pysdic.Camera.visualize_projected_point_cloud#

Camera.visualize_projected_point_cloud(point_cloud, points_color='black', points_size=5, points_opacity=1.0, image=None, clip_sensor=True, show_pixel_grid=False, title=None)[source]#

Visualize the projected 2D points of a PointCloud on a 2D plot using matplotlib.

See also

project_points() to project 3D points to 2D image points.
visualize_projected_mesh() to visualize projected 3D meshes.
pysdic.PointCloud for the structure of the input.
Package matplotlib for visualization.

Parameters:

point_cloud (PointCloud) – An instance of PointCloud containing the 3D points in the world coordinate system to be projected and visualized.
points_color (str, optional) – The color of the projected points in the plot. Default is "black".
points_size (int, optional) – The size of the projected points in the plot. Default is 5.
points_opacity (float, optional) – The opacity of the projected points in the plot. Default is 1.0 (fully opaque).
image (Optional[Union[numpy.ndarray, Image]], optional) – An optional background image to display behind the projected points. If provided, the image should have dimensions matching the camera sensor size. Default is None.
clip_sensor (bool, optional) – If True, only the points that are projected within the camera sensor dimensions are visualized. Default is True.
show_pixel_grid (bool, optional) – If True, a grid representing the pixel layout of the camera sensor is displayed in the background. Default is False.
title (Optional[str], optional) – An optional title for the plot. Default is None with eefault title ‘Projected Points on Image Plane’.

Return type:

None

Examples

Visualize a projected point cloud using a simple camera:

import numpy
from pysdic import Camera
from pycvcam import Cv2Extrinsic, Cv2Intrinsic
from pysdic import PointCloud

rotation_vector = numpy.array([0.1, 0.2, 0.3])
translation_vector = numpy.array([12.0, 34.0, 56.0])

extrinsic = Cv2Extrinsic.from_rt(rotation_vector, translation_vector)

intrinsic = Cv2Intrinsic.from_matrix(
    numpy.array([[1000, 0, 320],
                [0, 1000, 240],
                [0, 0, 1]])
)

camera = Camera(
    sensor_height=480,
    sensor_width=640,
    intrinsic=intrinsic,
    extrinsic=extrinsic,
)

# Define some 3D world points in a PointCloud instance
world_points_array = numpy.array([
    [0, 0, 1000],
    [100, 0, 1000],
    [0, 100, 1000],
    [100, 100, 1000]
])
world_points = PointCloud(points=world_points_array)

# Visualize the projected point cloud
camera.visualize_projected_point_cloud(point_cloud=world_points, points_color="red", points_size=10, show_pixel_grid=True)

Visualize Projected Point Cloud Example — Example of projected point cloud visualization. This figure shows the 2D projection of the 3D points onto the image plane.#

pysdic.Camera.visualize_projected_point_cloud#

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