⚡️ ML Kit plugins for Capacitor. Supports Android and iOS.

This is a sample app built to demonstrate the use of MLKit Face detection. Dedicated to all Android Developers with heart.

A demo app for various Firebase ML-Kit vision functionalities 🕵️‍♀️

This repository contains a collection of Android applications developed using Google ML Kit, demonstrating the power and versatility of machine learning features in mobile development. Each project is crafted using Java and Kotlin, showcasing various use cases and practical implementations.

I built this app using Mlkit along with the TensorFlow Lite model for object detection, Arcore is used to place anchors to the detected objects. It's a good blend of Machine learning and Augmented reality to visualise ML information in a much better way than regular bounding boxes

Face Recognition (Identification) for Android Devices. Used Firebase ML Kit Face Detection for detecting faces, then applied arcface MobileNetV2 model for recognition

Arcore ml kit integration without sceneform to detected multiple objects in a signle frame and place 3d labels on them

React Native library to simplify the integration of AI and ML features into your mobile app.

An Android application performing recognition of facial emotions on an image

SmartLens uses Google's ML Kit for Barcode scanning, Face recognition, Text recognition, and Image labeling.

An attendance app that can be used to take attendance based on facial recognition and geolocation based authentications.

Android application which detects human faces and classifies them under wearing a face mask or not

ML Kit Face Detection in Flutter Example

A demo app using MVI, master-detail, SQLDelight, Hilt, Material Design, Navigation Component, Shared Element Transition, Coil, and MLKit face detection.

An Android app that scans images or human faces in real time and detects whether the mask is worn or not, with the ability to set an audible alert

CameraX + ML Kit = ❤️

O app consegue detectar rostos humanos e capturar informações sobre o rosto.

This React Native app is designed for marking attendance, utilizing both geolocation and face recognition technology. The app uses the device's GPS to verify the user's location and then employs facial recognition software to verify the user's identity.

stripped only Face Detection part out of vision quick start sample of Firebase ML Kit

An Expo module that uses device's front camera and MLKit to detect faces