|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/face-recognition-and-detection-in-android-the-2024-guide/
课程评论：没有评论
课程名称：安卓面部识别与检测——2025年指南 概述：欢迎加入一个激动人心的旅程，掌握在Android中使用Java和Kotlin进行面部识别和面部检测模型的技能！本课程全面教授如何将面部识别与检测功能无缝集成到Android应用中，充分利用图像和实时摄像头视频。面部识别技术在各个行业中变得至关重要，包括：安全机构用于识别和追踪罪犯，企业用于监控员工活动，教育机构用于简化考勤跟踪。本课程能帮助你掌握将多种面部识别模型集成到Android应用开发中的技能，从而创造出智能且稳健的Android应用程序。 课程亮点： 1. 理解基础知识：学习面部识别模型的基本原理，探索面部识别系统的两个主要组成部分： - 面部注册：通过图像扫描或实时摄像头捕捉在Android中注册面部，并将其与用户分配的名称存储在数据库中。 - 面部识别：深入了解如何在Android（Java/Kotlin）中识别注册面部，利用面部识别模型比较扫描的面部与注册的面部。 2. Android中的图像处理：掌握在Android中处理图像的基本技巧，包括从图库选择图像和使用摄像头捕捉图像，这些技能对于将图像传递给面部识别模型至关重要。 3. 使用图像的面部识别：构建你的第一个Android面部识别应用程序，允许用户注册和识别面部，使用FaceNet模型和Mobile FaceNet模型进行两种不同的面部识别。 4. 实时面部识别：深入学习实时面部识别的Android应用程序，使用实时摄像头视频帧进行注册和识别面部，包括在Android中显示实时摄像头视频，以及逐帧处理面部识别模型以实现实时识别和注册。 5. TensorFlow Lite集成：掌握在Android中使用TensorFlow Lite集成面部识别模型，了解为什么TensorFlow Lite是实现移动应用中机器学习模型的理想格式。 6. 面部检测：在应用面部识别之前，必须先检测图像或实时摄像头视频帧中的面部。本课程也将教你如何在Android中（Java/Kotlin）使用ML Kit库的面部检测模型进行面部检测。 课程成果：完成本课程后，你将能够： - 在Android（Java/Kotlin）中集成面部识别与检测模型，支持图像和实时摄像头视频。 - 在Android（Java/Kotlin）应用中实现基于面部识别的身份验证。 - 构建完整功能的基于面部识别的安全系统和考勤系统。 总之，本课程是掌握Android应用开发中面部识别的一本全面指南。不要错失这个机会，加入课程，解锁Android中面部识别的潜力！
Welcome to an exhilarating journey of mastering Face Recognition and Face Detection Models in Android with Java and Kotlin! This comprehensive course empowers you to seamlessly integrate facial recognition & detection into your Android apps, harnessing the power of both images and live camera footage.Face recognition has become a pivotal technology used across various industries:- Security agencies employ it for identifying and tracking criminals.- Companies utilize it to monitor employee activities.- Educational institutions leverage it for streamlined attendance tracking.In this course, you'll acquire the skills to integrate diverse face recognition models into Android App Development, enabling you to create intelligent and robust applications for AndroidCourse Highlights:Understanding the Basics:Embark on your journey by grasping the fundamental principles behind face recognition models. Explore the two core components of a face recognition system:1. **Face Registration:** - Learn to register faces through image scans or live camera footage in Android. - Capture and store faces along with user-assigned names in a database in Android.2. **Face Recognition:** - Dive into the process of recognizing registered faces in android ( Java / Kotlin ). - Utilize face recognition models to compare scanned faces with registered onesImage Handling in Android:Discover essential techniques for handling images in Android, including:- Choosing Images from Gallery in Android- Capturing Images using Camera in AndroidThese skills are crucial for passing images to face recognition models within your Android application.Face Recognition With Images in Android:Build your first face recognition application in Android, allowing users to:- Register faces- Recognize facesUtilize two distinct models for face recognition in Android:1. FaceNet Model2. Mobile FaceNet ModelReal-time Face Recognition:Advance to real-time face recognition Android applications, registering and recognizing faces using live camera footage frames. Learn to:- Display live camera footage in Android ( Java / Kotlin )- Process frames one by one with face recognition models in Android ( Java / Kotlin )- Achieve real-time recognition and registration in Android ( Java / Kotlin )TensorFlow Lite Integration:Master the integration of face recognition models in Android ( Java / Kotlin ) using TensorFlow Lite. Explore why TensorFlow Lite is the ideal format for implementing machine learning models in mobile applications.Face Detection:In face recognition applications before recognizing faces we need to detect faces from images or frames of live camera footage. So for detecting those faces, we are going to use the face detection model of the ML Kit library in Android ( Java / Kotlin ). So in this course, you will also learn to perform face detection in Android ( Java / Kotlin ) with both images & live camera footage.Course Outcomes:Upon completion of this course:- Integrate Face Recognition & Detection models in Android ( Java / Kotlin ) with both Images and live camera footage- Implement Face Recognition-based authentication in Android ( Java / Kotlin ) Applications- Construct fully functional Face Recognition-based security and attendance systems in Android ( Java / Kotlin )In essence, this course serves as a comprehensive guidebook for mastering face recognition in Android app development. Don't miss out on this opportunity to acquire a skill that truly matters. Join the course now and unlock the potential of Face Recognition in Android!
