ML Kit is a mobile SDK that puts Google's machine learning knowledge into a strong but easy-to-use kit for Android and iOS devices. If you're new or seasoned in machine learning, the features you need can be implemented in just a few lines of code. There's no need to have deep knowledge of neural networks or model optimization to get started. On the other hand, if you're an experienced ML creator, ML Kit provides convenient APIs that let you use your mobile apps with your custom TensorFlow Lite models.
How's It Working Out?
ML Kit supports the implementation of ML techniques in your applications by putting together Google's ML tools, such as the Google Cloud Vision API, TensorFlow Lite, and the Android Neural Networks API in a single SDK. If you need the strength of cloud-based computing, the real-time functionality of mobile-optimized on-device models, or the versatility of custom TensorFlow Lite models, with only a few lines of code, ML Kit makes this possible.
You can recognize text in any Latin language with ML Kit's text recognition APIs (and more, with Cloud-based text recognition).
Text recognition will simplify repetitive credit cards, receipts, and business card data entries. You can also extract text from pictures of documents using the Cloud-based API, which can be used to improve transparency or to translate documents. Apps can also keep track of real-world artifacts, for instance by reading the train numbers.
You can detect faces in an image with ML Kit's face detection API, recognize main facial features, and get the contours of detected faces.
You can get the details you need to perform tasks with face recognition, such as embellishing selfies and portraits or creating avatars from a user's image. Due to its real-time face detection feature, Google Firbase ML Kit can be used in applications including games or video chats as video chats that respond to the expressions of the player.
Object Detection And Tracking
For ML Kit's on-device object detection and tracking API, the most prominent objects in an image or live camera feed can be localized and tracked in real-time. Optionally, you can also group observed objects into one of many generic groups.
Detection and tracking of objects with a coarse classification are useful to create live visual search experiences. It functions well as the front end of a longer visual search pipeline because object detection and tracking happen quickly and fully on the computer. After detecting and filtering objects, you can pass them on to a cloud backend like Cloud Vision Product Search, or to a custom model like one you learned using AutoML Vision Edge.
You can identify well-known landmarks in an image using ML Kit 's landmark recognition API.
If you send a picture to this API, you get the landmarks recognized in it, along with the geographic coordinates of each landmark, and the region of the landmark picture. This information can be used to produce image metadata automatically, to create individualized experiences for users based on the content they post, and more.
You can evaluate the language of a string of text using ML Kit's on-device language recognition API.
Language recognition may be useful when dealing with user-provided text that sometimes does not come with any information in the language.
You can automatically translate text between 59 languages with ML Kit's on-device Translation API.
With the Smart Response API of ML Kit, you can create appropriate responses to the messages automatically. Smart Reply allows your users to respond quickly to messages, making it easier to respond to app messages with limited input capabilities.
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