Handwriting Text Identifier Model
This project demonstrates a handwriting text identifier model built using Convolutional Neural Networks (CNNs), trained to recognize handwritten digits similar to the MNIST dataset. The model processes images by:
Converting to grayscale Resizing to 28x28 pixels Normalizing pixel values Using CNN for digit classification The project includes data preprocessing, model training, and prediction steps implemented in Python using TensorFlow and OpenCV. You can download the pre-trained model, upload an image for prediction, or run it locally for optical character recognition (OCR) applications.