Accelerate Inference of Mobilenet V2 Image Classification Model with OpenVINO Post-Training Optimization Tool
This tutorial demostrates how to apply INT8 quantization to the Image classification model mobilenet-v2, using the Post-Training Optimization Tool API (part of OpenVINO). We will use mobilenet-v2 and Cifar10 dataset. The code of the tutorial is designed to be extendable to custom models and datasets. It consists of the following steps:
- Download and prepare the Mobilenet-v2 model and dataset
- Define data loading and accuracy validation functionality
- Prepare the model for quantization
- Run optimization pipeline
- Compare performance of the original and quantized models