crnn

Why we included this project

The original CRNN implementation is written in Torch7 and pairs a CNN feature extractor with a recurrent network and CTC loss, turning images of text straight into readable sequences. Instead of segmenting characters, the model learns to recognize whole words from the image, a design that made the accompanying paper a frequent starting point for later OCR work. Anyone digging into how OCR models work or trying to reproduce classic results will find the training and inference code useful. Deployment is a different matter: the project targets Ubuntu with CUDA GPUs and ships a pretrained Torch7 model, so most teams today will reach for the maintained PyTorch port linked in the repo. For understanding the original architecture and training pipeline, though, this is the source to read.