在移动设备和 IoT 设备上部署机器学习模型
TensorFlow Lite 是一种用于设备端推断的开源深度学习框架。
我们的一些 TensorFlow Lite 用户
Pose estimation and classification on edge devices with MoveNet
MoveNet is the state-of-the-art pose estimation model for mobile devices which can run in realtime on modern smartphones. Learn about recent updates and how you can do custom pose classification on Android, iOS and Raspberry Pi.
Build fast, sparse on-device models with the new TF MOT Pruning API
如需缩小移动和网络机器学习开发之间的差距，您可以利用 WebAssembly 的强大功能，将 TensorFlow Lite Task 库轻松部署到网络。
How TensorFlow helps Edge Impulse make ML accessible to embedded engineers
The TensorFlow ecosystem enables companies like Edge Impulse to put artificial intelligence in the hands of domain experts who are building the next generation of consumer and industrial technologies.
使用 TensorFlow Lite 训练您自己的自定义对象检测模型
了解如何通过仅编写几行代码，就能训练自定义对象检测模型并将其部署到 Android 应用中。您只需要有 Android Studio 和网络浏览器即可。无需具备机器学习知识。