This repository contains a classification with Keras and deep learning on grocery store image dataset. This dataset not only contains a large volume of natural images but also includes the corresponding information. We reorganize the dataset because our aim is to build a simple classification model. Then we fine-tune the DenseNet-169 for 100 epochs on our dataset.
It is available at https://github.com/marcusklasson/GroceryStoreDataset.
build_dataset ----dataset=/path to grocery store image dataset
The dataset consists of 5125 images from 81 classes.
--dataset dataset --model output/activity.model --label-bin output/lb.pickle --plot output/plot.png --epochs 100
The classification accuracy from fine-tuned DenseNet-169 is 0.98.
--model output/activity.model --labels output/lb.pickle --image assets/pic/Granny-Smith.jpg
