提交 941fd5f4 编写于 作者: T Topdu

[doc] add svtr algorithm_overview

上级 e9e3e324
......@@ -65,6 +65,7 @@
- [x] [NRTR](./algorithm_rec_nrtr.md)
- [x] [SAR](./algorithm_rec_sar.md)
- [x] [SEED](./algorithm_rec_seed.md)
- [x] [SVTR](./algorithm_rec_svtr.md)
参考[DTRB](https://arxiv.org/abs/1904.01906)[3]文字识别训练和评估流程,使用MJSynth和SynthText两个文字识别数据集训练,在IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE数据集上进行评估,算法效果如下:
......@@ -82,6 +83,7 @@
|NRTR|NRTR_MTB| 84.21% | rec_mtb_nrtr | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar) |
|SAR|Resnet31| 87.20% | rec_r31_sar | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_r31_sar_train.tar) |
|SEED|Aster_Resnet| 85.35% | rec_resnet_stn_bilstm_att | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_resnet_stn_bilstm_att.tar) |
|SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
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......@@ -90,5 +92,3 @@
已支持的端到端OCR算法列表(戳链接获取使用教程):
- [x] [PGNet](./algorithm_e2e_pgnet.md)
......@@ -58,6 +58,7 @@ Supported text recognition algorithms (Click the link to get the tutorial):
- [x] [NRTR](./algorithm_rec_nrtr_en.md)
- [x] [SAR](./algorithm_rec_sar_en.md)
- [x] [SEED](./algorithm_rec_seed_en.md)
- [x] [SVTR](./algorithm_rec_svtr.md)
Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation result of these above text recognition (using MJSynth and SynthText for training, evaluate on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE) is as follow:
......@@ -75,6 +76,7 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
|NRTR|NRTR_MTB| 84.21% | rec_mtb_nrtr | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar) |
|SAR|Resnet31| 87.20% | rec_r31_sar | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_r31_sar_train.tar) |
|SEED|Aster_Resnet| 85.35% | rec_resnet_stn_bilstm_att | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_resnet_stn_bilstm_att.tar) |
|SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
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