/KivyAndroidClassification

Image Classification for Android using Artificial Neural Network using NumPy and Kivy.

Primary LanguagePython

KivyAndroidClassification

Image Classification for Android using Artificial Neural Network using NumPy and Kivy.

This project runs a pre-trained artificial neural network (ANN) in Android for image classification. The ANN is built using NumPy (Numerical Python). In order to be able to run NumPy in Android, the Kivy framework is used for running NumPy on top of it. Kivy is a cross-platform Python framework which supports packaging Python libraries within the APK file.

The ANN created using NumPy is trained in a desktop computer using 4 classes from the Fruits360 dataset which are apple Braeburn, lemon Meyer, mango, and raspberry. The weights of the ANN are optimized using the genetic algorithm (GA). The optimized weights are saved in a NumPy binary file (.npy). This file is named weights.npy.

After the ANN is trained successfully, a Kivy desktop application is created that invokes this NPY file for predicting the class label of new test images. The application has 2 main files. The first is a KV file that holds the layout of the user interface which is named first.kv. The second one is a Python file that reads an image, loads the weights.npy file, classify the image, and print its class label on the screen. This file is named main.py.

After making sure the desktop application is working successfully, the Kivy application is exported into an Android application using Buildozer and python-4-android. Within it, a test image could be fed into the pre-trained ANN for classifying it. For building the Android application, the buildozer.spec file is requirdd.

The next figure shows the window of the application after running it in Linux. 5

For details about building the ANN from scratch in NumPy, extracting the features, optimization using GA, and feature reduction, you can read my previous tutorials that covers these points in details.

Artificial Neural Network Implementation using NumPy and Classification of the Fruits360 Image Dataset

Its GitHub project: https://github.com/ahmedfgad/NumPyANN

Artificial Neural Networks Optimization using Genetic Algorithm with Python

Its GitHub project: https://github.com/ahmedfgad/NeuralGenetic

Feature Reduction using Genetic Algorithm with Python

Its GitHub project: https://github.com/ahmedfgad/FeatureReductionGenetic

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