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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-with-opencv/
课程评论：没有评论
课程名称：使用OpenCV进行构建 课程概述：本课程旨在教导学员如何让计算机具备图像识别能力，通过OpenCV这一强大工具，让学员能够落实自己的创意。课程内容结合了文本、视频、代码示例和评估，提供了一条清晰的学习路径，以模块化的方式帮助学员按照自己的节奏学习，从而逐步迈向构建有趣的计算机视觉应用的目标。 OpenCV是一个跨平台的、免费使用的库，主要用于实时计算机视觉和图像处理，是开发者专注于图像处理、运动检测和图像分割等完整项目的最佳开源库之一。该课程通过深入研究和精心策划的内容，设计得以逐步掌握利用OpenCV开发计算机视觉应用的技能。每个模块不仅可以独立作为学习资源，同时也有助于不断增加学员的技能。 课程中将通过项目和学习方案教授OpenCV，从基础的图像处理入手，逐步开展光流视频分析和复杂场景中的文本识别等内容。学员将会开发出各种项目，涵盖图像处理、运动检测和图像分割等计算机视觉的不同概念。课程结束后，学员将熟悉OpenCV的基础知识，如矩阵运算、滤波器和直方图，同时还将掌握更高级的概念，如分割、机器学习、复杂视频分析和文本识别。 讲师团队由领域内的专家组成，包括计算机视觉研究者Prateek Joshi、IT和计算机视觉经验丰富的David Millán Escrivá、计算机图形学教授Vinícius Godoy以及渥太华大学电气工程与计算机科学学院教授Robert Laganière。他们在计算机视觉、图形学及模式识别领域都有着丰富的研究和实践经验。 总之，本课程为希望在计算机视觉和图像处理领域发展技能的学员提供了一条清晰有效的学习路线，帮助他们构建出引人注目的计算机视觉应用。
Yes, computers can see too. Want to know how? This course will not just show you how but equip you with skills to implement your own ideas. Let's get started! This course is a blend of text, videos, code examples, and assessments, which together makes your learning journey all the more exciting and truly rewarding. It includes sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. This helps you learn a range of topics at your own speed and also move towards your goal of building cool computer vision applications with OpenCV. OpenCV is a cross-platform, free-to-use library that is primarily used for real-time computer vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This course has been prepared using extensive research and curation skills. Each section adds to the skills learned and helps us to achieve mastery in developing computer vision applications using OpenCV. Every section is modular and can be used as a standalone resource too. This course has been designed to teach you OpenCV through the use of projects and learning recipes, and equip you with skills to develop your own cool applications. This course will take you through the commonly used Computer Vision techniques to build your own OpenCV projects from scratch. Starting with the installation of OpenCV on your system and understanding the basics of image processing, we will swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used computer vision techniques to build your own OpenCV projects from scratch. We will develop awesome projects that will focus on the different concepts of computer vision such as image processing, motion detection, and image segmentation. By the end of this course, you will be familiar with the basics of OpenCV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition. This course has been authored by some of the best in their fields: Prateek Joshi Prateek Joshi is a Computer Vision researcher and published author. He has over eight years of experience in this field with a primary focus on content-based analysis and deep learning. His work in this field has resulted in multiple patents, tech demos, and research papers at major IEEE conferences. You can visit his blog. David Millán Escrivá David Millán Escrivá has more than 13 years of experience in IT, with more than nine years of experience in Computer Vision, computer graphics, and pattern recognition, working on different projects and start-ups, applying his knowledge of Computer Vision, optical character recognition, and augmented reality. He is the author of the DamilesBlog, where he publishes research articles and tutorials on OpenCV, Computer Vision in general, and optical character recognition algorithms. Vinícius Godoy Vinícius Godoy is a computer graphics university professor at PUCPR. He started programming with C++ 18 years ago and ventured into the field of computer gaming and computer graphics 10 years ago. He is currently working with medical imaging systems for his PhD thesis. Robert Laganière Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content-based video analysis, visual surveillance, object recognition, and 3D reconstruction. Since 2011, Robert has also been Chief Scientist at Cognivue Corp, a leader in embedded vision solutions.
