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Facial Recognition with Android (1/4)
Summary
In this article, Andrew Kelly covers how to add facial recognition to an Android app using Google Vision (deprecated) and Firebase ML Kit. He explains how to add a camera preview surface, use a camera source to grab frames from the hardware camera, and use a detector to detect a face in a given frame. He also provides sample code and explains how to set up a Firebase project and get a google-services.json file. Finally, he discusses how to use the frame data callback to create a bitmap for facial classification.
Q&As
What is the purpose of this article?
The purpose of this article is to explain how to add facial recognition to an Android app.
How can facial recognition be added to an Android app?
Facial recognition can be added to an Android app by using Google AutoML, TensorFlow, or TensorFlow Lite.
What are the main components of the Android app used for facial recognition?
The main components of the Android app used for facial recognition are the camera preview surface, camera source, detector, and classify the face.
What is the difference between the Google Vision and Firebase ML Kit implementations?
The difference between the Google Vision and Firebase ML Kit implementations is that the Google Vision library has a CameraSource builder and the Firebase ML Kit directly interfaces with the Camera APIs on Android.
What is needed to use the Firebase ML Kit?
To use the Firebase ML Kit, a Firebase project needs to be set up and a google-services.json file needs to be downloaded and placed in the project/app folder.
AI Comments
👍 The article provides a comprehensive overview of facial recognition with Android, providing example code and helpful references.
👎 The article is quite long and technical, making it difficult to digest for those who may be unfamiliar with facial recognition technology.
AI Discussion
Me: It's about facial recognition with Android. It covers how to add facial recognition to an Android app, using both Google Vision and Firebase ML Kit libraries. It also covers how to set up a Firebase project and generate a google-services.json file in order to use ML Kit.
Friend: Wow, that's really interesting. What are the implications of this article?
Me: Well, this article shows how facial recognition technology is becoming more accessible and easier to use in Android apps. This has a lot of implications, such as improved security and privacy, as well as the potential for more personalized user experiences. There could also be ethical concerns, as facial recognition technology can be used to target and track individuals without their knowledge or consent.
Action items
- Create a Firebase project and download the google-services.json file to use with the ML Kit sample code.
- Implement the ICameraSource interface to switch between Google Vision and Firebase ML Kit.
- Experiment with the CameraSourcePreview class to render camera frames to the preview without needing to create an extra bitmap.
Technical terms
- Facial Recognition
- A technology that uses biometric data to identify a person by their face.
- Android
- An operating system developed by Google for mobile devices.
- Google Vision (deprecated)
- A library for facial recognition that is no longer supported by Google.
- Firebase ML Kit
- A library for facial recognition developed by Google.
- Camera Source
- A class that grabs frames from the hardware camera.
- Detector
- A class that detects a face in a given frame.
- GraphicOverlay
- A class that renders camera info passed to it.
- ICameraSource
- An interface that allows for the reuse of the CameraSourcePreview class between different implementations.
- AbstractActivity.kt
- A class that takes care of inflating the layout and requesting permission to use the camera.
- GoogleVisionActivity
- A class that provides methods for creating, starting and releasing the camera source.
- GraphicFaceTracker
- A class that provides different callback methods for when a face is detected, updated or gone from a frame.
- MLCameraSource
- A class that directly interfaces with the Camera 1 API and processes camera frames on a background thread.
- FaceDetector
- An implementation of the IFrameProcessor interface.
- MLKitActivity
- A class that provides the same methods as before for creating, starting and releasing the camera source.
- google-services.json
- A file that is needed to use the Firebase ML Kit.