Computer Vision Schulungen

Computer Vision Schulungen

Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media.

NobleProg onsite live Computer Vision training courses demonstrate through interactive discussion and hands-on practice the basics of Computer Vision as participants step through the creation of simple Computer Vision apps.

Computer Vision training is available in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local Computer Vision training can be carried out live on customer premises or in NobleProg local training centers.

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Computer Vision Schulungsübersicht

Code Name Dauer Übersicht
pythoncomputervision Computer Vision with Python 7 hours Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of simple Computer Vision apps using Python. By the end of this training, participants will be able to: Understand the basics of Computer Vision Use Python to implement Computer Vision tasks Build their own Computer Vision apps using Python Audience Python programmers interested in Computer Vision Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
rasberrypiopencv Raspberry Pi + OpenCV: Build a facial recognition system 21 hours This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc. By the end of this training, participants will be able to: Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi. Configure OpenCV to capture and detect facial images. Understand the various options for packaging a Rasberry Pi system for use in real-world environments. Adapt the system for a variety of use cases, including surveillance, identity verification, etc. Audience Developers Hardware/software technicians Technical persons in all industries Hobbyists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Note Other hardware and software options include: Arduino, OpenFace, Windows, etc. If you wish to use any of these, please contact us to arrange.
marvin Marvin Image Processing Framework - creating image and video processing applications with Marvin 14 hours Marvin is an extensible, cross-platform, open-source image and video processing framework developed in Java.  Developers can use Marvin to manipulate images, extract features from images for classification tasks, generate figures algorithmically, process video file datasets, and set up unit test automation. Some of Marvin's video applications include filtering, augmented reality, object tracking and motion detection. In this course participants will learn the principles of image and video analysis and utilize the Marvin Framework and its image processing algorithms to construct their own application. Audience     Software developers wishing to utilize a rich, plug-in based open-source framework to create image and video processing applications Format of the course     The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries.
patternmatching Pattern Matching 14 hours Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not. Audience     Engineers and developers seeking to develop machine vision applications     Manufacturing engineers, technicians and managers Format of the course     This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision.
opencv Computer Vision with OpenCV 28 hours OpenCV (Open Source Computer Vision Library: http://opencv.org) is an open-source BSD-licensed library that includes several hundreds of computer vision algorithms. Audience This course is directed at engineers and architects seeking to utilize OpenCV for computer vision projects
simplecv Computer Vision with SimpleCV 14 hours SimpleCV is an open source framework — meaning that it is a collection of libraries and software that you can use to develop vision applications. It lets you work with the images or video streams that come from webcams, Kinects, FireWire and IP cameras, or mobile phones. It’s helps you build software to make your various technologies not only see the world, but understand it too. Audience This course is directed at engineers and developers seeking to develop computer vision applications with SimpleCV.
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