(s).

To print frame_id of the last 10 LidarScans we do:

>>> for scan in source[-11:-1]:
...     print(scan.frame_id)

Finally, as you would expect from a typical slice operation, you can also using negative step and also use a reversed iteration as shown in the following example:

>>> for scan in source[0:10:2]:     # prints the frame_id of every second scan of the first 10 scans
...     print(scan.frame_id)

>>> for scan in source[10:0:-1]:     # prints the frame_id of every scan of the first 10 scans in reverse
...     print(scan.frame_id)