From 7c81d482e9fe876dd62d82bd649f5c24f21767ec Mon Sep 17 00:00:00 2001 From: huangjun12 <2399845970@qq.com> Date: Fri, 10 Feb 2023 11:08:40 +0800 Subject: [PATCH] add CT to algorithm overview (#8998) * add ct to model zoo * refine details --- doc/doc_ch/algorithm_overview.md | 2 ++ doc/doc_en/algorithm_overview_en.md | 2 ++ 2 files changed, 4 insertions(+) diff --git a/doc/doc_ch/algorithm_overview.md b/doc/doc_ch/algorithm_overview.md index 49637099..ed556ed9 100755 --- a/doc/doc_ch/algorithm_overview.md +++ b/doc/doc_ch/algorithm_overview.md @@ -32,6 +32,7 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广 - [x] [PSENet](./algorithm_det_psenet.md) - [x] [FCENet](./algorithm_det_fcenet.md) - [x] [DRRG](./algorithm_det_drrg.md) +- [x] [CT](./algorithm_det_ct.md) 在ICDAR2015文本检测公开数据集上，算法效果如下： @@ -51,6 +52,7 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广 |模型|骨干网络|precision|recall|Hmean|下载链接| | --- | --- | --- | --- | --- | --- | |SAST|ResNet50_vd|89.63%|78.44%|83.66%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar)| +|CT|ResNet18_vd|88.68%|81.70%|85.05%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r18_ct_train.tar)| 在CTW1500文本检测公开数据集上，算法效果如下： diff --git a/doc/doc_en/algorithm_overview_en.md b/doc/doc_en/algorithm_overview_en.md index 8fe2a35a..2e25746d 100755 --- a/doc/doc_en/algorithm_overview_en.md +++ b/doc/doc_en/algorithm_overview_en.md @@ -30,6 +30,7 @@ Supported text detection algorithms (Click the link to get the tutorial): - [x] [PSENet](./algorithm_det_psenet_en.md) - [x] [FCENet](./algorithm_det_fcenet_en.md) - [x] [DRRG](./algorithm_det_drrg_en.md) +- [x] [CT](./algorithm_det_ct_en.md) On the ICDAR2015 dataset, the text detection result is as follows: @@ -49,6 +50,7 @@ On Total-Text dataset, the text detection result is as follows: |Model|Backbone|Precision|Recall|Hmean|Download link| | --- | --- | --- | --- | --- | --- | |SAST|ResNet50_vd|89.63%|78.44%|83.66%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar)| +|CT|ResNet18_vd|88.68%|81.70%|85.05%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r18_ct_train.tar)| On CTW1500 dataset, the text detection result is as follows: -- GitLab