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update docs for DBNet and CRNN #78

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Mar 20, 2023
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update docs for DBNet and CRNN #78

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8 changes: 5 additions & 3 deletions configs/det/README.md
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English | [中文](https://github.com/mindspore-lab/mindocr/blob/main/configs/det/README_CN.md)

# DBNet

<!--- Guideline: use url linked to abstract in ArXiv instead of PDF for fast loading. -->
Expand Down Expand Up @@ -34,9 +36,9 @@ The overall architecture of DBNet is presented in _Figure 1._ It consists of mul

### ICDAR2015

| **Model** | **Backbone** | **Pretrained** | **Recall** | **Precision** | **F-score** |
|-----------|--------------|----------------|------------|---------------|-------------|
| DBNet | ResNet-50 | ImageNet | 81.70% | 85.84% | 83.72% |
| **Model** | **Backbone** | **Pretrained** | **Recall** | **Precision** | **F-score** | **Recipe** | **Download** |
|-----------|--------------|----------------|------------|---------------|-------------|--------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------|
| DBNet | ResNet-50 | ImageNet | 81.70% | 85.84% | 83.72% | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/det/db_r50_icdar15.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-db1df47a.ckpt) |

## Quick Start

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8 changes: 5 additions & 3 deletions configs/det/README_CN.md
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[English](https://github.com/mindspore-lab/mindocr/blob/main/configs/det/README.md) | 中文

# DBNet

<!--- Guideline: use url linked to abstract in ArXiv instead of PDF for fast loading. -->
Expand Down Expand Up @@ -25,9 +27,9 @@ DBNet的整体架构图如图1所示，包含以下阶段:

### ICDAR2015

| **模型** | **骨干** | **预训练模型** | **Recall** | **Precision** | **F-score** |
|-----------|--------------|----------------|------------|---------------|-------------|
| DBNet | ResNet-50 | ImageNet | 81.70% | 85.84% | 83.72% |
| **模型** | **骨干网络** | **预训练数据集** | **Recall** | **Precision** | **F-score** | **配置文件** | **模型权重下载** |
|---------|------------|----------------|------------|---------------|-------------|-----------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------|
| DBNet | ResNet-50 | ImageNet | 81.70% | 85.84% | 83.72% | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/det/db_r50_icdar15.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/dbnet/dbnet_resnet50-db1df47a.ckpt) |

## 快速上手

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10 changes: 6 additions & 4 deletions configs/rec/crnn/README.md
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English | [中文](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/README_CN.md)

# CRNN
<!--- Guideline: use url linked to abstract in ArXiv instead of PDF for fast loading. -->

Expand Down Expand Up @@ -35,10 +37,10 @@ According to our experiments, the evaluation results on public benchmark dataset

<div align="center">

| Model| Backbone | Config | Avg Accuracy | Download |
|------|----------|--------|--------------|----------|
| CRNN | VGG7 | [crnn_vgg7.yaml](./crnn_vgg7.yaml) | 82.03 | [model_weights]() |
| CRNN | ResNet34 | [crnn_resnet34.yaml](./crnn_resnet34.yaml) | 84.45 | [model_weights]() |
| **Model** | **Backbone** | **Avg Accuracy** | **Recipe** | **Download** |
|-----------|--------------|------------------|------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------|
| CRNN | VGG7 | 82.03 | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/crnn_vgg7.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/crnn/crnn_vgg7-ea7e996c.ckpt) |
| CRNN | ResNet34 | 84.45 | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/crnn_resnet34.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/crnn/crnn_resnet34-8aa4aedb.ckpt) |


</div>
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10 changes: 6 additions & 4 deletions configs/rec/crnn/README_CN.md
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[English](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/README.md) | 中文

# CRNN
<!--- Guideline: use url linked to abstract in ArXiv instead of PDF for fast loading. -->

Expand Down Expand Up @@ -35,10 +37,10 @@ Table Format:

<div align="center">

| 模型| 骨干网络 | 配置文件 | 平均准确率 | 模型下载 |
|------|----------|--------|--------------|----------|
| CRNN | VGG7 | [crnn_vgg7.yaml](./crnn_vgg7.yaml) | 82.03 | [model_weights]() |
| CRNN | ResNet34 | [crnn_resnet34.yaml](./crnn_resnet34.yaml) | 84.45 | [model_weights]() |
| **模型** | **骨干网络** | **平均准确率** | **配置文件** | **模型权重下载** |
|---------|------------|---------------|------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------|
| CRNN | VGG7 | 82.03 | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/crnn_vgg7.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/crnn/crnn_vgg7-ea7e996c.ckpt) |
| CRNN | ResNet34 | 84.45 | [yaml](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/crnn/crnn_resnet34.yaml) | [weights](https://download.mindspore.cn/toolkits/mindocr/crnn/crnn_resnet34-8aa4aedb.ckpt) |


</div>
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