Skip to content

Created an Android App which classifies and reconizes digit of MNIST dataset using Tensorflow-Lite and Keras.Trained the model on Laptop and deployed it on the android device.

License

Notifications You must be signed in to change notification settings

pdx97/Digit-Classification-of-MNIST-Dataset-using-Tensorflow-Lite

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Digit-Classification-of-MNIST-Dataset-using-Tensorflow-Lite This is a handwritten character image (MNIST) classifier that can run on any android device. The app stores a set of images (0-9) that we can cycle through and classify in order. It uses a pre-trained model to perform inference on the device. This idea can be applied to any images, both by using the camera and by pulling from the Web. We're using preloaded images so we can run the app in a simulator (no need for the device since it doesn't require a camera).

Installation Steps

Step 1

Download Android studio

https://developer.android.com/studio/index.html

Step 2

Download Android SDK

$ wget https://dl.google.com/android/android-sdk_r24.4.1-linux.tgz

$ tar xvzf android-sdk_r24.4.1-linux.tgz -C ~/tensorflow

Step 3

Download SDK Build Tools

$ cd ~/tensorflow/android-sdk-linux
$ tools/android update sdk --no-ui

Step 4

Download Android NDK

$ wget https://dl.google.com/android/repository/android-ndk-r12b-linux-x86_64.zip
$ unzip android-ndk-r12b-linux-x86_64.zip -d ~/tensorflow

Step 5

Train Model in Python on your desktop or a server

tensorflow_model/mnist_convnet_keras.py
tensorflow_model/mnist_convnet.py

Youtube Presentation

About

Created an Android App which classifies and reconizes digit of MNIST dataset using Tensorflow-Lite and Keras.Trained the model on Laptop and deployed it on the android device.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published