umangptl / App-Handwritten-Number-Recognition

IOS App πŸ“± for number πŸ”Ž recognization

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App-Handwritten-Number-Recognition

This project focuses on implementing an IOS application to recognize handwritten numbers from 0-9. The model utilizes a MNISTClassifier.mlmodel from Apple's website MNIST Drawing Classification

This iOS app allows users to draw digits on the screen and predict the digit using CoreML and Vision frameworks. It includes a simple canvas for drawing, a prediction button, and options to clear the canvas or load predefined images for testing.

Features

  • Drawing Canvas: Allows users to draw digits on the screen using touch gestures.
  • CoreML Prediction: Utilizes a pre-trained CoreML model to predict the drawn digit and also give a probability match.
  • Predefined Images: Provides options to load predefined images for quick testing.

Screenshots

Home-Page

Canva-Page

Recog-Page

Prerequisites

  • Xcode installed on your development machine.
  • iOS device or simulator to run the app.

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IOS App πŸ“± for number πŸ”Ž recognization


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