CRNN_Chinese_Characters_Rec

Why we included this project

When you need to read Chinese characters out of images, this is a compact PyTorch reference for the classic CRNN setup: a convolutional network pulls visual features, a recurrent layer handles the character sequence, and CTC loss handles alignment, so the model reads a full line without the image being pre-segmented. The README walks the whole path from data to a working demo, covering the synthetic 360CC dataset (or your own image and label files), training through a YAML config, and a demo script with a checkpoint that reports about 97.7% accuracy on the included benchmark. It's a solid starting point for learning OCR or building Chinese text recognition, with code compact enough to read end to end. One caveat: training is fixed-length and the repo targets PyTorch 1.2 and CUDA 10, so expect to update dependencies before it runs cleanly rather than treating it as plug and play.