adapt ms2.2 (#613)

mindspore-lab · Nov 17, 2023 · 44b56f9 · 44b56f9
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diff --git a/configs/det/dbnet/README.md b/configs/det/dbnet/README.md
@@ -91,7 +91,7 @@ DBNet and DBNet++ were trained on the ICDAR2015, MSRA-TD500, SCUT-CTW1500, Total
 | DBNet               | D910x1-MS2.0-G | ResNet-50     | ImageNet       | 83.53%     | 86.62%        | 85.05%      | 13.3 s/epoch | 75.2 img/s       | [yaml](db_r50_icdar15.yaml)         | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-c3a4aa24.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-c3a4aa24-fbf95c82.mindir)       |
 |                     |                |               |                |            |               |             |              |                |                                     |                                                                                                                                                                                                           |
 | DBNet++             | D910x1-MS2.0-G | ResNet-50     | SynthText  | 85.70%     | 87.81%        | 86.74%      | 17.7 s/epoch | 56 img/s  | [yaml](db++_r50_icdar15.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50-068166c2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50-068166c2-9934aff0.mindir)   |
-| DBNet++             | D910Bx1-MS2.2-G | ResNet-50     | SynthText  | 86.81%     | 86.85%        | 86.86%      | 12.7 s/epoch | 78.2 img/s  | [yaml](db++_r50_icdar15_910B.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910B-35dc71f2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910B-35dc71f2-e61a9c37.mindir) |
+| DBNet++             | D910x1-MS2.2-G | ResNet-50     | SynthText  | 86.81%     | 86.85%        | 86.86%      | 12.7 s/epoch | 78.2 img/s  | [yaml](db++_r50_icdar15_910.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910-35dc71f2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910-35dc71f2-e61a9c37.mindir) |
 </div>
 
 > The input_shape for exported DBNet MindIR and DBNet++ MindIR in the links are `(1,3,736,1280)` and `(1,3,1152,2048)`, respectively.

diff --git a/configs/det/dbnet/README_CN.md b/configs/det/dbnet/README_CN.md
@@ -73,7 +73,7 @@ DBNet和DBNet++在ICDAR2015，MSRA-TD500，SCUT-CTW1500，Total-Text和MLT2017
 | DBNet               | D910x1-MS2.0-G | ResNet-50     | ImageNet       | 83.53%     | 86.62%        | 85.05%      | 13.3 s/epoch | 75.2 img/s       | [yaml](db_r50_icdar15.yaml)         | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-c3a4aa24.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-c3a4aa24-fbf95c82.mindir)       |
 |                     |                |               |            |            |               |             |              |           |                                     |                                                                                                                                                                                                           |
 | DBNet++             | D910x1-MS2.0-G | ResNet-50     | SynthText  | 85.70%     | 87.81%        | 86.74%      | 17.7 s/epoch | 56 img/s  | [yaml](db++_r50_icdar15.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50-068166c2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50-068166c2-9934aff0.mindir)   |
-| DBNet++             | D910Bx1-MS2.2-G | ResNet-50     | SynthText  | 86.81%     | 86.85%        | 86.86%      | 12.7 s/epoch | 78.2 img/s  | [yaml](db++_r50_icdar15_910B.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910B-35dc71f2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910B-35dc71f2-e61a9c37.mindir)   |
+| DBNet++             | D910x1-MS2.2-G | ResNet-50     | SynthText  | 86.81%     | 86.85%        | 86.86%      | 12.7 s/epoch | 78.2 img/s  | [yaml](db++_r50_icdar15_910.yaml)       | [ckpt](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910-35dc71f2.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnetpp_resnet50_910-35dc71f2-e61a9c37.mindir)   |
 </div>
 
 > 链接中模型DBNet的MindIR导出时的输入Shape为`(1,3,736,1280)`，模型DBNet++的MindIR导出时的输入Shape为`(1,3,1152,2048)`。

diff --git a/configs/det/dbnet/db++_r50_icdar15_910B.yaml → configs/det/dbnet/db++_r50_icdar15_910.yaml b/configs/det/dbnet/db++_r50_icdar15_910B.yaml → configs/det/dbnet/db++_r50_icdar15_910.yaml