Signalizer is a all-in-one signal visualizing package with a bunch of unique focus-points real-time audio visualization with optimized 3D GPU graphics,Įverything being scalable and zoomable gridlessly as well as being arbitrarily precise in both settings and display.Ĭombined with a rich feature set, Signalizer is suited both for electrical/audio engineers fullscreen-inspecting signals, or for general small windows giving an
Samples Several code samples show how to use the most common APIs provided by the library. Cross Platform Support Cross platform support and unified API for threads, mutexes, wait events, message queues, timers, filesystem operations and logging.
The detector also supports negative markers where the white and black areas have been inverted. Configure the detector by passing multiple marker prototypes and whether all ids or exact marker id matches should be detected. Marker Detector Sequentially detect and track all markers in an image. New marker types can be defined by implementing a simple interface. The encoded content can be an integer or a string consisting of the most common characters encoded with 6 bits.
Marker Definition Encode and decode native ALVAR fiducial markers that consist of a margin and a variable resolution Hamming encoded content block. Blob Detection Sequentially detect and iterate over blobs in a binary image. The optimization is performed by specifying corresponding 2D image points and 3D world points along with weights for each point. Pose Optimization Optimize a perspective camera pose by minimizing 3D point reprojection errors. The projection is done in normalized coordinates and support for normalizing and un-normalizing points is provided. Project and back-project points using the perspective camera model and a given pose. Pose and Perspective Projection Store poses consisting of a 3D position and orientation in right-hand coordinates and easily convert to and from common rendering conventions. Calibrate the intrinsic and distortion parameters of a camera from images of a calibration target. Model the distortion parameter of a camera using the division lens model and undistort and distort image points. Camera and Lens Model the intrinsic parameters of a camera using the standard pinhole camera model and convert to and from a projection matrix. Image memory can be fully managed or wrap existing memory locations. Features ¶ Image Handling Access and work with single- and multi-channel image data.
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