Transformer-based Scene Text Recognition (Transformer-STR)
PyTorch implementation of my new method for Scene Text Recognition (STR) based on Transformer.
I adapted the four-stage STR framework devised by deep-text-recognition-benchmark, and replaced the Pred. stage with Transformer.
Equipped with Transformer, this method outperforms the best model of the aforementioned deep-text-recognition-benchmark by 7.6% on CUTE80.
Download pretrained weights from here
This pre-trained weights trained on Synthetic dataset for about 700K iters.
Git clone this repo and download the weights file, move it to checkpoints directory.
Download lmdb dataset for traininig and evaluation from here(provided by deep-text-recognition-benchmark)
data_lmdb_release.zip contains below. training datasets : MJSynth (MJ) and SynthText (ST) validation datasets : the union of the training sets IC13, IC15, IIIT, and SVT. evaluation datasets : benchmark evaluation datasets, consist of IIIT, SVT, IC03, IC13, IC15, SVTP, and CUTE.