What impact does post-training quantization have when converting a TensorFlow object detection model to TensorFlow Lite in terms of accuracy and performance on iOS devices?
Post-training quantization is a widely adopted technique used to optimize deep learning models—such as those built with TensorFlow—for deployment on edge devices, including iOS smartphones and tablets. When converting a TensorFlow object detection model to TensorFlow Lite, quantization offers significant benefits in terms of both model size and inference speed, but it also introduces certain
- Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Google tools for Machine Learning, TensorFlow object detection on iOS
What are the necessary steps to build the TensorFlow Lite library for iOS, and where can you find the source code for the sample app?
To build the TensorFlow Lite library for iOS, there are several necessary steps that need to be followed. This process involves setting up the necessary tools and dependencies, configuring the build settings, and compiling the library. Additionally, the source code for the sample app can be found in the TensorFlow GitHub repository. In this answer,
What are the prerequisites for using TensorFlow Lite with iOS, and how can you obtain the required model and labels files?
To use TensorFlow Lite with iOS, there are certain prerequisites that need to be fulfilled. These include having a compatible iOS device, installing the necessary software development tools, obtaining the model and labels files, and integrating them into your iOS project. In this answer, I will provide a detailed explanation of each step. 1. Compatible
- Published in Artificial Intelligence, EITC/AI/TFF TensorFlow Fundamentals, Programming TensorFlow, TensorFlow Lite for iOS, Examination review