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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-how-to-build-pose-detection-deep-learning-iphone-app/
课程评论：没有评论
课程名称：学习如何构建姿态检测深度学习iPhone应用 课程概述： 本课程旨在教你如何使用Posenet深度学习算法构建实时姿态检测iPhone应用。深度学习的应用在于训练机器识别视频和图像中的姿态。一旦模型训练完成，它可以在任何视频或图像中进行姿态检测。该应用不需要WiFi或移动网络连接，利用深度学习和预训练的Posenet模型，基于Apple的CoreML和Vision SDK实现全手机端的姿态检测，保障用户隐私与数据安全。在这个初学者教程中，将建立一个强大的姿态检测引擎基础。 学习内容包括： - 理解姿态检测的基本原理 - 理解深度学习和卷积神经网络（CNN）的基础知识 - Posenet在健身应用中的优势 - 基于Posenet、计算机视觉、CoreML和Swift构建实时视频姿态检测 - 基于Posenet、计算机视觉、CoreML和Swift构建实时图像姿态检测 通过本课程，你将掌握实时姿态检测的基本知识，这是一个强大且实用的技术。Swift、Posenet和CoreML都是免费且易于学习的工具，具有优秀的文档支持。本课程不要求有CNN或深度学习的先前知识，将从零开始讲解CNN。计算机视觉领域的工作机会丰富，学习实时物体检测将给你带来竞争优势。学习使用Posenet进行姿态检测将帮助你成为一名需求量大的计算机视觉开发者。 课程亮点： - 通过专业老师的指导，学习Posenet并构建实时姿态检测引擎 - 超过15节课程，逐步教你如何构建实时姿态检测引擎 - 适合中级程序员，尤其是喜欢通过示范学习的用户 - 采用视觉培训方法，增强学习效果，提升知识保留率 - 将复杂的应用程序分解成简单易懂的步骤，并提供挑战和解决方案，以巩固概念。 本课程将让你在自己的桌前学习姿态检测和深度学习，提升你的技能并为未来的职业发展打下坚实基础。
Course DescriptionLearn to build real time pose detection iPhone app using Posenet deep learning algorithm. Deep learning is popular where a machine can be trained to detect poses in video and images. Once trained, it can be used to detect poses in any video or image. The app does not require any wifi or cellular connectivity. It uses deep learning and pretrained posenet model. It leverages apple's coreml and vision SDK to achieve pose detection entirely on the phone. Since the app does not send your images or vides to remote service, it maintains your privacy and data secured. Build a strong foundation in pose detection engines with this tutorial for beginners.Understanding fundamentals of pose detectionUnderstanding fundamentals of deep learning and CNN Benefits of posenet for fitness appsBuild a real life pose detection in video using posenet, computer vision, coreml and swiftBuild a real life pose detection in image using posenet, computer vision,, coreml and swiftA Powerful Skill at Your Fingertips Learning the fundamentals of real time pose detection puts a powerful and very useful tool at your fingertips. swift, posenet and coreml are free, easy to learn, has excellent documentation.No prior knowledge of CNN or deep learning is assumed. I'll be covering topics like CNN from scratch. Jobs in computer vision area are plentiful, and being able to learn real time object detection will give you a strong edge. YOLO is state of art technology that can quickly help you achieve your goal. Learning pose detection with posenet will help you become a computer vision developer which is in high demand.Content and Overview This course teaches you on how to build real time pose detection engine using open source posenet, coreml and swift. You will work along with me step by step to build following answersReal time pose detection in VideoReal time pose detection in imageFundamentals of CNN and posenetWhat am I going to get from this course?Learn posenent and build real time pose detection engine from professional trainer from your own desk.Over 15 lectures teaching you how to build real time pose detection engineSuitable for intermediate programmers and ideal for users who learn faster when shown.Visual training method, offering users increased retention and accelerated learning.Breaks even the most complex applications down into simplistic steps.Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.
