CRNN Text Recognition Model Implemented with PaddlePaddle 2.0 Dynamic Graph

This document introduces a CRNN text recognition model implemented using PaddlePaddle 2.0 dynamic graph. The model extracts features through CNN, performs sequence prediction via RNN, and uses CTC Loss for loss calculation, making it suitable for input images of irregular lengths. **Training and Data Preparation:** 1. **Environment Configuration**: PaddlePaddle 2.0.1 and Python 3.7 need to be installed. 2. **Dataset Generation**: - Use the `create_image.py` script to automatically generate validation