Handwriting recognition is a powerful technology that is widely used in various applications, from scanning documents to recognizing notes and forms. In this tutorial, we will build a custom TensorFlow model to extract text from captcha images using the IAM Dataset. We will begin by collecting and preprocessing the Dataset, then define our model architecture using a CNN with LSTM layers and a CTC loss function. We will then train and evaluate the model and finally test it on a small sample of the test dataset. Along the way, we will discuss ways to improve the performance of our model, such as fine-tuning the hyperparameters, using a different dataset or augmenting the data, testing a different model architecture, or incorporating additional features. This tutorial will provide a good starting point for building an OCR system using TensorFlow.
Text Version Tutorial: pylessons.com/handwriting-rec...
GitHub: github.com/pythonlessons/mltu...
pypi: pypi.org/project/mltu/
#machinelearning #python #tensorflow #opencv #ocr
5 авг 2024
