def test_write_info(metadata: client.SensorInfo) -> None:
"""Check modifying metadata."""
metadata.hostname = ""
metadata.sn = ""
metadata.fw_rev = ""
metadata.mode = client.LidarMode.MODE_UNSPEC
metadata.prod_line = ""
metadata.format.columns_per_frame = 0
metadata.format.columns_per_packet = 0
metadata.format.pixels_per_column = 0
metadata.format.column_window = (0, 0)
metadata.format.pixel_shift_by_row = []
metadata.beam_azimuth_angles = []
metadata.beam_altitude_angles = []
metadata.imu_to_sensor_transform = numpy.zeros((4, 4))
metadata.lidar_to_sensor_transform = numpy.zeros((4, 4))
metadata.extrinsic = numpy.zeros((4, 4))
metadata.lidar_origin_to_beam_origin_mm = 0.0
assert metadata == client.SensorInfo()
with pytest.raises(TypeError):
metadata.mode = 1 # type: ignore
with pytest.raises(TypeError):
metadata.imu_to_sensor_transform = numpy.zeros((4, 5))
with pytest.raises(TypeError):
metadata.lidar_to_sensor_transform = numpy.zeros((3, 4))
with pytest.raises(TypeError):
metadata.extrinsic = numpy.zeros(16)
with pytest.raises(TypeError):
metadata.beam_altitude_angles = 1 # type: ignore
with pytest.raises(TypeError):
metadata.beam_azimuth_angles = ["foo"] # type: ignore
def main() -> None:
descr = """Visualize pcap or sensor data using simple viz bindings."""
epilog = """When reading data from a sensor, this will autoconfigure the udp
destination unless -x is used."""
parser = argparse.ArgumentParser(description=descr, epilog=epilog)
required = parser.add_argument_group('one of the following is required')
group = required.add_mutually_exclusive_group(required=True)
group.add_argument('--sensor', metavar='HOST', help='sensor hostname')
group.add_argument('--pcap', metavar='PATH', help='path to pcap file')
parser.add_argument('--meta', metavar='PATH', help='path to metadata json')
parser.add_argument('--lidar-port', type=int, help='lidar port for sensor')
parser.add_argument('-x',
'--no-auto-dest',
action='store_true',
help='do not auto configure udp destination')
args = parser.parse_args()
if args.sensor:
hostname = args.sensor
if args.lidar_port or (not args.no_auto_dest):
config = client.SensorConfig()
if args.lidar_port:
config.udp_port_lidar = args.lidar_port
print("Configuring sensor...")
client.set_config(hostname,
config,
udp_dest_auto=(not args.no_auto_dest))
config = client.get_config(hostname)
print("Initializing...")
scans = client.Scans.stream(hostname,
config.udp_port_lidar or 7502,
complete=False)
rate = None
elif args.pcap:
import ouster.pcap as pcap
if args.meta:
metadata_path = args.meta
else:
print("Deducing metadata based on pcap name. "
"To provide a different metadata path, use --meta")
metadata_path = os.path.splitext(args.pcap)[0] + ".json"
with open(metadata_path) as json:
info = client.SensorInfo(json.read())
scans = client.Scans(pcap.Pcap(args.pcap, info))
rate = 1.0
SimpleViz(scans.metadata, rate).run(scans)
def read_metadata(metadata_path: str) -> client.SensorInfo:
"""Read metadata json file as :class:`.client.SensorInfo` object
Args:
metadata_path: path to json file with sensor info
Returns:
:class:`.SensorInfo`: object initialized from the give json file
"""
with open(metadata_path, 'r') as f:
return client.SensorInfo(f.read())
def main():
"""Pcap examples runner."""
examples = {
"plot-xyz-points": pcap_display_xyz_points,
"2d-viewer": pcap_2d_viewer,
"read-packets": pcap_read_packets,
"plot-one-scan": pcap_show_one_scan,
"pcap-to-csv": pcap_to_csv,
"pcap-to-pcd": pcap_to_pcd,
"pcap-to-las": pcap_to_las,
"open3d-one-scan": pcap_3d_one_scan,
}
description = "Ouster Python SDK Pcap examples. The EXAMPLE must be one of:\n" + str.join(
'\n ', examples.keys())
parser = argparse.ArgumentParser(
description=description, formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('pcap_path', metavar='PCAP', help='path to pcap file')
parser.add_argument('metadata_path',
metavar='METADATA',
help='path to metadata json')
parser.add_argument('example',
metavar='EXAMPLE',
choices=examples.keys(),
help='name of the example to run')
parser.add_argument('--scan-num',
type=int,
default=1,
help='index of scan to use')
args = parser.parse_args()
try:
example = examples[args.example]
except KeyError:
print(f"No such example: {args.example}")
print(description)
exit(1)
if not args.metadata_path or not os.path.exists(args.metadata_path):
print(f"Metadata file does not exist: {args.metadata_path}")
exit(1)
print(f'example: {args.example}')
with open(args.metadata_path, 'r') as f:
metadata = client.SensorInfo(f.read())
source = pcap.Pcap(args.pcap_path, metadata)
with closing(source):
example(source, metadata, args.scan_num) # type: ignore
def main() -> None:
import argparse
import os
import ouster.pcap as pcap
descr = """Example visualizer using the open3d library.
Visualize either pcap data (specified using --pcap) or a running sensor
(specified using --sensor). If no metadata file is specified, this will look
for a file with the same name as the pcap with the '.json' extension, or
query it directly from the sensor.
Visualizing a running sensor requires the sensor to be configured and
sending lidar data to the default UDP port (7502) on the host machine.
"""
parser = argparse.ArgumentParser(description=descr)
parser.add_argument('--pause', action='store_true', help='start paused')
parser.add_argument('--start', type=int, help='skip to frame number')
parser.add_argument('--meta', metavar='PATH', help='path to metadata json')
required = parser.add_argument_group('one of the following is required')
group = required.add_mutually_exclusive_group(required=True)
group.add_argument('--sensor', metavar='HOST', help='sensor hostname')
group.add_argument('--pcap', metavar='PATH', help='path to pcap file')
args = parser.parse_args()
if args.sensor:
scans = client.Scans.stream(args.sensor, metadata=args.meta)
elif args.pcap:
pcap_path = args.pcap
metadata_path = args.meta or os.path.splitext(pcap_path)[0] + ".json"
with open(metadata_path, 'r') as f:
metadata = client.SensorInfo(f.read())
source = pcap.Pcap(pcap_path, metadata)
scans = client.Scans(source)
consume(scans, args.start or 0)
try:
viewer_3d(scans, paused=args.pause)
except (KeyboardInterrupt, StopIteration):
pass
finally:
scans.close()
def test_parse_info() -> None:
"""Sanity check parsing from json."""
with pytest.raises(ValueError):
client.SensorInfo('/')
with pytest.raises(ValueError):
client.SensorInfo('')
with pytest.raises(ValueError):
client.SensorInfo('{ }')
with pytest.raises(ValueError):
client.SensorInfo('{ "lidar_mode": "1024x10" }')
# TODO: this should actually fail unless *all* parameters needed to
# unambiguously interpret a sensor data stream are present
metadata = {
'lidar_mode': '1024x10',
'beam_altitude_angles': [0] * 64,
'beam_azimuth_angles': [0] * 64,
'lidar_to_sensor_transform': list(range(16))
}
info = client.SensorInfo(json.dumps(metadata))
# check that data format defaults are populated
assert info.format.pixels_per_column == 64
assert info.format.columns_per_frame == 1024
assert info.format.columns_per_packet > 0
assert info.format.column_window[0] == 0
assert info.format.column_window[1] == 1023
assert len(info.format.pixel_shift_by_row) == 64
# the lidar_to_sensor_transform json is interpreted as a 4x4 matrix in
# row-major order. Numpy also uses row-major storage order.
assert numpy.array_equal(info.lidar_to_sensor_transform,
numpy.array(range(16)).reshape(4, 4))
assert numpy.array_equal(info.extrinsic, numpy.identity(4))
metadata['lidar_origin_to_beam_origin_mm'] = 'foo'
with pytest.raises(RuntimeError):
client.SensorInfo(json.dumps(metadata))
def main():
"""Pcap examples runner."""
examples = {
"open3d-one-scan": pcap_3d_one_scan,
"plot-xyz-points": pcap_display_xyz_points,
"pcap-to-csv": pcap_to_csv,
"pcap-to-las": pcap_to_las,
"pcap-to-pcd": pcap_to_pcd,
"pcap-to-ply": pcap_to_ply,
"query-scan": pcap_query_scan,
"read-packets": pcap_read_packets,
}
description = "Ouster Python SDK Pcap examples. The EXAMPLE must be one of:\n " + str.join(
'\n ', examples.keys())
parser = argparse.ArgumentParser(
description=description, formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('pcap_path', metavar='PCAP', help='path to pcap file')
parser.add_argument('metadata_path',
metavar='METADATA',
help='path to metadata json')
parser.add_argument('example',
metavar='EXAMPLE',
choices=examples.keys(),
help='name of the example to run')
parser.add_argument('--scan-num',
type=int,
default=1,
help='index of scan to use')
args = parser.parse_args()
try:
example = examples[args.example]
except KeyError:
print(f"No such example: {args.example}")
print(description)
exit(1)
if not args.metadata_path or not os.path.exists(args.metadata_path):
print(f"Metadata file does not exist: {args.metadata_path}")
exit(1)
with open(args.metadata_path, 'r') as f:
metadata = client.SensorInfo(f.read())
if (metadata.format.udp_profile_lidar !=
client.UDPProfileLidar.PROFILE_LIDAR_LEGACY
and metadata.format.udp_profile_lidar !=
client.UDPProfileLidar.PROFILE_LIDAR_RNG19_RFL8_SIG16_NIR16
and args.example != 'query-scan'):
print(
f"This pcap example is only for pcaps of sensors in LEGACY or SINGLE RETURN mode. Exiting..."
)
exit(1)
print(f'example: {args.example}')
source = pcap.Pcap(args.pcap_path, metadata)
with closing(source):
example(source, metadata, args.scan_num) # type: ignore
TODO:
- separate set scan / update is annoying
- a proxy run()/quit() on ls_viz would be useful
- maybe: ls_viz could initialize underlying viz + expose it
- point_viz.run() twice is broken
- ideally, run() would open/close window
- auto camera movement example?
"""
from ouster import client, pcap
from ouster.sdk import viz
meta_path = "/mnt/aux/test_drives/OS1_128_2048x10.json"
pcap_path = "/mnt/aux/test_drives/OS1_128_2048x10.pcap"
meta = client.SensorInfo(open(meta_path).read())
packets = pcap.Pcap(pcap_path, meta)
scans = iter(client.Scans(packets))
point_viz = viz.PointViz("Example Viz")
ls_viz = viz.LidarScanViz(meta, point_viz)
ls_viz.scan = next(scans)
ls_viz.draw()
print("Showing first frame, close visuzlier window to continue")
point_viz.run()
ls_viz.scan = next(scans)
ls_viz.draw()
print("Showing second frame, close visuzlier window to continue")
point_viz.run()
def metadata():
meta_path = os.path.join(DATA_DIR, "os-992011000121_meta.json")
with open(meta_path, 'r') as f:
return client.SensorInfo(f.read())
def main():
"""PointViz visualizer examples."""
parser = argparse.ArgumentParser(
description=main.__doc__,
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('pcap_path',
nargs='?',
metavar='PCAP',
help='path to pcap file')
parser.add_argument('meta_path',
nargs='?',
metavar='METADATA',
help='path to metadata json')
args = parser.parse_args()
pcap_path = os.getenv("SAMPLE_DATA_PCAP_PATH", args.pcap_path)
meta_path = os.getenv("SAMPLE_DATA_JSON_PATH", args.meta_path)
if not pcap_path or not meta_path:
print("ERROR: Please add SAMPLE_DATA_PCAP_PATH and SAMPLE_DATA_JSON_PATH to" +
" environment variables or pass <pcap_path> and <meta_path>")
sys.exit()
print(f"Using:\n\tjson: {meta_path}\n\tpcap: {pcap_path}")
# Getting data sources
meta = client.SensorInfo(open(meta_path).read())
packets = pcap.Pcap(pcap_path, meta)
scans = iter(client.Scans(packets))
# ==============================
print("Ex 0: Empty Point Viz")
# [doc-stag-empty-pointviz]
# Creating a point viz instance
point_viz = viz.PointViz("Example Viz")
viz.add_default_controls(point_viz)
# ... add objects here
# update internal objects buffers and run visualizer
point_viz.update()
point_viz.run()
# [doc-etag-empty-pointviz]
# =========================================================================
print("Ex 1.0:\tImages and Labels: the Image object and 2D Image set_position() - height-normalized screen coordinates")
label_top = viz.Label("[0, 1]", 0.5, 0.0, align_top=True)
label_top.set_scale(2)
point_viz.add(label_top)
label_bot = viz.Label("[0, -1]", 0.5, 1, align_top=False)
label_bot.set_scale(2)
point_viz.add(label_bot)
# [doc-stag-image-pos-center]
img = viz.Image()
img.set_image(np.full((10, 10), 0.5))
img.set_position(-0.5, 0.5, -0.5, 0.5)
point_viz.add(img)
# [doc-etag-image-pos-center]
# visualize
point_viz.update()
point_viz.run()
# =========================================================================
print("Ex 1.1:\tImages and Labels: Window-aligned images with 2D Image set_hshift() - width-normalized [-1, 1] horizontal shift")
# [doc-stag-image-pos-left]
# move img to the left
img.set_position(0, 1, -0.5, 0.5)
img.set_hshift(-1)
# [doc-etag-image-pos-left]
# visualize
point_viz.update()
point_viz.run()
# [doc-stag-image-pos-right]
# move img to the right
img.set_position(-1, 0, -0.5, 0.5)
img.set_hshift(1)
# [doc-etag-image-pos-right]
# visualize
point_viz.update()
point_viz.run()
# [doc-stag-image-pos-right-bottom]
# move img to the right bottom
img.set_position(-1, 0, -1, 0)
img.set_hshift(1)
# [doc-etag-image-pos-right-bottom]
# visualize
point_viz.update()
point_viz.run()
# remove_objs(point_viz, [label_top, label_mid, label_bot, img])
remove_objs(point_viz, [label_top, label_bot, img])
# =======================================
print("Ex 1.2:\tImages and Labels: Lidar Scan Fields as Images")
# [doc-stag-scan-fields-images]
scan = next(scans)
img_aspect = (meta.beam_altitude_angles[0] -
meta.beam_altitude_angles[-1]) / 360.0
img_screen_height = 0.4 # [0..2]
img_screen_len = img_screen_height / img_aspect
# prepare field data
ranges = scan.field(client.ChanField.RANGE)
ranges = client.destagger(meta, ranges)
ranges = np.divide(ranges, np.amax(ranges), dtype=np.float32)
signal = scan.field(client.ChanField.SIGNAL)
signal = client.destagger(meta, signal)
signal = np.divide(signal, np.amax(signal), dtype=np.float32)
# creating Image viz elements
range_img = viz.Image()
range_img.set_image(ranges)
# top center position
range_img.set_position(-img_screen_len / 2, img_screen_len / 2,
1 - img_screen_height, 1)
point_viz.add(range_img)
signal_img = viz.Image()
signal_img.set_image(signal)
img_aspect = (meta.beam_altitude_angles[0] -
meta.beam_altitude_angles[-1]) / 360.0
img_screen_height = 0.4 # [0..2]
img_screen_len = img_screen_height / img_aspect
# bottom center position
signal_img.set_position(-img_screen_len / 2, img_screen_len / 2, -1,
-1 + img_screen_height)
point_viz.add(signal_img)
# [doc-etag-scan-fields-images]
# visualize
point_viz.update()
point_viz.run()
print("Ex 1.3:\tImages and Labels: Adding labels")
# [doc-stag-scan-fields-images-labels]
range_label = viz.Label(str(client.ChanField.RANGE), 0.5, 0, align_top=True)
range_label.set_scale(1)
point_viz.add(range_label)
signal_label = viz.Label(str(client.ChanField.SIGNAL),
0.5, 1 - img_screen_height / 2,
align_top=True)
signal_label.set_scale(1)
point_viz.add(signal_label)
# [doc-etag-scan-fields-images-labels]
# visualize
point_viz.update()
point_viz.run()
# ===============================================================
print("Ex 2.0:\tPoint Clouds: As Structured Points")
# [doc-stag-scan-structured]
cloud_scan = viz.Cloud(meta)
cloud_scan.set_range(scan.field(client.ChanField.RANGE))
cloud_scan.set_key(signal)
point_viz.add(cloud_scan)
# [doc-etag-scan-structured]
# visualize
point_viz.update()
point_viz.run()
remove_objs(point_viz, [cloud_scan])
# ===============================================================
print("Ex 2.1:\tPoint Clouds: As Unstructured Points")
# [doc-stag-scan-unstructured]
# transform scan data to 3d points
xyzlut = client.XYZLut(meta)
xyz = xyzlut(scan.field(client.ChanField.RANGE))
cloud_xyz = viz.Cloud(xyz.shape[0] * xyz.shape[1])
cloud_xyz.set_xyz(np.reshape(xyz, (-1, 3)))
cloud_xyz.set_key(signal.ravel())
point_viz.add(cloud_xyz)
# [doc-etag-scan-unstructured]
point_viz.camera.dolly(150)
# visualize
point_viz.update()
point_viz.run()
# =======================================================
print("Ex 2.2:\tPoint Clouds: Custom Axes Helper as Unstructured Points")
# [doc-stag-axes-helper]
# basis vectors
x_ = np.array([1, 0, 0]).reshape((-1, 1))
y_ = np.array([0, 1, 0]).reshape((-1, 1))
z_ = np.array([0, 0, 1]).reshape((-1, 1))
axis_n = 100
line = np.linspace(0, 1, axis_n).reshape((1, -1))
# basis vector to point cloud
axis_points = np.hstack((x_ @ line, y_ @ line, z_ @ line)).transpose()
# colors for basis vectors
axis_color_mask = np.vstack((
np.full((axis_n, 4), [1, 0.1, 0.1, 1]),
np.full((axis_n, 4), [0.1, 1, 0.1, 1]),
np.full((axis_n, 4), [0.1, 0.1, 1, 1])))
cloud_axis = viz.Cloud(axis_points.shape[0])
cloud_axis.set_xyz(axis_points)
cloud_axis.set_key(np.full(axis_points.shape[0], 0.5))
cloud_axis.set_mask(axis_color_mask)
cloud_axis.set_point_size(3)
point_viz.add(cloud_axis)
# [doc-etag-axes-helper]
point_viz.camera.dolly(50)
# visualize
point_viz.update()
point_viz.run()
remove_objs(point_viz, [
range_img, range_label, signal_img, signal_label, cloud_axis, cloud_xyz
])
# ===============================================================
print("Ex 2.3:\tPoint Clouds: the LidarScanViz class")
# [doc-stag-lidar-scan-viz]
# Creating LidarScan visualizer (3D point cloud + field images on top)
ls_viz = viz.LidarScanViz(meta, point_viz)
# adding scan to the lidar scan viz
ls_viz.scan = scan
# refresh viz data
ls_viz.draw()
# visualize
# update() is not needed for LidatScanViz because it's doing it internally
point_viz.run()
# [doc-etag-lidar-scan-viz]
# ===================================================
print("Ex 3.0:\tAugmenting point clouds with 3D Labels")
# [doc-stag-lidar-scan-viz-labels]
# Adding 3D Labels
label1 = viz.Label("Label1: [1, 2, 4]", 1, 2, 4)
point_viz.add(label1)
label2 = viz.Label("Label2: [2, 1, 4]", 2, 1, 4)
label2.set_scale(2)
point_viz.add(label2)
label3 = viz.Label("Label3: [4, 2, 1]", 4, 2, 1)
label3.set_scale(3)
point_viz.add(label3)
# [doc-etag-lidar-scan-viz-labels]
point_viz.camera.dolly(-100)
# visualize
point_viz.update()
point_viz.run()
# ===============================================
print("Ex 4.0:\tOverlay 2D Images and 2D Labels")
# [doc-stag-overlay-images-labels]
# Adding image 1 with aspect ratio preserved
img = viz.Image()
img_data = make_checker_board(10, (2, 4))
mask_data = np.zeros((30, 30, 4))
mask_data[:15, :15] = np.array([1, 0, 0, 1])
img.set_mask(mask_data)
img.set_image(img_data)
ypos = (0, 0.5)
xlen = (ypos[1] - ypos[0]) * img_data.shape[1] / img_data.shape[0]
xpos = (0, xlen)
img.set_position(*xpos, *ypos)
img.set_hshift(-0.5)
point_viz.add(img)
# Adding Label for image 1: positioned at bottom left corner
img_label = viz.Label("ARRrrr!", 0.25, 0.5)
img_label.set_rgba((1.0, 1.0, 0.0, 1))
img_label.set_scale(2)
point_viz.add(img_label)
# Adding image 2: positioned to the right of the window
img2 = viz.Image()
img_data2 = make_checker_board(10, (4, 2))
mask_data2 = np.zeros((30, 30, 4))
mask_data2[15:25, 15:25] = np.array([0, 1, 0, 0.5])
img2.set_mask(mask_data2)
img2.set_image(img_data2)
ypos2 = (0, 0.5)
xlen2 = (ypos2[1] - ypos2[0]) * img_data2.shape[1] / img_data2.shape[0]
xpos2 = (-xlen2, 0)
img2.set_position(*xpos2, *ypos2)
img2.set_hshift(1.0)
point_viz.add(img2)
# Adding Label for image 2: positioned at top left corner
img_label2 = viz.Label("Second", 1.0, 0.25, align_top=True, align_right=True)
img_label2.set_rgba((0.0, 1.0, 1.0, 1))
img_label2.set_scale(1)
point_viz.add(img_label2)
# [doc-etag-overlay-images-labels]
# visualize
point_viz.update()
point_viz.run()
# ===============================================================
print("Ex 5.0:\tAdding key handlers: 'R' for random camera dolly")
# [doc-stag-key-handlers]
def handle_dolly_random(ctx, key, mods) -> bool:
if key == 82: # key R
dolly_num = random.randrange(-15, 15)
print(f"Random Dolly: {dolly_num}")
point_viz.camera.dolly(dolly_num)
point_viz.update()
return True
point_viz.push_key_handler(handle_dolly_random)
# [doc-etag-key-handlers]
# visualize
point_viz.update()
point_viz.run()
def main() -> None:
descr = """Visualize pcap or sensor data using simple viz bindings."""
epilog = """When reading data from a sensor, this will currently not
configure the sensor or query it for the port to listen on. You will need to
set the sensor port and distination settings separately.
"""
parser = argparse.ArgumentParser(description=descr, epilog=epilog)
required = parser.add_argument_group('one of the following is required')
group = required.add_mutually_exclusive_group(required=True)
group.add_argument('--sensor', metavar='HOST', help='sensor hostname')
group.add_argument('--pcap', metavar='PATH', help='path to pcap file')
parser.add_argument('--meta', metavar='PATH', help='path to metadata json')
parser.add_argument('--lidar-port', type=int, default=7502)
args = parser.parse_args()
if args.sensor:
print("Initializing...")
scans = client.Scans.stream(args.sensor,
args.lidar_port,
complete=False)
elif args.pcap:
import ouster.pcap as pcap
if args.meta:
metadata_path = args.meta
else:
print("Deducing metadata based on pcap name. "
"To provide a different metadata path, use --meta")
metadata_path = os.path.splitext(args.pcap)[0] + ".json"
with open(metadata_path) as json:
info = client.SensorInfo(json.read())
scans = client.Scans(
pcap.Pcap(args.pcap, info, rate=1.0, lidar_port=args.lidar_port))
viz = PyViz(scans.metadata)
def run() -> None:
try:
for scan in scans:
viz.draw(scan)
finally:
# signal main thread to exit
viz.quit()
try:
print("Starting client thread...")
client_thread = threading.Thread(target=run, name="Client")
client_thread.start()
print("Starting rendering loop...")
viz.loop()
finally:
scans.close()
client_thread.join()
print("Done")
def meta_2_0():
meta_path = path.join(DATA_DIR, f"{TESTS['legacy-2.0']}.json")
with open(meta_path, 'r') as f:
return client.SensorInfo(f.read())
def meta(base_name: str):
meta_path = path.join(DATA_DIR, f"{base_name}.json")
with open(meta_path, 'r') as f:
return client.SensorInfo(f.read())
