From d721649148fb200adefcb2d6ccd14068e012fa44 Mon Sep 17 00:00:00 2001 From: wangjingyeye <1025993141@qq.com> Date: Wed, 24 Aug 2022 12:00:51 +0000 Subject: [PATCH] db++ doc --- doc/doc_ch/algorithm_overview.md | 4 +++- doc/doc_en/algorithm_det_db_en.md | 22 ++++++++++++++++++++-- doc/doc_en/algorithm_overview_en.md | 3 ++- 3 files changed, 25 insertions(+), 4 deletions(-) diff --git a/doc/doc_ch/algorithm_overview.md b/doc/doc_ch/algorithm_overview.md index ef96f6ec..cda8b7a9 100755 --- a/doc/doc_ch/algorithm_overview.md +++ b/doc/doc_ch/algorithm_overview.md @@ -17,7 +17,7 @@ ### 1.1 文本检测算法 已支持的文本检测算法列表（戳链接获取使用教程）： -- [x] [DB](./algorithm_det_db.md) +- [x] [DB与DB++](./algorithm_det_db.md) - [x] [EAST](./algorithm_det_east.md) - [x] [SAST](./algorithm_det_sast.md) - [x] [PSENet](./algorithm_det_psenet.md) @@ -34,6 +34,8 @@ |SAST|ResNet50_vd|91.39%|83.77%|87.42%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)| |PSE|ResNet50_vd|85.81%|79.53%|82.55%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_vd_pse_v2.0_train.tar)| |PSE|MobileNetV3|82.20%|70.48%|75.89%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_mv3_pse_v2.0_train.tar)| +|DB|ResNet50|86.41%|78.72%|82.38%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)| +|DB++|ResNet50|90.89%|82.66%|86.58%|[合成数据预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/ResNet50_dcn_asf_synthtext_pretrained.pdparams)/[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_db%2B%2B_icdar15_train.tar)| 在Total-text文本检测公开数据集上，算法效果如下： diff --git a/doc/doc_en/algorithm_det_db_en.md b/doc/doc_en/algorithm_det_db_en.md index f5f333a0..0bd0152c 100644 --- a/doc/doc_en/algorithm_det_db_en.md +++ b/doc/doc_en/algorithm_det_db_en.md @@ -1,4 +1,4 @@ -# DB +# DB and DB++ - [1. Introduction](#1) - [2. Environment](#2) @@ -21,13 +21,23 @@ Paper: > Liao, Minghui and Wan, Zhaoyi and Yao, Cong and Chen, Kai and Bai, Xiang > AAAI, 2020 +> [Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion](https://arxiv.org/abs/2202.10304) +> Liao, Minghui and Zou, Zhisheng and Wan, Zhaoyi and Yao, Cong and Bai, Xiang +> TPAMI, 2022 + On the ICDAR2015 dataset, the text detection result is as follows: |Model|Backbone|Configuration|Precision|Recall|Hmean|Download| | --- | --- | --- | --- | --- | --- | --- | |DB|ResNet50_vd|[configs/det/det_r50_vd_db.yml](../../configs/det/det_r50_vd_db.yml)|86.41%|78.72%|82.38%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)| |DB|MobileNetV3|[configs/det/det_mv3_db.yml](../../configs/det/det_mv3_db.yml)|77.29%|73.08%|75.12%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar)| +|DB++|ResNet50|[configs/det/det_r50_db++_ic15.yml](../../configs/det/det_r50_db++_ic15.yml)|90.89%|82.66%|86.58%|[pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/ResNet50_dcn_asf_synthtext_pretrained.pdparams)/[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_db%2B%2B_icdar15_train.tar)| + +On the TD_TR dataset, the text detection result is as follows: +|Model|Backbone|Configuration|Precision|Recall|Hmean|Download| +| --- | --- | --- | --- | --- | --- | --- | +|DB++|ResNet50|[configs/det/det_r50_db++_td_tr.yml](../../configs/det/det_r50_db++_td_tr.yml)|92.92%|86.48%|89.58%|[合成数据预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/ResNet50_dcn_asf_synthtext_pretrained.pdparams)/[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_db%2B%2B_td_tr_train.tar)| ## 2. Environment @@ -96,4 +106,12 @@ More deployment schemes supported for DB: pages={11474--11481}, year={2020} } -``` \ No newline at end of file + +@article{liao2022real, + title={Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion}, + author={Liao, Minghui and Zou, Zhisheng and Wan, Zhaoyi and Yao, Cong and Bai, Xiang}, + journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, + year={2022}, + publisher={IEEE} +} +``` diff --git a/doc/doc_en/algorithm_overview_en.md b/doc/doc_en/algorithm_overview_en.md index bc96cdf2..d8f9428a 100755 --- a/doc/doc_en/algorithm_overview_en.md +++ b/doc/doc_en/algorithm_overview_en.md @@ -17,7 +17,7 @@ This tutorial lists the OCR algorithms supported by PaddleOCR, as well as the mo ### 1.1 Text Detection Algorithms Supported text detection algorithms (Click the link to get the tutorial): -- [x] [DB](./algorithm_det_db_en.md) +- [x] [DB and DB++](./algorithm_det_db_en.md) - [x] [EAST](./algorithm_det_east_en.md) - [x] [SAST](./algorithm_det_sast_en.md) - [x] [PSENet](./algorithm_det_psenet_en.md) @@ -34,6 +34,7 @@ On the ICDAR2015 dataset, the text detection result is as follows: |SAST|ResNet50_vd|91.39%|83.77%|87.42%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)| |PSE|ResNet50_vd|85.81%|79.53%|82.55%|[trianed model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_vd_pse_v2.0_train.tar)| |PSE|MobileNetV3|82.20%|70.48%|75.89%|[trianed model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_mv3_pse_v2.0_train.tar)| +|DB++|ResNet50|90.89%|82.66%|86.58%|[合成数据预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/ResNet50_dcn_asf_synthtext_pretrained.pdparams)/[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_db%2B%2B_icdar15_train.tar)| On Total-Text dataset, the text detection result is as follows: -- GitLab