Records camera animation to a sequence of images.
arange ( 5 ), repeat = True, interp = 'linear' ) record ( folder, poses, ts=, tlim=, interp='cubic_natural', shutter_speed=inf, fps=24, prefix='frame_', ext='png' ) ¶ The viewer then proceeds to perform a more time consuming detailed rendering of the points. Once there are no more changes to the viewpoint, Thus greatly reducing the number of points being rendered. The octree is used to approximate groups of far away points as single points and cull points that are outside the view frustum, The viewer supports interactive visualization of tens of millions of points via an octree-based level-of-detail renderer.Īt startup the viewer organizes the input points into an octree. the viewer process’s port number)Īnd provides methods for querying and manipulating the viewer. The handle encapsulates the details of communicating with the viewer (e.g. The user can query and manipulate the viewer via the handle that is returned by pptk.viewer(). The viewer itself runs as a standalone operating system process separate from Python. It interprets the columns of such input as the x, y, and z coordinates of a point cloud. It accepts as input any Python variable that can be cast as a 3-column numpy array (i.e. The pptk.viewer() function enables one to directly visualize large point clouds in Python.
