Application Architecture

Application Architecture of Saral App

Overall Architecture

Saral SDK and Application Architecture

Handwritten Digits ML Model

Handwritten Digits Machine Learning model is build using Python,Keras ,Tensor-flow technologies.

This Machine Learning model is built on Resnet164 Architecture.

To embed this model in Android SDK/Application , its converted from HDF5 to TFLite format.

Model is trained on MNIST Handwritten digits open data-set along with handwritten digits from the field.

OpenCV is used for capturing ROI’s(Region Of Interest) and processing images before passing them to ML model for prediction.

OMR(Optical Mark Recognition) Detection

For OMR detection Saral SDK uses OpenCV Computer Vision Technology to capture answer sheet images , sub-divide them into individual ROI(Region of Interest Images).

Individual ROI(Region Of Interest) images of answer sheet are processed using OTSU thresholding in OpenCV and predict if OMR bubble is filled or unfilled using pixel count.

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