Firebase ML Kit has introduced to us at Google I/O 18. ML Kit is a mobile SDK that enables Android and iOS developers to have advanced Machine learning capabilities into their mobile app with ease. In Mobile app development, machine learning has become an integral part. Most of the big companies like Uber, Facebook, Microsoft, etc. rely on Machine learning for their businesses which helps them to know their users better and provide them with a better experience on their apps. So as a mobile app developer, it is essential to integrate some kind of intelligence into the app for better user experience. Let’s get an Overview of Firebase ML Kit.
What is Firebase ML Kit
Integrating ML Kit is one of the best and simplest tools that developers can incorporate into their mobile apps. Even a junior mobile app developer can deal with this task. ML Kit is available only in beta version, which can be launched using Firebase. There are 11 features available on Firebase ML Kit.
Top features of ML Kit are:
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Text recognition:
This text recognition feature is available both in the Cloud and on-device. This API enables the recognition of any Latin-based language in text form, facilitating the automation of tedious data entry tasks for credit cards, receipts, and business cards. The Cloud-based API enables developers to obtain the text from pictures of documents. This text is further used for documents translation or accessibility increase. Text recognition will allow the apps to read the numbers on real-world objects.
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Face Detection:
Users utilize the Face Detection API to detect faces in images, extract vital facial features, and construct contours of the detected faces. This is an offline feature using which the users can extract faces from pictures and edit them using the various filters. Even it is possible to generate avatars form users photos. Since it provides users to apply face detection feature in real-time mode, developers may integrate it into video chat or games.
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Barcode Scanning:
Using barcode scanner API which allows users to read data from barcodes using most standard barcode formats. The scanning is performed on the devices, and the internet is not necessary. With this barcode scanning, users can discern what is concealed in encoded data. This is the most comfortable way to detect the encoded data either it is contact information or any payment data.
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Image Labeling:
With the ML Kit API, you can develop an app to recognize objects in images. Recognition is a standalone feature accessible in both cloud and offline modes, without any need for additional metadata. The image labeling feature in the mobile app enables users to identify everything depicted in the picture. Users will get a list of all objects like people, animals, buildings, and so on. The recognized image will come with a score indicating the confidence level of the ML model. With this feature, the users can perform automatic metadata generation and content moderation.
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Object Detection and Tracking:
This API works on the device, which will be helpful for uses to localise and track objects in an image or live camera feed. The image can be classified into the selected general category. This feature will be more beneficial if the users want to build live search experience. After detecting all objects, the user has the option to send them to the cloud backend or a custom model.
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Landmark recognition:
This Landmark recognition API is available only in Cloud, which makes it possible to recognise well-known landmarks in any images. Furthermore, indicating the geo-coordinates of landmarks allows users to determine the location where the picture was taken. This information can utilize for metadata generation, delivering a personalized experience to users.
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Language identification:
Using this API, you can identify the language from one text string. Translators utilize this feature to determine the language written in an image or document.
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Translation:
Using this feature, you can translate up to 59 languages and so users can switch between languages, which means you can select various combinations of translations. This translation API uses the same standards used by Google Translate offline app.
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Smart reply:
Smart reply API produces reply suggestions based on the whole conversation. By using this feature, users receive comprehensive suggestions, not just for short answers like “yes” or “no.” This capability facilitates rapid message responses, as the replies are automatically generated. Currently, the system supports only the English language.
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AutoML Model inference:
This feature allows developers to train their image labelling models. The on-device image labeling API model is trained to recognize up to 400 different categories. But it is very much needed to narrow down the number of objects to recognise more specific ones. Consider the scenario where a user needs to distinguish between dog breeds. In this case, developers utilize the AutoML Vision Edge tool to train the model with images of the required dog breeds uploaded by them.
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Custom model inference:
Skilled developers best utilize this feature when they cannot find an appropriate ready-made model. They use ML Kit to build their custom model tailored to their needs. For this, the developers use TensorFlow Lite model with ML Kit.
Firebase ML Kit remains available in its beta version, with the caveat that all APIs may undergo changes in ways that are not backwards-compatible. This is an overview on Firebase ML Kit.
What are reasons to use Firebase ML Kit?
- Clear and easy to use
- Custom Models
- On-device and Cloud APIs
- Multi-platform
How other Firebase services associate with ML Kit
Other Firebase services may function Flawlessly with ML Kit SDK. Users employ Google Analytics to measure user engagement, while Cloud Firestore can store image labeling. Additionally, remote config and ML Kit facilitate easy A/B testing of custom ML models. Hope you got an overview of Firebase ML Kit.
We krify the leading mobile app development company based in India, and the UK has expertise developers in working with Firebase ML Kit.
If you are interested in integrating Firebase ML Kit features in your mobile app for better functioning and also to create trendiness to the app. Please contact us for more information.
