AutoML Vision Edge terminology

Term Description
Android Studio The official integrated development environment (IDE) for Android app development.
CocoaPods A dependency manager used here for iOS app development; for Swift and Objective-C Cocoa projects to provide a standard format for managing external libraries.
Core ML A machine learning framework used in Apple products. TensorFlow lite models can be converted to CoreML format for use on Apple devices.
Container ("export to Docker/container") The runtime instance of an image; one of the export options for your model using AutoML Vision Edge.
Edge devices A device that provides compute capability outside the cloud. The demand for privacy/confidentiality, low latency and bandwidth constraints drive demand for predictions with our models on these devices. Compute and power constraints lead to models specialized for them.
Edge TPU A type of Edge device; Google's purpose-built application-specific integrated circuit (ASIC) designed to run inference at the edge. Supports .tflite models only.
Firebase A mobile and web application development platform.
FlatBuffers Similar to Protocol buffers, with the primary difference being that FlatBuffers do not need a parsing/ unpacking step to a secondary representation before you can access data, often coupled with per-object memory allocation.
IoT Internet of Things (IoT); the use of network-connected devices, embedded in the physical environment, to improve some existing process or to enable a new scenario not previously possible.
ML Kit ML Kit acts as an API layer to your custom model; a mobile software development kit (SDK) that allows you to use a custom model on-device.
Pillow The Python Imaging Library (PIL) adds image processing capabilities to your Python interpreter; Pillow is a modified version of the base PIL.
Protocol buffers ("protobuf") Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data. Similar to FlatBuffers.
TensorFlow TensorFlow is an end-to-end open source platform for machine learning; software used to create a machine learning model.
TensorFlow lite model (TF Lite/model.tflite) A TensorFlow ML model that has been compressed for use on mobile and embedded devices.

  • TF Lite converter - TensorFlow Lite uses the optimized FlatBuffer format to represent graphs. Therefore, a TensorFlow model (protocol buffer) needs to be converted into a FlatBuffer file before deploying to clients.
  • TF Lite interpreter - A class that does the job of a tf.Session(), only for TF Lite models as opposed to regular TensorFlow models.
tf.session() A class for running TensorFlow operations using a TensorFlow model.
Xcode Xcode is an integrated development environment (IDE) for macOS containing a suite of software development tools developed by Apple for developing software for macOS, iOS, watchOS, and tvOS.