Fcenet readme update #495
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Fcenet readme update #495
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change the mindir file path
change the mindir file path
HaoyangLee
reviewed
Jul 11, 2023
configs/det/fcenet/README.md
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| @@ -51,7 +51,7 @@ The FCENet in MindOCR is trained on ICDAR 2015 dataset. The training results are | |||
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| | **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% | 95.59 s/epoch | 2.59 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) | | |||
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Suggested change
| | FCENet | D910x4-MS2.0-F | ResNet50 | ImageNet | 81.51% | 86.90% | 84.12% | 95.59 s/epoch | 2.59 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) | | |
| | FCENet | D910x4-MS2.0-F | ResNet50 | ImageNet | 81.51% | 86.90% | 84.12% | 95.59 s/epoch | 10.38 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) | |
日志中显示的是单卡fps，此处填写多（四）卡fps，约等于单卡fps *4
configs/det/fcenet/README.md
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| @@ -51,7 +51,7 @@ The FCENet in MindOCR is trained on ICDAR 2015 dataset. The training results are | |||
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| | **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% | 95.59 s/epoch | 2.59 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) | | |||
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补充一列ms/step，可从日志中的per step time获取，多个epoch取个均值
# Conflicts: # configs/det/fcenet/README.md # configs/det/fcenet/README_CN.md update fcenet readme
hadipash
approved these changes
Jul 13, 2023
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It would be better to combine with #468 |
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update log data |
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