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Grocery Store Image Classification with Keras

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.

down the grocery store image dataset

It is available at https://github.com/marcusklasson/GroceryStoreDataset.

build dataset

build_dataset ----dataset=/path to grocery store image dataset

The dataset consists of 5125 images from 81 classes.

train

--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.

Instance Segmentation Sample

predict

--model output/activity.model --labels output/lb.pickle --image assets/pic/Granny-Smith.jpg

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