02589nam 2200589 a 450 991100654230332120240313221033.01-62198-884-81-78216-392-1(CKB)2670000000369777(OCoLC)849939968(CaPaEBR)ebrary10695764(SSID)ssj0000908155(PQKBManifestationID)12431373(PQKBTitleCode)TC0000908155(PQKBWorkID)10898006(PQKB)11414782(MiAaPQ)EBC1192630(Au-PeEL)EBL1192630(CaPaEBR)ebr10695764(CaONFJC)MIL485750(OCoLC)842885402(PPN)188662936(EXLCZ)99267000000036977720150303d2013 uy 0engurcn|||||||||txtccrOpenCV computer vision with Python learn to capture videos, manipulate images, and track objects with Python using the OpenCV library /Joseph HowseBirmingham, England Packt Publishingc20131 online resource (122 p.) Includes index.1-78216-393-X Setting up OpenCV -- Handling files, cameras, and GUIs -- Filtering images -- Tracking faces with Haar cascades -- Detecting foreground/background regions and depth -- Integrating with Pygame -- Generating Haar cascades for custom targets.A practical, project-based tutorial for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python.OpenCV Computer Vision with Python is written for Python developers who are new to computer vision and want a practical guide to teach them the essentials. Some understanding of image data (for example, pixels and color channels) would be beneficial. At a minimum you will need access to at least one webcam. Certain exercises require additional hardware like a second webcam, a Microsoft Kinect or an OpenNI-compliant depth sensor such as the Asus Xtion PRO.Computer visionOperating systems (Computers)Python (Computer program language)Computer vision.Operating systems (Computers)Python (Computer program language)006.37Howse Joseph1149086MiAaPQMiAaPQMiAaPQBOOK9911006542303321OpenCV computer vision with Python4390170UNINA