From 4725a5578fba03da3e252e11f0991c7162326f50 Mon Sep 17 00:00:00 2001 From: zhoujun Date: Tue, 15 Nov 2022 18:48:02 +0800 Subject: [PATCH] add can, stt to algorithm_overview_en.md (#8317) --- doc/doc_ch/algorithm_overview.md | 30 +++++++++++++++++++++++++ doc/doc_en/algorithm_overview_en.md | 34 ++++++++++++++++++++++++++++- 2 files changed, 63 insertions(+), 1 deletion(-) diff --git a/doc/doc_ch/algorithm_overview.md b/doc/doc_ch/algorithm_overview.md index 7f6919c1..02a4cbad 100755 --- a/doc/doc_ch/algorithm_overview.md +++ b/doc/doc_ch/algorithm_overview.md @@ -3,6 +3,8 @@ - [1. 两阶段OCR算法](#1) - [1.1 文本检测算法](#11) - [1.2 文本识别算法](#12) + - [1.3 文本超分辨率算法](#13) + - [1.4 公式识别算法](#14) - [2. 端到端OCR算法](#2) - [3. 表格识别算法](#3) - [4. 关键信息抽取算法](#4) @@ -107,6 +109,34 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广 |RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)| |RFL|ResNetRFL| 88.63% | rec_resnet_rfl_att | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_resnet_rfl_att_train.tar) | + + + +### 1.3 文本超分辨率算法 +已支持的文本超分辨率算法列表（戳链接获取使用教程）： +- [x] [Text Gestalt](./algorithm_sr_gestalt.md) +- [x] [Text Telescope](./algorithm_sr_telescope.md) + +在TextZoom公开数据集上，算法效果如下： + +|模型|骨干网络|PSNR_Avg|SSIM_Avg|配置文件|下载链接| +|---|---|---|---|---|---| +|Text Gestalt|tsrn|19.28|0.6560| [configs/sr/sr_tsrn_transformer_strock.yml](../../configs/sr/sr_tsrn_transformer_strock.yml)|[训练模型](https://paddleocr.bj.bcebos.com/sr_tsrn_transformer_strock_train.tar)| +|Text Telescope|tbsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[训练模型](https://paddleocr.bj.bcebos.com/contribution/sr_telescope_train.tar)| + + + +### 1.4 公式识别算法 + +已支持的公式识别算法列表（戳链接获取使用教程）： +- [x] [CAN](./algorithm_rec_can.md.md) + +在CROHME手写公式数据集上，算法效果如下： + +|模型 |骨干网络|配置文件|ExpRate|下载链接| +| ----- | ----- | ----- | ----- | ----- | +|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_d28_can_train.tar)| + ## 2. 端到端算法 diff --git a/doc/doc_en/algorithm_overview_en.md b/doc/doc_en/algorithm_overview_en.md index 309d074e..fad0fb8a 100755 --- a/doc/doc_en/algorithm_overview_en.md +++ b/doc/doc_en/algorithm_overview_en.md @@ -3,6 +3,8 @@ - [1. Two-stage OCR Algorithms](#1) - [1.1 Text Detection Algorithms](#11) - [1.2 Text Recognition Algorithms](#12) + - [1.3 Text Super-Resolution Algorithms](#13) + - [1.4 Formula Recognition Algorithm](#14) - [2. End-to-end OCR Algorithms](#2) - [3. Table Recognition Algorithms](#3) - [4. Key Information Extraction Algorithms](#4) @@ -104,6 +106,36 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r |RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)| |RFL|ResNetRFL| 88.63% | rec_resnet_rfl_att | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_resnet_rfl_att_train.tar) | + + +### 1.3 Text Super-Resolution Algorithms + +Supported text super-resolution algorithms (Click the link to get the tutorial): +- [x] [Text Gestalt](./algorithm_sr_gestalt.md) +- [x] [Text Telescope](./algorithm_sr_telescope.md) + +On the TextZoom public dataset, the effect of the algorithm is as follows: + +|Model|Backbone|PSNR_Avg|SSIM_Avg|Config|Download link| +|---|---|---|---|---|---| +|Text Gestalt|tsrn|19.28|0.6560| [configs/sr/sr_tsrn_transformer_strock.yml](../../configs/sr/sr_tsrn_transformer_strock.yml)|[trained model](https://paddleocr.bj.bcebos.com/sr_tsrn_transformer_strock_train.tar)| +|Text Telescope|tbsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[trained model](https://paddleocr.bj.bcebos.com/contribution/sr_telescope_train.tar)| + + + +### 1.4 Formula Recognition Algorithm + +Supported formula recognition algorithms (Click the link to get the tutorial): + +- [x] [CAN](./algorithm_rec_can.md.md) + +On the CROHME handwritten formula dataset, the effect of the algorithm is as follows: + +|Model |Backbone|Config|ExpRate|Download link| +| ----- | ----- | ----- | ----- | ----- | +|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72%|[trained model](https://paddleocr.bj.bcebos.com/contribution/rec_d28_can_train.tar)| + + ## 2. End-to-end OCR Algorithms @@ -122,7 +154,7 @@ On the PubTabNet dataset, the algorithm result is as follows: |Model|Backbone|Config|Acc|Download link| |---|---|---|---|---| -|TableMaster|TableResNetExtra|[configs/table/table_master.yml](../../configs/table/table_master.yml)|77.47%|[trained](https://paddleocr.bj.bcebos.com/ppstructure/models/tablemaster/table_structure_tablemaster_train.tar) / [inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/tablemaster/table_structure_tablemaster_infer.tar)| +|TableMaster|TableResNetExtra|[configs/table/table_master.yml](../../configs/table/table_master.yml)|77.47%|[trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/tablemaster/table_structure_tablemaster_train.tar) / [inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/tablemaster/table_structure_tablemaster_infer.tar)| -- GitLab