Published 7/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 59m | Size: 597 MB
Build secure Android apps with real-time liveness & spoof detection using TensorFlow Lite — no paid APIs, fully offline
What you’ll learn
Build a real-time liveness detection (anti-spoofing) system inside an Android app
Perform offline liveness detection without using any paid APIs or SDKs
Integrate and run a TensorFlow Lite model for detecting real vs. fake faces
Detect spoof attempts like photos, videos, or masks using a free custom-trained model
Display live camera feed and recognize faces in real-time
Add liveness detection to an existing face recognition Android app
Understand how TensorFlow Lite models work in Android apps
Load and use TFLite models efficiently for on-device ML inference
Secure face-based apps like attendance, login, or verification systems
Requirements
Some Basic knowledge of Android App Development with Java or Kotlin
A computer with Android Studio or Visual Studio installed (Windows/macOS/Linux)
No prior machine learning experience required – everything is explained
Description
In this hands-on course, you’ll learn how to build a real-time liveness detection system (also called spoof detection) directly inside an Android app — without using any paid APIs or cloud services.Liveness detection helps confirm that the face in front of the camera is a real, live person — not just a photo, video, or mask. It’s a powerful feature used in banking apps, secure logins, KYC systems, and more.What Makes This Course Special?You’ll start by importing a complete real-time face recognition Android app (code provided in the course).New students: Everything is explained from scratch, including how the app works.Returning students: If you’ve taken my face recognition course, you can skip directly to the liveness detection section to enhance your existing app.Then, you’ll learn to integrate a custom-trained TensorFlow Lite model that performs real-time spoof detection — and yes, the model is included in the course for free!What You’ll Learn:What liveness detection is and why it’s importantReal-world threats like photo, video, and mask spoofingHow to run a free TFLite spoof detection model on live camera feedHow to add liveness detection to an existing face recognition appHow to build fully offline, secure Android AI featuresHow to test and evaluate spoof detection in real timeWho Should Take This Course?Android developers building camera-based or security appsDevelopers who’ve built face recognition apps and want to upgrade themBeginners — no prior ML experience neededAnyone interested in mobile AI security featuresWhy You’ll Love It:Includes complete real-time face recognition Android appFree pre-trained TensorFlow Lite model for spoof detectionWorks fully offline — no APIs, no cloud costsBeginner-friendly and step-by-stepBuilds a practical, in-demand mobile security featureBy the end, you’ll have a fully working Android liveness detection system, integrated inside a real-time face recognition app, helping you secure your apps against spoofing — all without paying a cent for external services.
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