Changelog

v0.2.1 (20/7/2021)

Highlights

1. Upgrade to use MMCV-full >= 1.3.8 and MMDetection >= 2.13.0 for latest features

2. Add ONNX and TensorRT export tool, supporting the deployment of DBNet, PSENet, PANet and CRNN (experimental) #278, #291, #300, #328

3. Unified parameter initialization method which uses init_cfg in config files #365

New Features

• Support TextOCR dataset #293

• Support Total-Text dataset #266, #273, #357

• Support grouping text detection box into lines #290, #304

• Add benchmark_processing script that benchmarks data loading process #261

• Add SynthText preprocessor for text recognition models #351, #361

• Support batch inference during testing #310

• Add user-friendly OCR inference script #366

Bug Fixes

• Fix improper class ignorance in SDMGR Loss #221

• Fix potential numerical zero division error in DRRG #224

• Fix installing requirements with pip and mim #242

• Fix dynamic input error of DBNet #269

• Fix space parsing error in LineStrParser #285

• Fix textsnake decode error #264

• Correct isort setup #288

• Fix a bug in SDMGR config #316

• Fix kie_test_img for KIE nonvisual #319

• Fix metafiles #342

• Fix different device problem in FCENet #334

• Ignore improper tailing empty characters in annotation files #358

• Docs fixes #247, #255, #265, #267, #268, #270, #276, #287, #330, #355, #367

• Fix NRTR config #356, #370

Improvements

• Add backend for resizeocr #244

• Skip image processing pipelines in SDMGR novisual #260

• Speedup DBNet #263

• Update mmcv installation method in workflow #323

• Add part of Chinese documentations #353, #362

• Add support for ConcatDataset with two workflows #348

• Add list_from_file and list_to_file utils #226

• Speed up sort_vertex #239

• Support distributed evaluation of KIE #234

• Add pretrained FCENet on IC15 #258

• Support CPU for OCR demo #227

• Avoid extra image pre-processing steps #375

v0.2.0 (18/5/2021)

Highlights

1. Add the NER approach Bert-softmax (NAACL’2019)

2. Add the text detection method DRRG (CVPR’2020)

3. Add the text detection method FCENet (CVPR’2021)

4. Increase the ease of use via adding text detection and recognition end-to-end demo, and colab online demo.

5. Simplify the installation.

New Features

• Add Bert-softmax for Ner task #148

• Add DRRG #189

• Add FCENet #133

• Add end-to-end demo #105

• Support batch inference #86 #87 #178

• Add TPS preprocessor for text recognition #117 #135

• Add demo documentation #151 #166 #168 #170 #171

• Add checkpoint for Chinese recognition #156

• Add metafile #175 #176 #177 #182 #183

• Add support for numpy array inference #74

Bug Fixes

• Fix the duplicated point bug due to transform for textsnake #130

• Fix CTC loss NaN #159

• Fix error raised if result is empty in demo #144

• Fix results missing if one image has a large number of boxes #98

• Fix package missing in dockerfile #109

Improvements

• Simplify installation procedure via removing compiling #188

• Speed up panet post processing so that it can detect dense texts #188

• Add zh-CN README #70 #95

• Support windows #89

• Add Colab #147 #199

• Add 1-step installation using conda environment #193 #194 #195

v0.1.0 (7/4/2021)

Highlights

• MMOCR is released.

Main Features

• Support text detection, text recognition and the corresponding downstream tasks such as key information extraction.

• For text detection, support both single-step (PSENet, PANet, DBNet, TextSnake) and two-step (MaskRCNN) methods.

• For text recognition, support CTC-loss based method CRNN; Encoder-decoder (with attention) based methods SAR, Robustscanner; Segmentation based method SegOCR; Transformer based method NRTR.

• For key information extraction, support GCN based method SDMG-R.

• Provide checkpoints and log files for all of the methods above.