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An attempt to classify digits 0-9 drawn on an Android app by classifying the dataset using the TFLite utility.

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nikhil-sachdeva/DigitsClassifier

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DigitsClassifier

It is an attempt to classify digits drawn in an Android app from 0 to 9.

App Working App Working


V1


1. Retrained mobilenet TF model for MNIST dataset to classify digits.
2. Accuracy was ~60% because of the difference in the digits drawn and the dataset.

V2


  1. Trained the dataset created through the first app in a CNN model. Dateset is available here.
  2. Saved weights in summary.h5 file, created the Graph.pb TF file using amir-abdi/keras_to_tensorflow. And then finally converted the Graph.pb file to a optimized_graph.lite file using tflite_convert(a TF utility).
  3. The optimized_graph.lite file can be directly used in the app, which can now classify drawn digits with a ~60-70% accuracy.
  4. The mobilenet model re-trained for the given dataset can classify drawn digits with accuracy upto ~90%.

Tensorboard Visualization of Model

App Working



Resources used

  1. Keras Documentation
  2. Tensorflow For Poets
  3. Drawing View Library.
  4. amir-abdi/keras_to_tensorflow
  5. TFLite Convert

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An attempt to classify digits 0-9 drawn on an Android app by classifying the dataset using the TFLite utility.

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