Accelerate Inference of MobileNet V2 Image Classification Model with Post-Training Optimization Tool in OpenVINO™
This tutorial demonstrates how to apply INT8 quantization to the
MobileNet V2 Image Classification model, using the
Post-Training Optimization Tool API
(part of OpenVINO). The tutorial uses mobilenet-v2 and Cifar10 dataset.
The code of the tutorial is designed to be extendable to custom models and
datasets.
The tutorial consists of the following steps:
- Downloading and preparing the Mobilenet-v2 model and the dataset.
- Defining a data loading and an accuracy validation functionality.
- Preparing the model for quantization.
- Running optimization pipeline.
- Comparing performance of the original and quantized models.
If you have not installed all required dependencies, follow the Installation Guide.