update Fcenet readme (#475)

* update fcenet readme

* Update README.md

change the mindir file path

* Update README_CN.md

change the mindir file path

Author: colawyee

configs/det/fcenet/README.md

@@ -51,7 +51,7 @@ The FCENet in MindOCR is trained on ICDAR 2015 dataset. The training results are
 
 | **Model**              | **Context**       | **Backbone**      | **Pretrained** | **Recall** | **Precision** | **F-score** | **Train T.**     | **Throughput**   | **Recipe**                            | **Download**                                                                                                                                                                                                |
 |---------------------|----------------|---------------|------------|------------|---------------|-------------|--------------|-----------|-------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| FCENet               | D910x4-MS2.0-F | ResNet50   | ImageNet       |  81.51%     | 86.90%        | 84.12%     | 33 s/epoch   | 7 img/s      | [yaml](fce_icdar15.yaml) | [ckpt](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f-5e765611.mindir) |
+| FCENet               | D910x4-MS2.0-F | ResNet50   | ImageNet       |  81.51%     | 86.90%        | 84.12%     | 33 s/epoch   | 7 img/s      | [yaml](fce_icdar15.yaml) | [ckpt](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f-dad7dfcc.mindir) |
 
 </div>
 

configs/det/fcenet/README_CN.md

@@ -53,7 +53,7 @@ MindOCR中的FCENet网络在ICDAR 2015数据集上训练。训练结果如下：
 
 | **模型**              | **环境配置**       | **骨干网络**      | **预训练数据集** | **Recall** | **Precision** | **F-score** | **训练时间**     | **吞吐量**   | **配置文件**                            | **模型权重下载**                                                                                                                                                                                                |
 |---------------------|----------------|---------------|------------|------------|---------------|-------------|--------------|-----------|-------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| FCENet               | D910x4-MS2.0-F | ResNet50   | ImageNet       | 81.51%     | 86.90%        | 84.12%      | 33 s/epoch   | 7 img/s      | [yaml](fce_icdar15.yaml) | [ckpt](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f-5e765611.mindir) |
+| FCENet               | D910x4-MS2.0-F | ResNet50   | ImageNet       | 81.51%     | 86.90%        | 84.12%      | 33 s/epoch   | 7 img/s      | [yaml](fce_icdar15.yaml) | [ckpt](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f.ckpt) \| [mindir](https://download.mindspore.cn/toolkits/mindocr/fcenet/fcenet_resnet50-43857f7f-dad7dfcc.mindir) |
 
 </div>