Use on-device machine learning in your apps to easily solve real-world problems.
ML Kit is a mobile SDK that brings Google's on-device machine learning expertise to Android and iOS apps. Use our powerful yet easy to use Vision and Natural Language APIs to solve common challenges in your apps or create brand-new user experiences. All are powered by Google's best-in-class ML models and offered to you at no cost.
ML Kit's APIs all run on-device, allowing for real-time use cases where you want to process a live camera stream for example. This also means that the functionality is available offline.
We launched the beta of Text Recognition v2, which adds support for Chinese, Devanagari, Japanese and Korean scripts and greatly increases range of supported languages. It also includes improved ML-based block/paragraph detection and overall increased recognition accuracy.
At Google I/O 2021 we presented ML Kit: Turnkey APIs to use on-device ML in mobile apps. In this session we cover what's new with ML Kit and demonstrate how easy it is to use the SDK to build an app using on-device machine learning.
We also launched a new On-device Machine Learning page that helps mobile and web app developers getting started with on-device ML. It provides a clear overview of all solutions Google offers, from turn-key solutions like ML Kit to tools for training models like TensorFlow Lite Model Maker.
ML Kit is now Generally Available (GA), with the exception of Pose Detection, Entity Extraction, Text Recognition v2 and Selfie Segmentation which are offered in beta.
- Explore the ready-to-use APIs: text recognition, face detection, barcode scanning, image labeling, object detection and tracking, pose detection, selfie segmentation, smart reply, text translation, and language identification.
- Learn how to use custom TensorFlow Lite image labeling models in your apps. Read Custom models with ML Kit.
- Take a look at our sample apps and codelabs. They help you get started with all of the APIs.
If ML Kit's turn-key APIs don't meet your needs and you require a more custom solution, visit the On-device Machine Learning page for guidance on all of Google's solutions and tools for on-device machine learning.