Source code for ouster.client.core

"""Ouster sensor Python client.

This module contains more idiomatic wrappers around the lower-level module
generated using pybind11.
from contextlib import closing
from more_itertools import take
from typing import cast, Iterable, Iterator, List, Optional, Tuple
from typing_extensions import Protocol
from threading import Thread
import time

from . import _client
from . import (ColHeader, SensorInfo, ImuPacket, LidarPacket, LidarScan,

[docs]class ClientError(Exception): """Base class for client errors.""" pass
[docs]class ClientTimeout(ClientError): """Raised when data does not arrive within the expected time.""" pass
[docs]class ClientOverflow(ClientError): """Raised when data loss is possible due to internal buffers filling up.""" pass
[docs]class PacketSource(Protocol): """Represents a single-sensor data stream."""
[docs] def __iter__(self) -> Iterator[Packet]: """A PacketSource supports ``Iterable[Packet]``. Currently defined explicitly due to: """ ...
@property def metadata(self) -> SensorInfo: """Metadata associated with the packet stream.""" ...
[docs] def close(self) -> None: """Release the underlying resource, if any.""" ...
[docs]class Packets(PacketSource): """Create a :class:`PacketSource` from an existing iterator.""" _it: Iterator[Packet] _metadata: SensorInfo def __init__(self, it: Iterable[Packet], metadata: SensorInfo): """ Args: it: A stream of packets metadata: Metadata for the packet stream """ self._it = iter(it) self._metadata = metadata @property def metadata(self) -> SensorInfo: return self._metadata
[docs] def __iter__(self) -> Iterator[Packet]: """Return the underlying iterator.""" return self._it
[docs] def close(self) -> None: pass
[docs]class Sensor(PacketSource): """A packet source listening on local UDP ports. Uses a separate thread that fills internal buffers without holding the GIL. Note: Make sure ``close()`` will be called on all instances before Python attempts to exit, or the interpreter will hang waiting to join the thread (like any other non-daemonized Python thread). """ _cli: _client.Client _timeout: Optional[float] _metadata: SensorInfo _pf: _client.PacketFormat _producer: Thread _cache: Optional[Tuple[_client.ClientState, bytearray]] def __init__(self, hostname: str = "localhost", lidar_port: int = 7502, imu_port: int = 7503, *, metadata: Optional[SensorInfo] = None, buf_size: int = 128, timeout: Optional[float] = 1.0, _overflow_err: bool = False, _flush_before_read: bool = True) -> None: """ Neither the ports nor udp destination configuration on the sensor will be updated. The metadata will be fetched over the network from the sensor unless explicitly provided using the ``metadata`` parameter. Args: hostname: hostname of the sensor lidar_port: UDP port to listen on for lidar data imu_port: UDP port to listen on for imu data metadata: explicitly provide metadata for the stream buf_size: number of packets to buffer before dropping data timeout: seconds to wait for packets before signaling error or None _overflow_err: if True, raise ClientOverflow _flush_before_read: if True, try to clear buffers before reading Raises: ClientError: If initializing the client fails. """ self._cli = _client.Client(hostname, lidar_port, imu_port, buf_size) self._timeout = timeout self._overflow_err = _overflow_err self._flush_before_read = _flush_before_read self._cache = None self._fetched_meta = "" # Fetch from sensor if not explicitly provided if metadata: self._metadata = metadata else: self._fetch_metadata() self._metadata = SensorInfo(self._fetched_meta) self._pf = _client.PacketFormat.from_info(self._metadata) # Use args to avoid capturing self causing circular reference self._producer = Thread(target=lambda cli, pf: cli.produce(pf), args=(self._cli, self._pf)) self._producer.start() def _fetch_metadata(self) -> None: if not self._fetched_meta: self._fetched_meta = self._cli.get_metadata() if not self._fetched_meta: raise ClientError("Failed to collect metadata")
[docs] def write_metadata(self, path: str) -> None: """Save metadata to disk. Args: path: path to write """ self._fetch_metadata() with open(path, 'w') as f: f.write(self._fetched_meta)
@property def metadata(self) -> SensorInfo: return self._metadata def _next_packet(self) -> Optional[Packet]: if self._cache is None: # Lidar packets are bigger than IMU: wastes some space but is simple buf = bytearray(self._pf.lidar_packet_size) st = self._cli.consume(buf, self._timeout or 0) else: st, buf = self._cache self._cache = None if self._overflow_err and st & _client.ClientState.OVERFLOW: raise ClientOverflow() if st & _client.ClientState.LIDAR_DATA: return LidarPacket(buf, self._metadata) elif st & _client.ClientState.IMU_DATA: return ImuPacket(buf, self._metadata) elif st == _client.ClientState.TIMEOUT: raise ClientTimeout(f"No packets received within {self._timeout}s") elif st & _client.ClientState.ERROR: raise ClientError("Client returned ERROR state") elif st & _client.ClientState.EXIT: return None raise AssertionError("Should be unreachable") def _peek(self) -> Tuple[_client.ClientState, bytearray]: if self._cache is None: # Lidar packets are bigger than IMU: wastes some space but is simple buf = bytearray(self._pf.lidar_packet_size) st = self._cli.consume(buf, self._timeout or 0) self._cache = (st, buf) return self._cache
[docs] def __iter__(self) -> Iterator[Packet]: """Access the UDP data stream as an iterator. Reading may block waiting for network data for up to the specified timeout. Failing to consume this iterator faster than the data rate of the sensor may cause packets to be dropped. Raises: ClientTimeout: if no packets are received within the configured timeout. ClientError: if the client enters an unspecified error state. ValueError: if the packet source has already been closed """ # Attempt to flush any old data before producing packets if self._flush_before_read: self.flush(full=True) while True: p = self._next_packet() if p is not None: yield p else: raise ValueError("I/O operation on closed packet source")
[docs] def flush(self, n_frames: int = 3, *, full=False) -> int: """Drop some data to clear internal buffers. Args: n_frames: number of frames to drop full: clear internal buffers first, so data is read from the OS receive buffers (or the network) directly Raises: ClientTimeout: if a lidar packet is not received within the configured timeout. """ if full: self._cli.flush() last_frame = -1 n_dropped = 0 last_ts = time.monotonic() while True: st, buf = self._peek() if st & _client.ClientState.LIDAR_DATA: frame = LidarPacket(buf, self._metadata).header( ColHeader.FRAME_ID)[0] if frame != last_frame: last_frame = frame n_frames -= 1 if n_frames < 0: break last_ts = time.monotonic() if self._timeout is not None and (time.monotonic() >= last_ts + self._timeout): raise ClientTimeout( f"No packets received within {self._timeout}s") # call for effect and drop packet try: if self._next_packet() is None: break except ClientOverflow: pass n_dropped += 1 return n_dropped
def buf_use(self) -> int: return self._cli.size
[docs] def close(self) -> None: """Shut down producer thread and close network connection. Attributes may be unset if constructor throws an exception. """ if hasattr(self, '_cli'): self._cli.shutdown() if hasattr(self, '_producer'): self._producer.join()
def __del__(self) -> None: self.close()
[docs]class Scans: """An iterable stream of scans batched from a PacketSource. Batching will emit a scan every time the frame_id increments (i.e. on receiving first packet in the next scan). Reordered packets will be handled, except across frame boundaries: packets from the previous scan will be dropped. Optionally filters out incomplete frames and enforces a timeout. A batching timeout can be useful to detect when we're only receiving incomplete frames or only imu packets. Can also be configured to manage internal buffers for soft real-time applications. """ def __init__(self, source: PacketSource, *, complete: bool = False, timeout: Optional[float] = None, _max_latency: int = 0) -> None: """ Args: source: any source of packets complete: if True, only return full scans timeout: seconds to wait for a scan before error or None _max_latency: (experimental) approximate max number of frames to buffer """ self._source = source self._complete = complete self._timeout = timeout self._max_latency = _max_latency
[docs] def __iter__(self) -> Iterator[LidarScan]: """Get an iterator.""" w = self._source.metadata.format.columns_per_frame h = self._source.metadata.format.pixels_per_column packets_per_frame = w // self._source.metadata.format.columns_per_packet column_window = self._source.metadata.format.column_window # If source is a sensor, make a type-specialized reference available sensor = cast(Sensor, self._source) if isinstance( self._source, Sensor) else None ls_write = _client.LidarScan(w, h) pf = _client.PacketFormat.from_info(self._source.metadata) batch = _client.ScanBatcher(w, pf) # Time from which to measure timeout start_ts = time.monotonic() it = iter(self._source) while True: try: packet = next(it) except StopIteration: return if self._timeout is not None and (time.monotonic() >= start_ts + self._timeout): raise ClientTimeout(f"No lidar scans within {self._timeout}s") if isinstance(packet, LidarPacket): if batch(packet._data, ls_write): # Got a new frame, return it and start another ls = LidarScan.from_native(ls_write) if not self._complete or ls._complete(column_window): yield ls start_ts = time.monotonic() ls_write = _client.LidarScan(w, h) # Drop data along frame boundaries to maintain _max_latency and # clear out already-batched first packet of next frame if self._max_latency and sensor is not None: buf_frames = sensor.buf_use() // packets_per_frame drop_frames = buf_frames - self._max_latency + 1 if drop_frames > 0: sensor.flush(drop_frames) batch = _client.ScanBatcher(w, pf)
[docs] def close(self) -> None: """Close the underlying PacketSource.""" self._source.close()
@property def metadata(self) -> SensorInfo: """Return metadata from the underlying PacketSource.""" return self._source.metadata
[docs] @classmethod def sample( cls, hostname: str = "localhost", n: int = 1, lidar_port: int = 7502, *, metadata: Optional[SensorInfo] = None ) -> Tuple[SensorInfo, Iterator[List[LidarScan]]]: """Conveniently sample n consecutive scans from a sensor. Does not leave UDP ports open. Suitable for interactive use. Args: hostname: hostname of the sensor n: number of consecutive frames in each sample lidar_port: UDP port to listen on for lidar data metadata: explicitly provide metadata for the stream Returns: A tuple of metadata queried from the sensor and an iterator that samples n consecutive scans """ with closing(Sensor(hostname, metadata=metadata)) as sensor: metadata = sensor.metadata def next_batch() -> List[LidarScan]: with closing( Sensor(hostname, lidar_port, metadata=metadata, buf_size=n * 128, _flush_before_read=False)) as source: source.flush(full=True) scans = cls(source, timeout=1.0, complete=True, _max_latency=0) return take(n, scans) return metadata, iter(next_batch, [])
[docs] @classmethod def stream(cls, hostname: str = "localhost", lidar_port: int = 7502, *, buf_size: int = 640, timeout: float = 1.0, complete: bool = True, metadata: Optional[SensorInfo] = None) -> 'Scans': """Stream scans from a sensor. Will drop frames preemptively to avoid filling up internal buffers and to avoid returning frames older than the scanning period of the sensor. Args: hostname: hostname of the sensor lidar_port: UDP port to listen on for lidar data timeout: seconds to wait for scans before signaling error complete: if True, only return full scans metadata: explicitly provide metadata for the stream """ source = Sensor(hostname, lidar_port, metadata=metadata, buf_size=buf_size, timeout=timeout, _flush_before_read=True) return cls(source, timeout=timeout, complete=complete, _max_latency=2)