paralleldomain.model.annotation¶

camera_frame: SensorFrame = ...  # get any camera's SensorFrame

from paralleldomain.model.annotation import AnnotationTypes

boxes_2d = camera_frame.get_annotations(AnnotationTypes.BoundingBoxes2D)
for b in boxes_2d.boxes:
    print(b.class_id, b.instance_id)

Access class map for an annotation type in a scene:

scene: Scene = ...  # get a Scene instance

from paralleldomain.model.annotation import AnnotationTypes

class_map = scene.get_class_map(AnnotationTypes.SemanticSegmentation2D)
for id, class_detail in class_map.items():
    print(id, class_detail.name)

class BoundingBox2D(x, y, width, height, class_id, instance_id, attributes=<factory>)¶

Represents a 2D Bounding Box annotation including geometry.

Parameters

x – x
y – y
width – width
height – height
class_id – class_id
instance_id – instance_id
attributes – attributes

x¶

Top-Left corner in image pixels coordinates along x-axis

Type: paralleldomain.model.geometry.bounding_box_2d.T

y¶

Top-Left corner in image pixels coordinates along y-axis

Type: paralleldomain.model.geometry.bounding_box_2d.T

width¶

Width of box in pixel along x-axis

Type: paralleldomain.model.geometry.bounding_box_2d.T

height¶

Height of box in pixel along y-axis

Type: paralleldomain.model.geometry.bounding_box_2d.T

class_id¶

Class ID of annotated object. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property area¶: Returns area of 2D Bounding Box in square pixel.

property edges: numpy.ndarray¶

Returns the 2D edges of a bounding box.

Edges are returned in order of connecting the vertices in the following order:

[0, 1]
[1, 2]
[2, 3]
[3, 0]

0--------1
|        |
|        | right
|        |
3--------2
  bottom

Return type: ndarray

include_point(point, inline=False)¶

Extends the dimensions of the box to include the specified point.

Parameters

point (paralleldomain.model.geometry.point_2d.Point2DBaseGeometry[paralleldomain.model.geometry.bounding_box_2d.T]) – Instance of Point2DGeometry which needs to be included in updated bounding box.
inline (bool) – When set, do not return a copy of the object but update the current object. Default: False.

Returns

A copy of the current object with extended dimensions, if inline is set. Otherwise, returns None.

Return type

Optional[BoundingBox2DBaseGeometry[TypeVar(T, int, float)]]

include_points(points, inline=False)¶

Extends the dimensions of the box to include the specified point.

Parameters

points (List[paralleldomain.model.geometry.point_2d.Point2DBaseGeometry[paralleldomain.model.geometry.bounding_box_2d.T]]) – List of Point2DGeometry which need to be included in updated bounding box.
inline (bool) – When set, do not return a copy of the object but update the current object. Default: False.

Returns

A copy of the current object with extended dimensions, if inline is set. Otherwise, returns None.

Return type

Optional[BoundingBox2DBaseGeometry[TypeVar(T, int, float)]]

classmethod merge_boxes(target_box, source_box)¶

Takes two 2D box geometries as input and merges both into a new box geometry. The resulting box geometry has dimensions from target_box and source_box merged into it.

Return type

BoundingBox2DBaseGeometry[TypeVar(T, int, float)]

Parameters

target_box (paralleldomain.model.geometry.bounding_box_2d.BoundingBox2DBaseGeometry) –
source_box (paralleldomain.model.geometry.bounding_box_2d.BoundingBox2DBaseGeometry) –

property vertices: numpy.ndarray¶

Returns the 2D vertices of a bounding box.

Vertices are returned in the following order:

0--------1
|        |
|        | right
|        |
3--------2
  bottom

Return type: ndarray

class BoundingBoxes2D(boxes)¶

Collection of 2D Bounding Boxes.

Parameters: boxes (List[paralleldomain.model.annotation.bounding_box_2d.BoundingBox2D]) – boxes
Return type: None

boxes¶

Unordered list of BoundingBox2D instances

Type: List[paralleldomain.model.annotation.bounding_box_2d.BoundingBox2D]

get_box_by_instance_id(instance_id)¶

Returns the box with matching instance ID.

Parameters: instance_id (int) – Instance ID of box that should be returned.
Returns: Matching box instance. If none found, returns None.
Return type: Optional[BoundingBox2D]

get_boxes_by_attribute_key(attr_key)¶

Returns all boxes having a certain attribute, independent of value.

Parameters: attr_key (str) – Name of attribute.
Returns: List of box instances that have the specified attribute.
Return type: List[BoundingBox2D]

get_boxes_by_attribute_value(attr_key, attr_value)¶

Returns all boxes having the specified attribute and value.

Parameters

attr_key (str) – Name of attribute.
attr_value (Any) – Value of attribute.

Returns

List of box instances that have the specified attribute and value.

Return type

List[BoundingBox2D]

get_boxes_by_attribute_values(attr_key, attr_values)¶

Returns all boxes having the specified attribute and any of the values.

Parameters

attr_key (str) – Name of attribute.
attr_values (List[Any]) – Allowed values of attribute.

Returns

List of box instances that have the specified attribute and any of the values.

Return type

List[BoundingBox2D]

get_boxes_by_class_id(class_id)¶

Returns all boxes having a the specified class ID.

Parameters: class_id (int) – Class ID.
Returns: List of box instances that are of the specified class.
Return type: List[BoundingBox2D]

get_boxes_by_class_ids(class_ids)¶

Returns all boxes having any of the specified class IDs.

Parameters: class_ids (List[int]) – Class IDs.
Returns: List of box instances that are of any of the specified classes.
Return type: List[BoundingBox2D]

static merge_boxes(target_box, source_box)¶

Takes two 2D boxes as input and merges both into a new box. The resulting box has the exact same properties as target_box, but with extended source_box dimensions merged into it.

Return type

BoundingBox2D

Parameters

target_box (paralleldomain.model.annotation.bounding_box_2d.BoundingBox2D) –
source_box (paralleldomain.model.annotation.bounding_box_2d.BoundingBox2D) –

class BoundingBox3D(pose, width, height, length, class_id, instance_id, num_points, attributes=<factory>)¶

Represents a 3D Bounding Box geometry.

Parameters

pose – pose
length – length
width – width
height – height
class_id – class_id
instance_id – instance_id
num_points – num_points
attributes – attributes

pose¶

6D Pose for box in 3D sensor space.

Type: paralleldomain.utilities.transformation.Transformation

length¶

Length of box in meter along x-axis.

Type: paralleldomain.model.geometry.bounding_box_3d.T

width¶

Width of box in meter along y-axis.

Type: paralleldomain.model.geometry.bounding_box_3d.T

height¶

Height of box in meter along z-axis.

Type: paralleldomain.model.geometry.bounding_box_3d.T

class_id¶

Class ID of annotated object. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D.

Type: int

num_points¶

Number of LiDAR points of related Sensor.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property edges: numpy.ndarray¶

Returns the 3D edges of a bounding box.

Edges are returned in order of connecting the vertices in the following order:

[0, 1]
[1, 2]
[2, 3]
[3, 0]
[4, 5]
[5, 6]
[6, 7]
[7, 4]
[2, 6]
[7, 3]
[1, 5]
[4, 0]

   5--------6
  /|   top /|
 / |      / |
1--------2  |
|  4-----|--7
| /      | /
|/       |/ left
0--------3
  front

Return type: ndarray

property faces: numpy.ndarray¶

Returns the 3D faces of a bounding box.

Faces are returned in order of connecting the vertices in the following order:

[0, 1, 2, 3] (front)
[4, 5, 6, 7] (back)
[3, 2, 6, 7] (left)
[0, 1, 5, 4] (right)
[6, 2, 1, 5] (top)
[7, 3, 0, 4] (bottom)

   5--------6
  /|   top /|
 / |      / |
1--------2  |
|  4-----|--7
| /      | /
|/       |/ left
0--------3
  front

Return type: ndarray

classmethod merge_boxes(target_box, source_box)¶

Takes two 3D box geometries as input and merges both into a new box geometry. The resulting box geometry has dimensions from target_box and source_box merged into it.

Return type

BoundingBox3DBaseGeometry[TypeVar(T, int, float)]

Parameters

target_box (paralleldomain.model.geometry.bounding_box_3d.BoundingBox3DBaseGeometry) –
source_box (paralleldomain.model.geometry.bounding_box_3d.BoundingBox3DBaseGeometry) –

property vertices: numpy.ndarray¶

Returns the 3D vertices of a bounding box.

Vertices are returned in the following order:

   5--------6
  /|   top /|
 / |      / |
1--------2  |
|  4-----|--7
| /      | /
|/       |/ left
0--------3
  front

Return type: ndarray

property volume: paralleldomain.model.geometry.bounding_box_3d.T¶

Returns volume of 3D Bounding Box in cubic meter.

Return type: TypeVar(T, int, float)

class BoundingBoxes3D(boxes)¶

Collection of 3D Bounding Boxes

Parameters: boxes (List[paralleldomain.model.annotation.bounding_box_3d.BoundingBox3D]) – boxes
Return type: None

boxes¶

Unordered list of BoundingBox3D instances

Type: List[paralleldomain.model.annotation.bounding_box_3d.BoundingBox3D]

get_box_by_instance_id(instance_id)¶

Returns the box with matching instance ID.

Parameters: instance_id (int) – Instance ID of box that should be returned.
Returns: Matching box instance. If none found, returns None.
Return type: Optional[BoundingBox3D]

get_boxes_by_attribute_key(attr_key)¶

Returns all boxes having a certain attribute, independent of value.

Parameters: attr_key (str) – Name of attribute.
Returns: List of box instances that have the specified attribute.
Return type: List[BoundingBox3D]

get_boxes_by_attribute_value(attr_key, attr_value)¶

Returns all boxes having the specified attribute and value.

Parameters

attr_key (str) – Name of attribute.
attr_value (Any) – Value of attribute.

Returns

List of box instances that have the specified attribute and value.

Return type

List[BoundingBox3D]

get_boxes_by_attribute_values(attr_key, attr_values)¶

Returns all boxes having the specified attribute and any of the values.

Parameters

attr_key (str) – Name of attribute.
attr_values (List[Any]) – Allowed values of attribute.

Returns

List of box instances that have the specified attribute and any of the values.

Return type

List[BoundingBox3D]

get_boxes_by_class_id(class_id)¶

Returns all boxes having a the specified class ID.

Parameters: class_id (int) – Class ID.
Returns: List of box instances that are of the specified class.
Return type: List[BoundingBox3D]

get_boxes_by_class_ids(class_ids)¶

Returns all boxes having any of the specified class IDs.

Parameters: class_ids (List[int]) – Class IDs.
Returns: List of box instances that are of any of the specified classes.
Return type: List[BoundingBox3D]

static merge_boxes(target_box, source_box)¶

Takes two 3D boxes as input and merges both into a new box. The resulting box has the exact same properties as target_box, but with extended source_box dimensions merged into it.

Return type

BoundingBox3D

Parameters

target_box (paralleldomain.model.annotation.bounding_box_3d.BoundingBox3D) –
source_box (paralleldomain.model.annotation.bounding_box_3d.BoundingBox3D) –

class Depth(depth)¶

Represents a Depth mask for a camera image.

Parameters: depth (numpy.ndarray) – depth
Return type: None

depth¶

Matrix of shape (H X W x 1), , where H is the height and W is the width of corresponding camera image. The third axis contains the depth distance for each pixel as int in meter.

Type: numpy.ndarray

class InstanceSegmentation2D(instance_ids)¶

Represents a 2D Instance Segmentation mask for a camera image.

Parameters: instance_ids (numpy.ndarray) – instance_ids
Return type: None

instance_ids¶

Matrix of shape (H x W x 1), where H is the height and W is the width of corresponding camera image. The third axis contains the instance ID for each pixel as int.

Type: numpy.ndarray

get_instance(instance_id)¶

Returns a bool mask where instance is present.

Parameters: instance_id (int) – ID of instance to be masked
Returns: Mask of same shape as class_ids and bool values. True where pixel matches instance, False where it doesn’t.
Return type: ndarray

get_instances(instance_ids)¶

Returns a bool mask where instances are present.

Parameters: instance_ids (List[int]) – IDs of instances to be masked
Returns: Mask of same shape as class_ids and bool values. True where pixel matches one of the instances, False where it doesn’t.
Return type: ndarray

property rgb_encoded: numpy.ndarray¶

Outputs instance_ids mask as RGB matrix with shape (H x W x 3), with R being the lowest and B being the highest 8 bit.

Return type: ndarray

class InstanceSegmentation3D(instance_ids)¶

Represents a 3D Instance Segmentation mask for a point cloud.

Parameters: instance_ids (numpy.ndarray) – instance_ids
Return type: None

instance_ids¶

2D Matrix of size (N x 1), where N is the length of the corresponding point cloud. The second axis contains the instance ID for each point as int.

Type: numpy.ndarray

class OpticalFlow(vectors)¶

Represents an Optical Flow mask for a camera image.

Parameters: vectors (numpy.ndarray) – vectors
Return type: None

vectors¶

Matrix of shape (H X W x 2), , where H is the height and W is the width of corresponding camera image. The third axis contains the x and y offset to the pixels coordinate on the next image.

Type: numpy.ndarray

Example

Using the Optical Flow vector mask in combination with Image.coordinates allows for a fast retrieval of absolute pixel coordinates.

camera_frame: SensorFrame = ...  # get any camera's SensorFrame

flow = camera_frame.get_annotations(AnnotationTypes.OpticalFlow)
rgb = camera_frame.image.rgb
next_image = np.zeros_like(rgb)
coordinates = camera_frame.image.coordinates
next_frame_coords = coordinates + np.round(flow.vectors).astype(int)[...,[1,0]]

for y in range(rgb.shape[0]):
    for x in range(rgb.shape[1]):
        next_coord = next_frame_coords[y, x]
        if 0 <= next_coord[0] < rgb.shape[0] and 0 <= next_coord[1] < rgb.shape[1]:
            next_image[next_coord[0], next_coord[1], :] = rgb[y, x, :]

import cv2
cv2.imshow("window_name", cv2.cvtColor(
        src=next_image,
        code=cv2.COLOR_RGBA2BGRA,
))
cv2.waitKey()

class Point2D(x, y, class_id, instance_id=-1, attributes=<factory>)¶

Represents a 2D Point.

Parameters

x – x
y – y
class_id – class_id
instance_id – instance_id
attributes – attributes

x¶

coordinate along x-axis in image pixels

Type: paralleldomain.model.geometry.point_2d.T

y¶

coordinate along y-axis in image pixels

Type: paralleldomain.model.geometry.point_2d.T

class_id¶

Class ID of the point. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

to_numpy()¶: Returns the coordinates as a numpy array with shape (1 x 2).

class Points2D(points)¶

Collection of 2D Points

Parameters: points (List[paralleldomain.model.annotation.point_2d.Point2D]) – points
Return type: None

points¶

Unordered list of Point2D instances

Type: List[paralleldomain.model.annotation.point_2d.Point2D]

class Point3D(x, y, z, class_id, instance_id=-1, attributes=<factory>)¶

Represents a 3D Point.

Parameters

x – x
y – y
class_id – class_id
instance_id – instance_id
attributes – attributes

x¶

coordinate along x-axis in image pixels

Type: paralleldomain.model.geometry.point_3d.T

y¶

coordinate along y-axis in image pixels

Type: paralleldomain.model.geometry.point_3d.T

class_id¶

Class ID of the point. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation3D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

to_numpy()¶: Returns the coordinates as a numpy array with shape (1 x 3).

class Points3D(points)¶

Collection of 3D Points

Parameters: points (List[paralleldomain.model.annotation.point_3d.Point3D]) – points
Return type: None

points¶

Unordered list of Point3D instances

Type: List[paralleldomain.model.annotation.point_3d.Point3D]

class PointCachePointsDecoderProtocol(*args, **kwargs)¶

class PointCache(instance_id, components)¶

Represents a 3D Bounding Box geometry.

Parameters

instance_id (int) – instance_id
components (List[paralleldomain.model.annotation.point_cache.PointCacheComponent]) – components

Return type

None

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., BoundingBox3D or InstanceSegmentation3D.

Type: int

components¶

The point cache component containing the point cloud.

Type: List[paralleldomain.model.annotation.point_cache.PointCacheComponent]

class PointCaches(caches)¶

Represents a 3D Bounding Box geometry.

Parameters

instance_id – instance_id
components – components
caches (List[paralleldomain.model.annotation.point_cache.PointCache]) –

Return type

None

instance_id¶: Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., BoundingBox3D or InstanceSegmentation3D.

components¶: The point cache component containing the point cloud.

class Polygon2D(lines, class_id, instance_id=-1, attributes=<factory>)¶

A closed polygon made a collection of 2D Lines.

Parameters

lines – lines
class_id – class_id
instance_id – instance_id
attributes – attributes

lines¶

Ordered list of Line2D instances

Type: List[paralleldomain.model.geometry.polyline_2d.Line2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]]

class_id¶

Class ID of the polygon. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property length¶: Returns the length of the line.

to_numpy()¶: Returns all ordered vertices as a numpy array of shape (N x 2).

class Polygons2D(polygons)¶

Collection of 2D Polygons

Parameters: polygons (List[paralleldomain.model.annotation.polygon_2d.Polygon2D]) – polygons
Return type: None

polygons¶

Ordered list of Polygon2D instances

Type: List[paralleldomain.model.annotation.polygon_2d.Polygon2D]

class Polygon3D(lines, class_id, instance_id=-1, attributes=<factory>)¶

A closed polygon made a collection of 3D Lines.

Parameters

lines – lines
class_id – class_id
instance_id – instance_id
attributes – attributes

lines¶

Ordered list of Line3D instances

Type: List[paralleldomain.model.geometry.polyline_3d.Line3DBaseGeometry[paralleldomain.model.geometry.polyline_3d.T]]

class_id¶

Class ID of the polygon. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation3D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property length¶: Returns the length of the line.

to_numpy()¶: Returns all ordered vertices as a numpy array of shape (N x 3).

class Polygons3D(polygons)¶

Collection of 3D Polygons

Parameters: polygons (List[paralleldomain.model.annotation.polygon_3d.Polygon3D]) – polygons
Return type: None

polygons¶

Ordered list of Polygon3D instances

Type: List[paralleldomain.model.annotation.polygon_3d.Polygon3D]

class Line2D(start, end, class_id, directed=False, instance_id=-1, attributes=<factory>)¶

Represents a 2D Line.

Parameters

start – start
end – end
class_id – class_id
instance_id – instance_id
attributes – attributes

start¶

the 2D start point of the line in image coordinates

Type: paralleldomain.model.geometry.point_2d.Point2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]

end¶

the 2D end point of the line in image coordinates

Type: paralleldomain.model.geometry.point_2d.Point2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]

directed¶

whether the line is directed from start to end (if False the line is bi-directional)

Type: bool

class_id¶

Class ID of the line. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property direction: paralleldomain.model.geometry.point_2d.Point2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]¶

Returns the directional vector of the line.

Return type: Point2DBaseGeometry[TypeVar(T, int, float)]

intersects_at(other)¶

Returns the point at which the two lines intersect and a bool value that indicated if the intersection point is within the line segments. Returns None if the lines are parallel. See: https://stackoverflow.com/questions/563198/how-do-you-detect-where-two-line-segments-intersect

Return type: Tuple[Optional[Point2DBaseGeometry[TypeVar(T, int, float)]], bool, bool]
Parameters: other (paralleldomain.model.geometry.polyline_2d.Line2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]) –

property length: float¶

Returns the length of the line.

Return type: float

property slope: float¶

Returns the slope of the line. Returns np.inf for vertical lines.

Return type: float

to_numpy()¶: Returns the start and end coordinates as a numpy array with shape (2 x 2).

class Polyline2D(lines, class_id, instance_id=-1, attributes=<factory>)¶

A polyline made of a collection of 2D Lines

Parameters

lines – lines
class_id – class_id
instance_id – instance_id
attributes – attributes

lines¶

Ordered list of Line2D instances

Type: List[paralleldomain.model.geometry.polyline_2d.Line2DBaseGeometry[paralleldomain.model.geometry.polyline_2d.T]]

class_id¶

Class ID of the polyline. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation2D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property length¶: Returns the length of the line.

to_numpy()¶: Returns all ordered vertices as a numpy array of shape (N x 2).

class Polylines2D(polylines)¶

Collection of 2D Polylines

Parameters: polylines (List[paralleldomain.model.annotation.polyline_2d.Polyline2D]) – polylines
Return type: None

polylines¶

Ordered list of Polyline2D instances

Type: List[paralleldomain.model.annotation.polyline_2d.Polyline2D]

class Line3D(start, end, class_id, directed=False, instance_id=-1, attributes=<factory>)¶

Represents a 3D Line.

Parameters

start – start
end – end
class_id – class_id
instance_id – instance_id
attributes – attributes

start¶

the 3D start point of the line in image coordinates

Type: paralleldomain.model.geometry.point_3d.Point3DBaseGeometry[paralleldomain.model.geometry.polyline_3d.T]

end¶

the 3D end point of the line in image coordinates

Type: paralleldomain.model.geometry.point_3d.Point3DBaseGeometry[paralleldomain.model.geometry.polyline_3d.T]

directed¶

whether the line is directed from start to end (if False the line is bi-directional)

Type: bool

class_id¶

Class ID of the line. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation3D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property direction: paralleldomain.model.geometry.point_3d.Point3DBaseGeometry[paralleldomain.model.geometry.polyline_3d.T]¶

Returns the directional vector of the line.

Return type: Point3DBaseGeometry[TypeVar(T, int, float)]

property length: float¶

Returns the length of the line.

Return type: float

to_numpy()¶: Returns the start and end coordinates as a numpy array with shape (2 x 3).

class Polyline3D(lines, class_id, instance_id=-1, attributes=<factory>)¶

A polyline made of a collection of 3D Lines

Parameters

lines – lines
class_id – class_id
instance_id – instance_id
attributes – attributes

lines¶

Ordered list of Line3D instances

Type: List[paralleldomain.model.geometry.polyline_3d.Line3DBaseGeometry[paralleldomain.model.geometry.polyline_3d.T]]

class_id¶

Class ID of the polyline. Can be used to lookup more details in ClassMap.

Type: int

instance_id¶

Instance ID of annotated object. Can be used to cross-reference with other instance annotation types, e.g., InstanceSegmentation3D or InstanceSegmentation3D. If unknown defaults to -1.

Type: int

attributes¶

Dictionary of arbitrary object attributes.

Type: Dict[str, Any]

property length¶: Returns the length of the line.

to_numpy()¶: Returns all ordered vertices as a numpy array of shape (N x 3).

class Polylines3D(polylines)¶

Collection of 3D Polylines

Parameters: polylines (List[paralleldomain.model.annotation.polyline_3d.Polyline3D]) – polylines
Return type: None

polylines¶

Ordered list of Polyline3D instances

Type: List[paralleldomain.model.annotation.polyline_3d.Polyline3D]

class SceneFlow(vectors)¶

Represents an Scene Flow mask for a point cloud.

Parameters: vectors (numpy.ndarray) – vectors
Return type: None

vectors¶

Matrix of shape (N x 3), , where N is the number of points of the corresponding point cloud. The second axis contains the x, y and z offset to the position the sampled point will be at in the next frame. Note: This exact position might not be sampled by a Lidar in the next frame!

Type: numpy.ndarray

Example

Using the Scene Flow vector mask in combination with PointCloud.xyz to get a view of the next frame.

lidar_frame: LidarSensorFrame = ...  # get any lidars's SensorFrame

flow = lidar_frame.get_annotations(AnnotationTypes.SceneFlow)
xyz = lidar_frame.point_cloud.xyz
next_frame_xyz = xyz + flow.vectors

import open3d as o3d
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(next_frame_xyz)
o3d.visualization.draw_geometries([pcd])

class SemanticSegmentation2D(class_ids)¶

Represents a 2D Semantic Segmentation mask for a camera image.

Parameters: class_ids (numpy.ndarray) – class_ids
Return type: None

class_ids¶

Matrix of shape (H x W x 1), where H is height and W is width of corresponding camera image. The third axis contains the class ID for each pixel as int.

Type: numpy.ndarray

get_class_mask(class_id)¶

Returns a bool mask where class is present.

Parameters: class_id (int) – ID of class to be masked
Returns: Mask of same shape as class_ids and bool values. True where pixel matches class, False where it doesn’t.
Return type: ndarray

get_classes_mask(class_ids)¶

Returns a bool mask where classes are present.

Parameters: class_ids (List[int]) – IDs of classes to be masked
Returns: Mask of same shape as class_ids and bool values. True where pixel matches one of the classes, False where it doesn’t.
Return type: ndarray

property rgb_encoded: numpy.ndarray¶

Outputs class_ids mask as RGB-encoded image matrix with shape (H x W x 3), with R (index: 0) being the lowest and B (index: 2) being the highest 8 bit.

Return type: ndarray

class SemanticSegmentation3D(class_ids)¶

Represents a 3D Semantic Segmentation mask for a point cloud.

Parameters: class_ids (numpy.ndarray) – class_ids
Return type: None

class_ids¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the class ID for each point as int.

Type: numpy.ndarray

class SurfaceNormals2D(normals)¶

Represents a mask of surface normals for a camera image.

Parameters: normals (numpy.ndarray) – vectors
Return type: None

normals¶

Matrix of shape (H X W x 3), , where H is the height and W is the width of corresponding camera image. The third axis contains the x, y and z normal direction of the surface sampled by the pixel in the camera coordinate system.

Type: numpy.ndarray

class SurfaceNormals3D(normals)¶

Represents a mask of surface normals for a point cloud.

Parameters: normals (numpy.ndarray) – vectors
Return type: None

normals¶

Matrix of shape (N x 3), , where N is the number of points of the corresponding point cloud. The second axis contains the x, y and z normal direction of the surface the corresponding point was sampled from.

Type: numpy.ndarray

Example

Using the Surface Normal mask in combination with PointCloud.xyz to visualize the normals of each point.

lidar_frame: LidarSensorFrame = ...  # get any lidars's SensorFrame

sur_normals = lidar_frame.get_annotations(AnnotationTypes.SurfaceNormals3D)
xyz = lidar_frame.point_cloud.xyz
normal_points = xyz + sur_normals.normals
normal_line_points = np.concatenate([xyz, normal_points], axis=-1).reshape((2 * len(xyz), 3))
line_connections = np.arange(2 * len(xyz)).reshape((-1, 2))

import open3d as o3d
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(xyz)

colors = [[1, 0, 0] for i in range(len(line_connections))]
line_set = o3d.geometry.LineSet(
    points=o3d.utility.Vector3dVector(normal_line_points),
    lines=o3d.utility.Vector2iVector(line_connections),
)
line_set.colors = o3d.utility.Vector3dVector(colors)

o3d.visualization.draw_geometries([pcd, line_set])

class MaterialProperties2D¶

Not Implemented yet!

Return type: None

class MaterialProperties3D(material_ids, roughness=None, metallic=None, specular=None, emissive=None, opacity=None, flags=None)¶

Represents a 3D Material Segmentation mask for a point cloud.

Parameters

material_ids (numpy.ndarray) – material_ids
roughness (Optional[numpy.ndarray]) – roughness
metallic (Optional[numpy.ndarray]) – metallic
specular (Optional[numpy.ndarray]) – specular
emissive (Optional[numpy.ndarray]) – emissive
opacity (Optional[numpy.ndarray]) – opacity
flags (Optional[numpy.ndarray]) – flags

Return type

None

material_ids¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the material ID for each point as int.

Type: numpy.ndarray

roughness¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the material’s roughness value for each point as float.

Type: Optional[numpy.ndarray]

specular¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the material’s specular value for each point as float.

Type: Optional[numpy.ndarray]

emissive¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the material’s emissive value for each point as float.

Type: Optional[numpy.ndarray]

opacity¶

Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains the material’s opacity value for each point as float.

Type: Optional[numpy.ndarray]

flag¶: Matrix of shape (N x 1), where N is the length of the corresponding point cloud. The second axis contains special flags for each point encoded as float.