左侧的图片来自使用 Kotlin（Android 版）编写的 ARCore ML Kit 示例。此示例应用使用机器学习模型对相机视图中的对象进行分类，并将标签附加到虚拟场景中的对象。
ML Kit API 同时适用于 Android 和 iOS 开发，并且 Google Cloud Vision API 具有 REST 和 RPC 接口，因此您可以在使用 Android NDK (C)、您自己的 iOS 应用或 Unity (AR Foundation) 应用中构建的应用中获得与 ARCore ML Kit 示例相同的结果。
[null,null,["最后更新时间 (UTC)：2025-07-26。"],[[["\u003cp\u003eARCore's camera feed can be used with ML Kit and Google Cloud Vision API for identifying real-world objects and creating intelligent AR experiences.\u003c/p\u003e\n"],["\u003cp\u003eThe provided sample app demonstrates object classification by attaching virtual labels to identified objects.\u003c/p\u003e\n"],["\u003cp\u003eML Kit offers cross-platform support for Android and iOS, while Google Cloud Vision API provides REST and RPC interfaces for broader integration.\u003c/p\u003e\n"],["\u003cp\u003eDevelopers can utilize ARCore's data as input for their own machine learning models for object recognition.\u003c/p\u003e\n"],["\u003cp\u003eThese functionalities extend to apps built with Android NDK (C), iOS, and Unity (AR Foundation), offering flexibility in development environments.\u003c/p\u003e\n"]]],[],null,["# Machine learning with ARCore\n\nYou can use the camera feed that ARCore captures in a machine learning pipeline\nwith the [ML Kit](https://developers.google.com/ml-kit) and the [Google Cloud Vision API](https://cloud.google.com/vision) to identify real-world objects, and create an\nintelligent augmented reality experience.\nYour browser does not support the video tag.\n\nThe image at left is taken from the [ARCore ML Kit sample](https://github.com/googlesamples/arcore-ml-sample),\nwritten in Kotlin for Android. This sample app uses a machine learning\nmodel to classify objects in the camera's view and attaches a label to the object\nin the virtual scene.\n\nThe [ML Kit](https://developers.google.com/ml-kit) API provides for both Android\nand iOS development, and the [Google Cloud Vision API](https://cloud.google.com/vision)\nhas both REST and RPC interfaces, so you can achieve the same results as the\nARCore ML Kit sample in your own app built with the Android NDK (C), with iOS, or\nwith Unity (AR Foundation).\n\nSee [Use ARCore as input for Machine Learning models](/ar/develop/java/machine-learning)\nfor an overview of the patterns you need to implement. Then apply these to your\napp built with the Android NDK (C), with iOS, or with Unity (AR Foundation)."]]
