Skip to content

GitLab

"vscode:/vscode.git/clone" did not exist on "bdad0cefe69cfe41cebe040112a293f738eb526e"
Commit 41a1b292 authored by Leif's avatar Leif
Browse files

Merge remote-tracking branch 'origin/dygraph' into dygraph

parents 9471054e 3d30899b
Hide whitespace changes
Inline Side-by-side
Showing with 577 additions and 93 deletions
deploy/slim/quantization/README_en.md
View file @ 41a1b292
## Introduction ## Introduction
Generally, a more complex model would achive better performance in the task, but it also leads to some redundancy in the model. Generally, a more complex model would achieve better performance in the task, but it also leads to some redundancy in the model.
Quantization is a technique that reduces this redundancy by reducing the full precision data to a fixed number, Quantization is a technique that reduces this redundancy by reducing the full precision data to a fixed number,
so as to reduce model calculation complexity and improve model inference performance. so as to reduce model calculation complexity and improve model inference performance.
...@@ -31,14 +31,14 @@ python setup.py install ...@@ -31,14 +31,14 @@ python setup.py install
``` ```
### 2. Download Pretrain Model ### 2. Download Pre-trained Model
PaddleOCR provides a series of trained [models](../../../doc/doc_en/models_list_en.md). PaddleOCR provides a series of pre-trained [models](../../../doc/doc_en/models_list_en.md).
If the model to be quantified is not in the list, you need to follow the [Regular Training](../../../doc/doc_en/quickstart_en.md) method to get the trained model. If the model to be quantified is not in the list, you need to follow the [Regular Training](../../../doc/doc_en/quickstart_en.md) method to get the trained model.
### 3. Quant-Aware Training ### 3. Quant-Aware Training
Quantization training includes offline quantization training and online quantization training. Quantization training includes offline quantization training and online quantization training.
Online quantization training is more effective. It is necessary to load the pre-training model. Online quantization training is more effective. It is necessary to load the pre-trained model.
After the quantization strategy is defined, the model can be quantified. After the quantization strategy is defined, the model can be quantified.
The code for quantization training is located in `slim/quantization/quant.py`. For example, to train a detection model, the training instructions are as follows: The code for quantization training is located in `slim/quantization/quant.py`. For example, to train a detection model, the training instructions are as follows:
...@@ -54,7 +54,7 @@ python deploy/slim/quantization/quant.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3 ...@@ -54,7 +54,7 @@ python deploy/slim/quantization/quant.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3
### 4. Export inference model ### 4. Export inference model
After getting the model after pruning and finetuning we, can export it as inference_model for predictive deployment: Once we got the model after pruning and fine-tuning, we can export it as an inference model for the deployment of predictive tasks:
```bash ```bash
python deploy/slim/quantization/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o Global.checkpoints=output/quant_model/best_accuracy Global.save_inference_dir=./output/quant_inference_model python deploy/slim/quantization/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o Global.checkpoints=output/quant_model/best_accuracy Global.save_inference_dir=./output/quant_inference_model
......
deploy/slim/quantization/export_model.py
View file @ 41a1b292
...@@ -76,7 +76,7 @@ def main(): ...@@ -76,7 +76,7 @@ def main():
} }
FLAGS = ArgsParser().parse_args() FLAGS = ArgsParser().parse_args()
config = load_config(FLAGS.config) config = load_config(FLAGS.config)
merge_config(FLAGS.opt) config = merge_config(config, FLAGS.opt)
logger = get_logger() logger = get_logger()
# build post process # build post process
......
doc/doc_ch/algorithm_overview.md
View file @ 41a1b292
...@@ -25,8 +25,8 @@ PaddleOCR开源的文本检测算法列表： ...@@ -25,8 +25,8 @@ PaddleOCR开源的文本检测算法列表：
在ICDAR2015文本检测公开数据集上，算法效果如下： 在ICDAR2015文本检测公开数据集上，算法效果如下：
|模型|骨干网络|precision|recall|Hmean|下载链接| |模型|骨干网络|precision|recall|Hmean|下载链接|
| --- | --- | --- | --- | --- | --- | | --- | --- | --- | --- | --- | --- |
|EAST|ResNet50_vd|85.80%|86.71%|86.25%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)| |EAST|ResNet50_vd|88.71%|81.36%|84.88%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)|
|EAST|MobileNetV3|79.42%|80.64%|80.03%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)| |EAST|MobileNetV3|78.2%|79.1%|78.65%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)|
|DB|ResNet50_vd|86.41%|78.72%|82.38%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)| |DB|ResNet50_vd|86.41%|78.72%|82.38%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)|
|DB|MobileNetV3|77.29%|73.08%|75.12%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar)| |DB|MobileNetV3|77.29%|73.08%|75.12%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar)|
|SAST|ResNet50_vd|91.39%|83.77%|87.42%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)| |SAST|ResNet50_vd|91.39%|83.77%|87.42%|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)|
...@@ -61,18 +61,18 @@ PaddleOCR基于动态图开源的文本识别算法列表： ...@@ -61,18 +61,18 @@ PaddleOCR基于动态图开源的文本识别算法列表：
|模型|骨干网络|Avg Accuracy|模型存储命名|下载链接| |模型|骨干网络|Avg Accuracy|模型存储命名|下载链接|
|---|---|---|---|---| |---|---|---|---|---|
|Rosetta|Resnet34_vd|80.9%|rec_r34_vd_none_none_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar)| |Rosetta|Resnet34_vd|79.11%|rec_r34_vd_none_none_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar)|
|Rosetta|MobileNetV3|78.05%|rec_mv3_none_none_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar)| |Rosetta|MobileNetV3|75.80%|rec_mv3_none_none_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar)|
|CRNN|Resnet34_vd|82.76%|rec_r34_vd_none_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar)| |CRNN|Resnet34_vd|81.04%|rec_r34_vd_none_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar)|
|CRNN|MobileNetV3|79.97%|rec_mv3_none_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar)| |CRNN|MobileNetV3|77.95%|rec_mv3_none_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar)|
|StarNet|Resnet34_vd|84.44%|rec_r34_vd_tps_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar)| |StarNet|Resnet34_vd|82.85%|rec_r34_vd_tps_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar)|
|StarNet|MobileNetV3|81.42%|rec_mv3_tps_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar)| |StarNet|MobileNetV3|79.28%|rec_mv3_tps_bilstm_ctc|[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar)|
|RARE|MobileNetV3|82.5%|rec_mv3_tps_bilstm_att |[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar)| |RARE|Resnet34_vd|83.98%|rec_r34_vd_tps_bilstm_att |[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar)|
|RARE|Resnet34_vd|83.6%|rec_r34_vd_tps_bilstm_att |[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar)| |RARE|MobileNetV3|81.76%|rec_mv3_tps_bilstm_att |[训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar)|
|SRN|Resnet50_vd_fpn| 88.52% | rec_r50fpn_vd_none_srn | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r50_vd_srn_train.tar) | |SRN|Resnet50_vd_fpn| 86.31% | rec_r50fpn_vd_none_srn | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r50_vd_srn_train.tar) |
|NRTR|NRTR_MTB| 84.3% | rec_mtb_nrtr | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar) | |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| 87.2% | rec_r31_sar | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_r31_sar_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| 85.2% | rec_resnet_stn_bilstm_att | [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_resnet_stn_bilstm_att.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) |
<a name="2"></a> <a name="2"></a>
......
doc/doc_ch/android_demo.md
View file @ 41a1b292
...@@ -14,12 +14,12 @@ Demo测试的时候使用的是NDK 20b版本，20版本以上均可以支持编 ...@@ -14,12 +14,12 @@ Demo测试的时候使用的是NDK 20b版本，20版本以上均可以支持编
1. Start a new Android Studio project 1. Start a new Android Studio project
在项目模版中选择 Native C++ 选择PaddleOCR/depoly/android_demo 路径 在项目模版中选择 Native C++ 选择PaddleOCR/deploy/android_demo 路径
进入项目后会自动编译，第一次编译会花费较长的时间，建议添加代理加速下载。 进入项目后会自动编译，第一次编译会花费较长的时间，建议添加代理加速下载。
**代理添加：** **代理添加：**
选择 Android Studio -> Perferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration 选择 Android Studio -> Preferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration
![](../demo/proxy.png) ![](../demo/proxy.png)
......
doc/doc_ch/code_and_doc.md
View file @ 41a1b292
...@@ -16,7 +16,7 @@ PaddleOCR的Python代码遵循 [PEP8规范](https://www.python.org/dev/peps/pep- ...@@ -16,7 +16,7 @@ PaddleOCR的Python代码遵循 [PEP8规范](https://www.python.org/dev/peps/pep-
- 空格 - 空格
- 空格应该加在逗号、分号、冒号前，而非他们的后面 - 空格应该加在逗号、分号、冒号后，而非他们的前面
```python ```python
# 正确： # 正确：
...@@ -334,4 +334,4 @@ git push origin new_branch ...@@ -334,4 +334,4 @@ git push origin new_branch
2）如果评审意见比较多: 2）如果评审意见比较多:
- 请给出总体的修改情况。 - 请给出总体的修改情况。
- 请采用`start a review`进行回复，而非直接回复的方式。原因是每个回复都会发送一封邮件，会造成邮件灾难。 - 请采用`start a review`进行回复，而非直接回复的方式。原因是每个回复都会发送一封邮件，会造成邮件灾难。
\ No newline at end of file
doc/doc_ch/detection.md
View file @ 41a1b292
...@@ -78,11 +78,11 @@ json.dumps编码前的图像标注信息是包含多个字典的list，字典中 ...@@ -78,11 +78,11 @@ json.dumps编码前的图像标注信息是包含多个字典的list，字典中
cd PaddleOCR/ cd PaddleOCR/
# 根据backbone的不同选择下载对应的预训练模型 # 根据backbone的不同选择下载对应的预训练模型
# 下载MobileNetV3的预训练模型 # 下载MobileNetV3的预训练模型
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams
# 或，下载ResNet18_vd的预训练模型 # 或，下载ResNet18_vd的预训练模型
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet18_vd_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet18_vd_pretrained.pdparams
# 或，下载ResNet50_vd的预训练模型 # 或，下载ResNet50_vd的预训练模型
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet50_vd_ssld_pretrained.pdparams
``` ```
<a name="2-----"></a> <a name="2-----"></a>
......
doc/doc_ch/knowledge_distillation.md
View file @ 41a1b292
<a name="0"></a>
# 知识蒸馏 # 知识蒸馏
+ [知识蒸馏](#0)
+ [1. 简介](#1)
- [1.1 知识蒸馏介绍](#11)
- [1.2 PaddleOCR知识蒸馏简介](#12)
+ [2. 配置文件解析](#2)
+ [2.1 识别配置文件解析](#21)
- [2.1.1 模型结构](#211)
- [2.1.2 损失函数](#212)
- [2.1.3 后处理](#213)
- [2.1.4 指标计算](#214)
- [2.1.5 蒸馏模型微调](#215)
+ [2.2 检测配置文件解析](#22)
- [2.2.1 模型结构](#221)
- [2.2.2 损失函数](#222)
- [2.2.3 后处理](#223)
- [2.2.4 蒸馏指标计算](#224)
- [2.2.5 检测蒸馏模型Fine-tune](#225)
<a name="1"></a>
## 1. 简介 ## 1. 简介
<a name="11"></a>
### 1.1 知识蒸馏介绍 ### 1.1 知识蒸馏介绍
近年来，深度神经网络在计算机视觉、自然语言处理等领域被验证是一种极其有效的解决问题的方法。通过构建合适的神经网络，加以训练，最终网络模型的性能指标基本上都会超过传统算法。 近年来，深度神经网络在计算机视觉、自然语言处理等领域被验证是一种极其有效的解决问题的方法。通过构建合适的神经网络，加以训练，最终网络模型的性能指标基本上都会超过传统算法。
...@@ -13,11 +32,12 @@ ...@@ -13,11 +32,12 @@
此外，在知识蒸馏任务中，也衍生出了互学习的模型训练方法，论文[Deep Mutual Learning](https://arxiv.org/abs/1706.00384)中指出，使用两个完全相同的模型在训练的过程中互相监督，可以达到比单个模型训练更好的效果。 此外，在知识蒸馏任务中，也衍生出了互学习的模型训练方法，论文[Deep Mutual Learning](https://arxiv.org/abs/1706.00384)中指出，使用两个完全相同的模型在训练的过程中互相监督，可以达到比单个模型训练更好的效果。
<a name="12"></a>
### 1.2 PaddleOCR知识蒸馏简介 ### 1.2 PaddleOCR知识蒸馏简介
无论是大模型蒸馏小模型，还是小模型之间互相学习，更新参数，他们本质上是都是不同模型之间输出或者特征图(feature map)之间的相互监督，区别仅在于 (1) 模型是否需要固定参数。(2) 模型是否需要加载预训练模型。 无论是大模型蒸馏小模型，还是小模型之间互相学习，更新参数，他们本质上是都是不同模型之间输出或者特征图(feature map)之间的相互监督，区别仅在于 (1) 模型是否需要固定参数。(2) 模型是否需要加载预训练模型。
对于大模型蒸馏小模型的情况，大模型一般需要加载预训练模型并固定参数；对于小模型之间互相蒸馏的情况，小模型一般都不加载预训练模型，参数也都是可学习的状态。 对于大模型蒸馏小模型的情况，大模型一般需要加载预训练模型并固定参数；对于小模型之间互相蒸馏的情况，小模型一般都不加载预训练模型，参数也都是可学习的状态。
在知识蒸馏任务中，不只有2个模型之间进行蒸馏的情况，多个模型之间互相学习的情况也非常普遍。因此在知识蒸馏代码框架中，也有必要支持该种类别的蒸馏方法。 在知识蒸馏任务中，不只有2个模型之间进行蒸馏的情况，多个模型之间互相学习的情况也非常普遍。因此在知识蒸馏代码框架中，也有必要支持该种类别的蒸馏方法。
...@@ -30,17 +50,19 @@ PaddleOCR中集成了知识蒸馏的算法，具体地，有以下几个主要 ...@@ -30,17 +50,19 @@ PaddleOCR中集成了知识蒸馏的算法，具体地，有以下几个主要
通过知识蒸馏，在中英文通用文字识别任务中，不增加任何预测耗时的情况下，可以给模型带来3%以上的精度提升，结合学习率调整策略以及模型结构微调策略，最终提升提升超过5%。 通过知识蒸馏，在中英文通用文字识别任务中，不增加任何预测耗时的情况下，可以给模型带来3%以上的精度提升，结合学习率调整策略以及模型结构微调策略，最终提升提升超过5%。
<a name="2"></a>
## 2. 配置文件解析 ## 2. 配置文件解析
在知识蒸馏训练的过程中，数据预处理、优化器、学习率、全局的一些属性没有任何变化。模型结构、损失函数、后处理、指标计算等模块的配置文件需要进行微调。 在知识蒸馏训练的过程中，数据预处理、优化器、学习率、全局的一些属性没有任何变化。模型结构、损失函数、后处理、指标计算等模块的配置文件需要进行微调。
下面以识别与检测的知识蒸馏配置文件为例，对知识蒸馏的训练与配置进行解析。 下面以识别与检测的知识蒸馏配置文件为例，对知识蒸馏的训练与配置进行解析。
<a name="21"></a>
### 2.1 识别配置文件解析 ### 2.1 识别配置文件解析
配置文件在[ch_PP-OCRv2_rec_distillation.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_distillation.yml)。 配置文件在[ch_PP-OCRv2_rec_distillation.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_distillation.yml)。
<a name="211"></a>
#### 2.1.1 模型结构 #### 2.1.1 模型结构
知识蒸馏任务中，模型结构配置如下所示。 知识蒸馏任务中，模型结构配置如下所示。
...@@ -176,6 +198,7 @@ Architecture: ...@@ -176,6 +198,7 @@ Architecture:
} }
``` ```
<a name="212"></a>
#### 2.1.2 损失函数 #### 2.1.2 损失函数
知识蒸馏任务中，损失函数配置如下所示。 知识蒸馏任务中，损失函数配置如下所示。
...@@ -212,7 +235,7 @@ Loss: ...@@ -212,7 +235,7 @@ Loss:
关于`CombinedLoss`更加具体的实现可以参考: [combined_loss.py](../../ppocr/losses/combined_loss.py#L23)。关于`DistillationCTCLoss`等蒸馏损失函数更加具体的实现可以参考[distillation_loss.py](../../ppocr/losses/distillation_loss.py)。 关于`CombinedLoss`更加具体的实现可以参考: [combined_loss.py](../../ppocr/losses/combined_loss.py#L23)。关于`DistillationCTCLoss`等蒸馏损失函数更加具体的实现可以参考[distillation_loss.py](../../ppocr/losses/distillation_loss.py)。
<a name="213"></a>
#### 2.1.3 后处理 #### 2.1.3 后处理
知识蒸馏任务中，后处理配置如下所示。 知识蒸馏任务中，后处理配置如下所示。
...@@ -228,7 +251,7 @@ PostProcess: ...@@ -228,7 +251,7 @@ PostProcess:
关于`DistillationCTCLabelDecode`更加具体的实现可以参考: [rec_postprocess.py](../../ppocr/postprocess/rec_postprocess.py#L128) 关于`DistillationCTCLabelDecode`更加具体的实现可以参考: [rec_postprocess.py](../../ppocr/postprocess/rec_postprocess.py#L128)
<a name="214"></a>
#### 2.1.4 指标计算 #### 2.1.4 指标计算
知识蒸馏任务中，指标计算配置如下所示。 知识蒸馏任务中，指标计算配置如下所示。
...@@ -245,7 +268,7 @@ Metric: ...@@ -245,7 +268,7 @@ Metric:
关于`DistillationMetric`更加具体的实现可以参考: [distillation_metric.py](../../ppocr/metrics/distillation_metric.py#L24)。 关于`DistillationMetric`更加具体的实现可以参考: [distillation_metric.py](../../ppocr/metrics/distillation_metric.py#L24)。
<a name="215"></a>
#### 2.1.5 蒸馏模型微调 #### 2.1.5 蒸馏模型微调
对蒸馏得到的识别蒸馏进行微调有2种方式。 对蒸馏得到的识别蒸馏进行微调有2种方式。
...@@ -279,15 +302,15 @@ paddle.save(s_params, "ch_PP-OCRv2_rec_train/student.pdparams") ...@@ -279,15 +302,15 @@ paddle.save(s_params, "ch_PP-OCRv2_rec_train/student.pdparams")
转化完成之后，使用[ch_PP-OCRv2_rec.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec.yml)，修改预训练模型的路径（为导出的`student.pdparams`模型路径）以及自己的数据路径，即可进行模型微调。 转化完成之后，使用[ch_PP-OCRv2_rec.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec.yml)，修改预训练模型的路径（为导出的`student.pdparams`模型路径）以及自己的数据路径，即可进行模型微调。
<a name="22"></a>
### 2.2 检测配置文件解析 ### 2.2 检测配置文件解析
检测模型蒸馏的配置文件在PaddleOCR/configs/det/ch_PP-OCRv2/目录下，包含三个蒸馏配置文件： 检测模型蒸馏的配置文件在PaddleOCR/configs/det/ch_PP-OCRv2/目录下，包含三个蒸馏配置文件：
- ch_PP-OCRv2_det_cml.yml，采用cml蒸馏，采用一个大模型蒸馏两个小模型，且两个小模型互相学习的方法 - ch_PP-OCRv2_det_cml.yml，采用cml蒸馏，采用一个大模型蒸馏两个小模型，且两个小模型互相学习的方法
- ch_PP-OCRv2_det_dml.yml，采用DML的蒸馏，两个Student模型互蒸馏的方法 - ch_PP-OCRv2_det_dml.yml，采用DML的蒸馏，两个Student模型互蒸馏的方法
- ch_PP-OCRv2_det_distill.yml，采用Teacher大模型蒸馏小模型Student的方法 - ch_PP-OCRv2_det_distill.yml，采用Teacher大模型蒸馏小模型Student的方法
<a name="221"></a>
#### 2.2.1 模型结构 #### 2.2.1 模型结构
知识蒸馏任务中，模型结构配置如下所示： 知识蒸馏任务中，模型结构配置如下所示：
...@@ -419,7 +442,8 @@ Architecture: ...@@ -419,7 +442,8 @@ Architecture:
} }
``` ```
#### 2.1.2 损失函数 <a name="222"></a>
#### 2.2.2 损失函数
知识蒸馏任务中，检测ch_PP-OCRv2_det_distill.yml蒸馏损失函数配置如下所示。 知识蒸馏任务中，检测ch_PP-OCRv2_det_distill.yml蒸馏损失函数配置如下所示。
...@@ -484,8 +508,8 @@ Loss: ...@@ -484,8 +508,8 @@ Loss:
关于`DistillationDilaDBLoss`更加具体的实现可以参考: [distillation_loss.py](https://github.com/PaddlePaddle/PaddleOCR/blob/release%2F2.4/ppocr/losses/distillation_loss.py#L185)。关于`DistillationDBLoss`等蒸馏损失函数更加具体的实现可以参考[distillation_loss.py](https://github.com/PaddlePaddle/PaddleOCR/blob/04c44974b13163450dfb6bd2c327863f8a194b3c/ppocr/losses/distillation_loss.py?_pjax=%23js-repo-pjax-container%2C%20div%5Bitemtype%3D%22http%3A%2F%2Fschema.org%2FSoftwareSourceCode%22%5D%20main%2C%20%5Bdata-pjax-container%5D#L148)。 关于`DistillationDilaDBLoss`更加具体的实现可以参考: [distillation_loss.py](https://github.com/PaddlePaddle/PaddleOCR/blob/release%2F2.4/ppocr/losses/distillation_loss.py#L185)。关于`DistillationDBLoss`等蒸馏损失函数更加具体的实现可以参考[distillation_loss.py](https://github.com/PaddlePaddle/PaddleOCR/blob/04c44974b13163450dfb6bd2c327863f8a194b3c/ppocr/losses/distillation_loss.py?_pjax=%23js-repo-pjax-container%2C%20div%5Bitemtype%3D%22http%3A%2F%2Fschema.org%2FSoftwareSourceCode%22%5D%20main%2C%20%5Bdata-pjax-container%5D#L148)。
<a name="223"></a>
#### 2.1.3 后处理 #### 2.2.3 后处理
知识蒸馏任务中，检测蒸馏后处理配置如下所示。 知识蒸馏任务中，检测蒸馏后处理配置如下所示。
...@@ -503,8 +527,8 @@ PostProcess: ...@@ -503,8 +527,8 @@ PostProcess:
关于`DistillationDBPostProcess`更加具体的实现可以参考: [db_postprocess.py](../../ppocr/postprocess/db_postprocess.py#L195) 关于`DistillationDBPostProcess`更加具体的实现可以参考: [db_postprocess.py](../../ppocr/postprocess/db_postprocess.py#L195)
<a name="224"></a>
#### 2.1.4 蒸馏指标计算 #### 2.2.4 蒸馏指标计算
知识蒸馏任务中，检测蒸馏指标计算配置如下所示。 知识蒸馏任务中，检测蒸馏指标计算配置如下所示。
...@@ -518,15 +542,15 @@ Metric: ...@@ -518,15 +542,15 @@ Metric:
由于蒸馏需要包含多个网络，甚至多个Student网络，在计算指标的时候只需要计算一个Student网络的指标即可，`key`字段设置为`Student`则表示只计算`Student`网络的精度。 由于蒸馏需要包含多个网络，甚至多个Student网络，在计算指标的时候只需要计算一个Student网络的指标即可，`key`字段设置为`Student`则表示只计算`Student`网络的精度。
<a name="225"></a>
#### 2.1.5 检测蒸馏模型finetune #### 2.2.5 检测蒸馏模型finetune
检测蒸馏有三种方式： 检测蒸馏有三种方式：
- 采用ch_PP-OCRv2_det_distill.yml，Teacher模型设置为PaddleOCR提供的模型或者您训练好的大模型 - 采用ch_PP-OCRv2_det_distill.yml，Teacher模型设置为PaddleOCR提供的模型或者您训练好的大模型
- 采用ch_PP-OCRv2_det_cml.yml，采用cml蒸馏，同样Teacher模型设置为PaddleOCR提供的模型或者您训练好的大模型 - 采用ch_PP-OCRv2_det_cml.yml，采用cml蒸馏，同样Teacher模型设置为PaddleOCR提供的模型或者您训练好的大模型
- 采用ch_PP-OCRv2_det_dml.yml，采用DML的蒸馏，两个Student模型互蒸馏的方法，在PaddleOCR采用的数据集上大约有1.7%的精度提升。 - 采用ch_PP-OCRv2_det_dml.yml，采用DML的蒸馏，两个Student模型互蒸馏的方法，在PaddleOCR采用的数据集上大约有1.7%的精度提升。
在具体finetune时，需要在网络结构的`pretrained`参数中设置要加载的预训练模型。 在具体fine-tune时，需要在网络结构的`pretrained`参数中设置要加载的预训练模型。
在精度提升方面，cml的精度>dml的精度>distill蒸馏方法的精度。当数据量不足或者Teacher模型精度与Student精度相差不大的时候，这个结论或许会改变。 在精度提升方面，cml的精度>dml的精度>distill蒸馏方法的精度。当数据量不足或者Teacher模型精度与Student精度相差不大的时候，这个结论或许会改变。
......
doc/doc_ch/recognition.md
View file @ 41a1b292
...@@ -63,6 +63,17 @@ train_data/rec/train/word_002.jpg 用科技让复杂的世界更简单 ...@@ -63,6 +63,17 @@ train_data/rec/train/word_002.jpg 用科技让复杂的世界更简单
| ... | ...
``` ```
除上述单张图像为一行格式之外，PaddleOCR也支持对离线增广后的数据进行训练，为了防止相同样本在同一个batch中被多次采样，我们可以将相同标签对应的图片路径写在一行中，以列表的形式给出，在训练中，PaddleOCR会随机选择列表中的一张图片进行训练。对应地，标注文件的格式如下。
```
["11.jpg", "12.jpg"] 简单可依赖
["21.jpg", "22.jpg", "23.jpg"] 用科技让复杂的世界更简单
3.jpg ocr
```
上述示例标注文件中，"11.jpg"和"12.jpg"的标签相同，都是`简单可依赖`，在训练的时候，对于该行标注，会随机选择其中的一张图片进行训练。
- 测试集 - 测试集
同训练集类似，测试集也需要提供一个包含所有图片的文件夹（test）和一个rec_gt_test.txt，测试集的结构如下所示： 同训练集类似，测试集也需要提供一个包含所有图片的文件夹（test）和一个rec_gt_test.txt，测试集的结构如下所示：
......
doc/doc_ch/thirdparty.md
View file @ 41a1b292
...@@ -60,9 +60,9 @@ PaddleOCR非常欢迎社区贡献以PaddleOCR为核心的各种服务、部署 ...@@ -60,9 +60,9 @@ PaddleOCR非常欢迎社区贡献以PaddleOCR为核心的各种服务、部署
如果您在使用PaddleOCR时遇到了代码bug、功能不符合预期等问题，可以为PaddleOCR贡献您的修改，其中： 如果您在使用PaddleOCR时遇到了代码bug、功能不符合预期等问题，可以为PaddleOCR贡献您的修改，其中：
- Python代码规范可参考[附录1：Python代码规范](./code_and_doc.md/#附录1)。 - Python代码规范可参考[附录1：Python代码规范](./code_and_doc.md#附录1)。
- 提交代码前请再三确认不会引入新的bug，并在PR中描述优化点。如果该PR解决了某个issue，请在PR中连接到该issue。所有的PR都应该遵守附录3中的[3.2.10 提交代码的一些约定。](./code_and_doc.md/#提交代码的一些约定) - 提交代码前请再三确认不会引入新的bug，并在PR中描述优化点。如果该PR解决了某个issue，请在PR中连接到该issue。所有的PR都应该遵守附录3中的[3.2.10 提交代码的一些约定。](./code_and_doc.md#提交代码的一些约定)
- 请在提交之前参考下方的[附录3：Pull Request说明](./code_and_doc.md#附录3)。如果您对git的提交流程不熟悉，同样可以参考附录3的3.2节。 - 请在提交之前参考下方的[附录3：Pull Request说明](./code_and_doc.md#附录3)。如果您对git的提交流程不熟悉，同样可以参考附录3的3.2节。
...@@ -70,7 +70,7 @@ PaddleOCR非常欢迎社区贡献以PaddleOCR为核心的各种服务、部署 ...@@ -70,7 +70,7 @@ PaddleOCR非常欢迎社区贡献以PaddleOCR为核心的各种服务、部署
### 2.3 文档优化 ### 2.3 文档优化
如果您在使用PaddleOCR时遇到了文档表述不清楚、描述缺失、链接失效等问题，可以为PaddleOCR贡献您的修改。文档书写规范请参考[附录2：文档规范](./code_and_doc.md/#附录2)。**最后请在PR的题目中加上标签`【third-party】` , 在说明中@Evezerest，拥有此标签的PR将会被高优处理。** 如果您在使用PaddleOCR时遇到了文档表述不清楚、描述缺失、链接失效等问题，可以为PaddleOCR贡献您的修改。文档书写规范请参考[附录2：文档规范](./code_and_doc.md#附录2)。**最后请在PR的题目中加上标签`【third-party】` , 在说明中@Evezerest，拥有此标签的PR将会被高优处理。**
## 3. 更多贡献机会 ## 3. 更多贡献机会
......
doc/doc_ch/update.md
View file @ 41a1b292
...@@ -9,7 +9,7 @@ ...@@ -9,7 +9,7 @@
- 2020.12.07 [FAQ](../../doc/doc_ch/FAQ.md)新增5个高频问题，总数124个，并且计划以后每周一都会更新，欢迎大家持续关注。 - 2020.12.07 [FAQ](../../doc/doc_ch/FAQ.md)新增5个高频问题，总数124个，并且计划以后每周一都会更新，欢迎大家持续关注。
- 2020.11.25 更新半自动标注工具[PPOCRLabel](../../PPOCRLabel/README_ch.md)，辅助开发者高效完成标注任务，输出格式与PP-OCR训练任务完美衔接。 - 2020.11.25 更新半自动标注工具[PPOCRLabel](../../PPOCRLabel/README_ch.md)，辅助开发者高效完成标注任务，输出格式与PP-OCR训练任务完美衔接。
- 2020.9.22 更新PP-OCR技术文章，https://arxiv.org/abs/2009.09941 - 2020.9.22 更新PP-OCR技术文章，https://arxiv.org/abs/2009.09941
- 2020.9.19 更新超轻量压缩ppocr_mobile_slim系列模型，整体模型3.5M(详见PP-OCR Pipline)，适合在移动端部署使用。 - 2020.9.19 更新超轻量压缩ppocr_mobile_slim系列模型，整体模型3.5M(详见PP-OCR Pipeline)，适合在移动端部署使用。
- 2020.9.17 更新超轻量ppocr_mobile系列和通用ppocr_server系列中英文ocr模型，媲美商业效果。 - 2020.9.17 更新超轻量ppocr_mobile系列和通用ppocr_server系列中英文ocr模型，媲美商业效果。
- 2020.9.17 更新[英文识别模型](./models_list.md#english-recognition-model)和[多语种识别模型](./models_list.md#english-recognition-model)，已支持`德语、法语、日语、韩语`，更多语种识别模型将持续更新。 - 2020.9.17 更新[英文识别模型](./models_list.md#english-recognition-model)和[多语种识别模型](./models_list.md#english-recognition-model)，已支持`德语、法语、日语、韩语`，更多语种识别模型将持续更新。
- 2020.8.26 更新OCR相关的84个常见问题及解答，具体参考[FAQ](./FAQ.md) - 2020.8.26 更新OCR相关的84个常见问题及解答，具体参考[FAQ](./FAQ.md)
......
doc/doc_en/FAQ_en.md
View file @ 41a1b292
## FAQ ## FAQ
1. **Prediction error: got an unexpected keyword argument 'gradient_clip'** 1. **Prediction error: got an unexpected keyword argument 'gradient_clip'**
The installed version of paddle is incorrect. Currently, this project only supports paddle1.7, which will be adapted to 1.8 in the near future. The installed version of paddle is incorrect. Currently, this project only supports Paddle 1.7, which will be adapted to 1.8 in the near future.
2. **Error when converting attention recognition model: KeyError: 'predict'** 2. **Error when converting attention recognition model: KeyError: 'predict'**
Solved. Please update to the latest version of the code. Solved. Please update to the latest version of the code.
...@@ -31,7 +31,7 @@ At present, PaddleOCR has opensourced two Chinese models, namely 8.6M ultra-ligh ...@@ -31,7 +31,7 @@ At present, PaddleOCR has opensourced two Chinese models, namely 8.6M ultra-ligh
|General Chinese OCR model|Resnet50_vd+Resnet34_vd|det_r50_vd_db.yml|rec_chinese_common_train.yml| |General Chinese OCR model|Resnet50_vd+Resnet34_vd|det_r50_vd_db.yml|rec_chinese_common_train.yml|
8. **Is there a plan to opensource a model that only recognizes numbers or only English + numbers?** 8. **Is there a plan to opensource a model that only recognizes numbers or only English + numbers?**
It is not planned to opensource numbers only, numbers + English only, or other vertical text models. Paddleocr has opensourced a variety of detection and recognition algorithms for customized training. The two Chinese models are also based on the training output of the open-source algorithm library. You can prepare the data according to the tutorial, choose the appropriate configuration file, train yourselves, and we believe that you can get good result. If you have any questions during the training, you are welcome to open issues or ask in the communication group. We will answer them in time. It is not planned to opensource numbers only, numbers + English only, or other vertical text models. PaddleOCR has opensourced a variety of detection and recognition algorithms for customized training. The two Chinese models are also based on the training output of the open-source algorithm library. You can prepare the data according to the tutorial, choose the appropriate configuration file, train yourselves, and we believe that you can get good result. If you have any questions during the training, you are welcome to open issues or ask in the communication group. We will answer them in time.
9. **What is the training data used by the open-source model? Can it be opensourced?** 9. **What is the training data used by the open-source model? Can it be opensourced?**
At present, the open source model, dataset and magnitude are as follows: At present, the open source model, dataset and magnitude are as follows:
...@@ -46,11 +46,11 @@ At present, the open source model, dataset and magnitude are as follows: ...@@ -46,11 +46,11 @@ At present, the open source model, dataset and magnitude are as follows:
10. **Error in using the model with TPS module for prediction** 10. **Error in using the model with TPS module for prediction**
Error message: Input(X) dims[3] and Input(Grid) dims[2] should be equal, but received X dimension[3]\(108) != Grid dimension[2]\(100) Error message: Input(X) dims[3] and Input(Grid) dims[2] should be equal, but received X dimension[3]\(108) != Grid dimension[2]\(100)
Solution：TPS does not support variable shape. Please set --rec_image_shape='3,32,100' and --rec_char_type='en' Solution: TPS does not support variable shape. Please set --rec_image_shape='3,32,100' and --rec_char_type='en'
11. **Custom dictionary used during training, the recognition results show that words do not appear in the dictionary** 11. **Custom dictionary used during training, the recognition results show that words do not appear in the dictionary**
The used custom dictionary path is not set when making prediction. The solution is setting parameter `rec_char_dict_path` to the corresponding dictionary file. The used custom dictionary path is not set when making prediction. The solution is setting parameter `rec_char_dict_path` to the corresponding dictionary file.
12. **Results of cpp_infer and python_inference are very different** 12. **Results of cpp_infer and python_inference are very different**
Versions of exprted inference model and inference libraray should be same. For example, on Windows platform, version of the inference libraray that PaddlePaddle provides is 1.8, but version of the inference model that PaddleOCR provides is 1.7, you should export model yourself(`tools/export_model.py`) on PaddlePaddle1.8 and then use the exported model for inference. Versions of exported inference model and inference library should be same. For example, on Windows platform, version of the inference library that PaddlePaddle provides is 1.8, but version of the inference model that PaddleOCR provides is 1.7, you should export model yourself(`tools/export_model.py`) on PaddlePaddle 1.8 and then use the exported model for inference.
doc/doc_en/algorithm_overview_en.md
View file @ 41a1b292
...@@ -30,8 +30,8 @@ On the ICDAR2015 dataset, the text detection result is as follows: ...@@ -30,8 +30,8 @@ On the ICDAR2015 dataset, the text detection result is as follows:
|Model|Backbone|Precision|Recall|Hmean|Download link| |Model|Backbone|Precision|Recall|Hmean|Download link|
| --- | --- | --- | --- | --- | --- | | --- | --- | --- | --- | --- | --- |
|EAST|ResNet50_vd|85.80%|86.71%|86.25%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)| |EAST|ResNet50_vd|88.71%|81.36%|84.88%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)|
|EAST|MobileNetV3|79.42%|80.64%|80.03%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)| |EAST|MobileNetV3|78.2%|79.1%|78.65%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)|
|DB|ResNet50_vd|86.41%|78.72%|82.38%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)| |DB|ResNet50_vd|86.41%|78.72%|82.38%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)|
|DB|MobileNetV3|77.29%|73.08%|75.12%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar)| |DB|MobileNetV3|77.29%|73.08%|75.12%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar)|
|SAST|ResNet50_vd|91.39%|83.77%|87.42%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)| |SAST|ResNet50_vd|91.39%|83.77%|87.42%|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar)|
...@@ -67,20 +67,20 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r ...@@ -67,20 +67,20 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
|Model|Backbone|Avg Accuracy|Module combination|Download link| |Model|Backbone|Avg Accuracy|Module combination|Download link|
|---|---|---|---|---| |---|---|---|---|---|
|Rosetta|Resnet34_vd|80.9%|rec_r34_vd_none_none_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar)| |Rosetta|Resnet34_vd|79.11%|rec_r34_vd_none_none_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar)|
|Rosetta|MobileNetV3|78.05%|rec_mv3_none_none_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar)| |Rosetta|MobileNetV3|75.80%|rec_mv3_none_none_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar)|
|CRNN|Resnet34_vd|82.76%|rec_r34_vd_none_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar)| |CRNN|Resnet34_vd|81.04%|rec_r34_vd_none_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar)|
|CRNN|MobileNetV3|79.97%|rec_mv3_none_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar)| |CRNN|MobileNetV3|77.95%|rec_mv3_none_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar)|
|StarNet|Resnet34_vd|84.44%|rec_r34_vd_tps_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar)| |StarNet|Resnet34_vd|82.85%|rec_r34_vd_tps_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar)|
|StarNet|MobileNetV3|81.42%|rec_mv3_tps_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar)| |StarNet|MobileNetV3|79.28%|rec_mv3_tps_bilstm_ctc|[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar)|
|RARE|MobileNetV3|82.5%|rec_mv3_tps_bilstm_att |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar)| |RARE|Resnet34_vd|83.98%|rec_r34_vd_tps_bilstm_att |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar)|
|RARE|Resnet34_vd|83.6%|rec_r34_vd_tps_bilstm_att |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar)| |RARE|MobileNetV3|81.76%|rec_mv3_tps_bilstm_att |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar)|
|SRN|Resnet50_vd_fpn| 88.52% | rec_r50fpn_vd_none_srn |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r50_vd_srn_train.tar)| |SRN|Resnet50_vd_fpn| 86.31% | rec_r50fpn_vd_none_srn |[trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r50_vd_srn_train.tar)|
|NRTR|NRTR_MTB| 84.3% | rec_mtb_nrtr | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar) | |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| 87.2% | rec_r31_sar | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_r31_sar_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| 85.2% | rec_resnet_stn_bilstm_att | [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/rec/rec_resnet_stn_bilstm_att.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) |
Please refer to the document for training guide and use of PaddleOCR Please refer to the document for training guide and use of PaddleOCR
## 2. Training ## 2. Training
......
doc/doc_en/android_demo_en.md
View file @ 41a1b292
...@@ -20,7 +20,7 @@ File -> New ->New Project to create "Native C++" project ...@@ -20,7 +20,7 @@ File -> New ->New Project to create "Native C++" project
**Agent add:** **Agent add:**
Android Studio -> Perferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration Android Studio -> Preferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration
![](../demo/proxy.png) ![](../demo/proxy.png)
......
doc/doc_en/angle_class_en.md
View file @ 41a1b292
...@@ -92,7 +92,7 @@ python3 -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c ...@@ -92,7 +92,7 @@ python3 -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c
PaddleOCR provides a variety of data augmentation methods. If you want to add disturbance during training, Please uncomment the `RecAug` and `RandAugment` fields under `Train.dataset.transforms` in the configuration file. PaddleOCR provides a variety of data augmentation methods. If you want to add disturbance during training, Please uncomment the `RecAug` and `RandAugment` fields under `Train.dataset.transforms` in the configuration file.
The default perturbation methods are: cvtColor, blur, jitter, Gasuss noise, random crop, perspective, color reverse, RandAugment. The default perturbation methods are: cvtColor, blur, jitter, Gauss noise, random crop, perspective, color reverse, RandAugment.
Except for RandAugment, each disturbance method is selected with a 50% probability during the training process. For specific code implementation, please refer to: Except for RandAugment, each disturbance method is selected with a 50% probability during the training process. For specific code implementation, please refer to:
[rec_img_aug.py](../../ppocr/data/imaug/rec_img_aug.py) [rec_img_aug.py](../../ppocr/data/imaug/rec_img_aug.py)
......
doc/doc_en/code_and_doc.md 0 → 100644
View file @ 41a1b292
- Appendix
This appendix contains python, document specifications and Pull Request process. Please follow the relevant contents
- [Appendix 1：Python Code Specification](#Appendix1)
- [Appendix 2：Document Specification](#Appendix2)
- [Appendix 3：Pull Request Description](#Appendix3)
<a name="Appendix1"></a>
## Appendix 1：Python Code Specification
The Python code of PaddleOCR follows [PEP8 Specification]( https://www.python.org/dev/peps/pep-0008/ ), some of the key concerns include the following
- Space
- Spaces should be added after commas, semicolons, colons, not before them
```python
# true:
print(x, y)
# false:
print(x , y)
```
- When specifying a keyword parameter or default parameter value in a function, do not use spaces on both sides of it
```python
# true:
def complex(real, imag=0.0)
# false:
def complex(real, imag = 0.0)
```
- comment
- Inline comments: inline comments are indicated by the` # `sign. Two spaces should be left between code and` # `, and one space should be left between` # `and comments, for example
```python
x = x + 1 # Compensate for border
```
- Functions and methods: The definition of each function should include the following:
- Function description: Utility, input and output of function
- Args: Name and description of each parameter
- Returns: The meaning and type of the return value
```python
def fetch_bigtable_rows(big_table, keys, other_silly_variable=None):
"""Fetches rows from a Bigtable.
Retrieves rows pertaining to the given keys from the Table instance
represented by big_table. Silly things may happen if
other_silly_variable is not None.
Args:
big_table: An open Bigtable Table instance.
keys: A sequence of strings representing the key of each table row
to fetch.
other_silly_variable: Another optional variable, that has a much
longer name than the other args, and which does nothing.
Returns:
A dict mapping keys to the corresponding table row data
fetched. Each row is represented as a tuple of strings. For
example:
{'Serak': ('Rigel VII', 'Preparer'),
'Zim': ('Irk', 'Invader'),
'Lrrr': ('Omicron Persei 8', 'Emperor')}
If a key from the keys argument is missing from the dictionary,
then that row was not found in the table.
"""
pass
```
<a name="Appendix2"></a>
## Appendix 2: Document Specification
### 2.1 Overall Description
- Document Location: If you add new features to your original Markdown file, please **Do not re-create** a new file. If you don't know where to add it, you can first PR the code and then ask the official in commit.
- New Markdown Document Name: Describe the content of the document in English, typically a combination of lowercase letters and underscores, such as `add_New_Algorithm.md`
- New Markdown Document Format: Catalog - Body - FAQ
> The directory generation method can use [this site](https://ecotrust-canada.github.io/markdown-toc/ ) Automatically extract directories after copying MD contents, and then add `<a name='XXXX'></a> before each heading of the MD file
- English and Chinese: Any changes or additions to the document need to be made in both Chinese and English documents.
### 2.2 Format Specification
- Title format: The document title format follows the format of: Arabic decimal point combination-space-title (for example, `2.1 XXXX`, `2.XXXX`)
- Code block: Displays code in code block format that needs to be run, describing the meaning of command parameters before the code block. for example:
> Pipeline of detection + direction Classify + recognition: Vertical text can be recognized after set direction classifier parameters`--use_angle_cls true`.
>
> ```
> paddleocr --image_dir ./imgs/11.jpg --use_angle_cls true
> ```
- Variable Rrferences: If code variables or command parameters are referenced in line, they need to be represented in line code, for example, above `--use_angle_cls true` with one space in front and one space in back
- Uniform naming: e.g. PP-OCRv2, PP-OCR mobile, `paddleocr` whl package, PPOCRLabel, Paddle Lite, etc.
- Supplementary notes: Supplementary notes by reference format `>`.
- Picture: If a picture is added to the description document, specify the naming of the picture (describing its content) and add the picture under `doc/`.
- Title: Capitalize the first letter of each word in the title.
<a name="Appendix3"></a>
## Appendix 3: Pull Request Description
### 3.1 PaddleOCR Branch Description
PaddleOCR will maintain two branches in the future, one for each:
- release/x.x family branch: stable release version branch, also the default branch. PaddleOCR releases a new release branch based on feature updates and adapts to the release version of Paddle. As versions iterate, more and more release/x.x family branches are maintained by default with the latest version of the release branch.
- dygraph branch: For the development branch, adapts the dygraph version of the Paddle dynamic graph to primarily develop new functionality. If you need to redevelop, choose the dygraph branch. To ensure that the dygraph branch pulls out the release/x.x branch when needed, the code for the dygraph branch can only use the valid API in the latest release branch of Paddle. That is, if a new API has been developed in the Paddle dygraph branch but has not yet appeared in the release branch code, do not use it in Paddle OCR. In addition, performance optimization, parameter tuning, policy updates that do not involve API can be developed normally.
The historical branch of PaddleOCR will no longer be maintained in the future. These branches will continue to be maintained, considering that some of you may still be using them:
- Develop branch: This branch was used for the development and testing of static diagrams and is currently compatible with version >=1.7. If you have special needs, you can also use this branch to accommodate older versions of Paddle, but you won't update your code until you fix the bug.
PaddleOCR welcomes you to actively contribute code to repo. Here are some basic processes for contributing code.
### 3.2 PaddleOCR Code Submission Process And Specification
> If you are familiar with Git use, you can jump directly to [Some Conventions For Submitting Code in 3.2.10](#Some_conventions_for_submitting_code)
#### 3.2.1 Create Your `Remote Repo`
- In PaddleOCR [GitHub Home]( https://github.com/PaddlePaddle/PaddleOCR ) Click the `Fork` button in the upper left corner to create a `remote repo`in your personal directory, such as ` https://github.com/ {your_name}/PaddleOCR`.
![banner](../banner.png)
- Clone `Remote repo`
```
# pull code of develop branch
git clone https://github.com/{your_name}/PaddleOCR.git -b dygraph
cd PaddleOCR
```
> Clone failures are mostly due to network reasons, try again later or configure the proxy
#### 3.2.2 Login And Connect Using Token
Start by viewing the information for the current `remote repo`.
```
git remote -v
# origin https://github.com/{your_name}/PaddleOCR.git (fetch)
# origin https://github.com/{your_name}/PaddleOCR.git (push)
```
Only the information of the clone `remote repo`, i.e. the PaddleOCR under your username, is available. Due to the change in Github's login method, you need to reconfigure the `remote repo` address by means of a Token. The token is generated as follows:
1. Find Personal Access Tokens: Click on your avatar in the upper right corner of the Github page and choose Settings --> Developer settings --> Personal access tokens,
2. Click Generate new token: Fill in the token name in Note, such as 'paddle'. In Select scopes, select repo (required), admin:repo_hook, delete_repo, etc. You can check them according to your needs. Then click Generate token to generate the token, and finally copy the generated token.
Delete the original origin configuration
```
git remote rm origin
```
Change the remote branch to `https://oauth2:{token}@github.com/{your_name}/PaddleOCR.git`. For example, if the token value is 12345 and your user name is PPOCR, run the following command
```
git remote add origin https://oauth2:12345@github.com/PPOCR/PaddleOCR.git
```
This establishes a connection to our own `remote repo`. Next we create a remote host of the original PaddleOCR repo, named upstream.
```
git remote add upstream https://github.com/PaddlePaddle/PaddleOCR.git
```
Use `git remote -v` to view current `remote warehouse` information, output as follows, found to include two origin and two upstream of `remote repo` .
```
origin https://github.com/{your_name}/PaddleOCR.git (fetch)
origin https://github.com/{your_name}/PaddleOCR.git (push)
upstream https://github.com/PaddlePaddle/PaddleOCR.git (fetch)
upstream https://github.com/PaddlePaddle/PaddleOCR.git (push)
```
This is mainly to keep the local repository up to date when subsequent pull request (PR) submissions are made.
#### 3.2.3 Create Local Branch
First get the latest code of upstream, then create a new_branch branch based on the dygraph of the upstream repo (upstream).
```
git fetch upstream
git checkout -b new_branch upstream/dygraph
```
> If for a newly forked PaddleOCR project, the user's remote repo (origin) has the same branch updates as the upstream repository (upstream), you can also create a new local branch based on the default branch of the origin repo or a specified branch with the following command
>
> ```
> # Create new_branch branch on user remote repo (origin) based on develop branch
> git checkout -b new_branch origin/develop
> # Create new_branch branch based on upstream remote repo develop branch
> # If you need to create a new branch from upstream,
> # you need to first use git fetch upstream to get upstream code
> git checkout -b new_branch upstream/develop
> ```
The final switch to the new branch is displayed with the following output information.
```
Branch new_branch set up to track remote branch develop from upstream.
Switched to a new branch 'new_branch'
```
After switching branches, file changes can be made on this branch
#### 3.2.4 Use Pre-Commit Hook
Paddle developers use the pre-commit tool to manage Git pre-submit hooks. It helps us format the source code (C++, Python) and automatically check for basic things (such as having only one EOL per file, not adding large files to Git) before committing it.
The pre-commit test is part of the unit test in Travis-CI. PR that does not satisfy the hook cannot be submitted to PaddleOCR. Install it first and run it in the current directory：
```
pip install pre-commit
pre-commit install
```
> 1. Paddle uses clang-format to adjust the C/C++ source code format. Make sure the `clang-format` version is above 3.8.
>
> 2. Yapf installed through pip install pre-commit is slightly different from conda install-c conda-forge pre-commit, and PaddleOCR developers use `pip install pre-commit`.
#### 3.2.5 Modify And Submit Code
If you make some changes on `README.Md ` on PaddleOCR, you can view the changed file through `git status`, and then add the changed file using `git add`。
```
git status # View change files
git add README.md
pre-commit
```
Repeat these steps until the pre-comit format check does not error. As shown below.
![img](../precommit_pass.png)
Use the following command to complete the submission.
```
git commit -m "your commit info"
```
#### 3.2.6 Keep Local Repo Up To Date
Get the latest code for upstream and update the current branch. Here the upstream comes from section 2.2, `Connecting to a remote repo`.
```
git fetch upstream
# If you want to commit to another branch, you need to pull code from another branch of upstream, here is develop
git pull upstream develop
```
#### 3.2.7 Push To Remote Repo
```
git push origin new_branch
```
#### 3.2.7 Submit Pull Request
Click the new pull request to select the local branch and the target branch, as shown in the following figure. In the description of PR, fill in the functions completed by the PR. Next, wait for review, and if you need to modify something, update the corresponding branch in origin with the steps above.
![banner](../pr.png)
#### 3.2.8 Sign CLA Agreement And Pass Unit Tests
- Signing the CLA When submitting a Pull Request to PaddlePaddle for the first time, you need to sign a CLA (Contributor License Agreement) agreement to ensure that your code can be incorporated as follows:
1. Please check the Check section in PR, find the license/cla, and click on the right detail to enter the CLA website
2. Click Sign in with GitHub to agree on the CLA website and when clicked, it will jump back to your Pull Request page
#### 3.2.9 Delete Branch
- Remove remote branch
After PR is merged into the main repo, we can delete the branch of the remote repofrom the PR page.
You can also use `git push origin:branch name` to delete remote branches, such as:
```
git push origin :new_branch
```
- Delete local branch
```
# Switch to the development branch, otherwise the current branch cannot be deleted
git checkout develop
# Delete new_ Branch Branch
git branch -D new_branch
```
<a name="Some_conventions_for_submitting_code"></a>
#### 3.2.10 Some Conventions For Submitting Code
In order for official maintainers to better focus on the code itself when reviewing it, please follow the following conventions each time you submit your code:
1）Please ensure that the unit tests in Travis-CI pass smoothly. If not, indicate that there is a problem with the submitted code, and the official maintainer generally does not review it.
2）Before submitting a Pull Request.
- Note the number of commits.
Reason: If you only modify one file and submit more than a dozen commits, each commit will only make a few modifications, which can be very confusing to the reviewer. The reviewer needs to look at each commit individually to see what changes have been made, and does not exclude the fact that changes between commits overlap each other.
Suggestion: Keep as few commits as possible each time you submit, and supplement your last commit with git commit --amend. For multiple commits that have been Push to a remote warehouse, you can refer to [squash commits after push](https://stackoverflow.com/questions/5667884/how-to-squash-commits-in-git-after-they-have-been-pushed ).
- Note the name of each commit: it should reflect the content of the current commit, not be too arbitrary.
3） If you have solved a problem, add in the first comment box of the Pull Request:fix #issue_number，This will automatically close the corresponding Issue when the Pull Request is merged. Key words include:close, closes, closed, fix, fixes, fixed, resolve, resolves, resolved,please choose the right vocabulary. Detailed reference [Closing issues via commit messages](https://help.github.com/articles/closing-issues-via-commit-messages).
In addition, in response to the reviewer's comments, you are requested to abide by the following conventions:
1） Each review comment from an official maintainer would like a response, which would better enhance the contribution of the open source community.
- If you agree to the review opinion and modify it accordingly, give a simple Done.
- If you disagree with the review, please give your own reasons for refuting.
2）If there are many reviews:
- Please give an overview of the changes.
- Please reply with `start a review', not directly. The reason is that each reply sends an e-mail message, which can cause a mail disaster.
doc/doc_en/community_contribution_en.md 0 → 100644
View file @ 41a1b292
# COMMUNITY CONTRIBUTION
Thank you for your support and interest in PaddleOCR. The goal of PaddleOCR is to build a professional, harmonious and supportive open source community with developers. This document presents existing community contributions, explanations for various contributions, and new opportunities and processes to make the contribution process more efficient and clear.
PaddleOCR wants to help any developer with a dream realize their vision and enjoy the joy of creating value through the power of AI.
---
<a href="https://github.com/PaddlePaddle/PaddleOCR/graphs/contributors">
<img src="https://contrib.rocks/image?repo=PaddlePaddle/PaddleOCR" />
</a>
> The picture above shows PaddleOCR's current Contributor, updated regularly
## 1. COMMUNITY CONTRIBUTION
### 1.1 PaddleOCR BASED COMMUNITY PROJECT
- 【The lastest】 [FastOCRLabel](https://gitee.com/BaoJianQiang/FastOCRLabel): Complete C# version annotation tool (@ [包建强](https://gitee.com/BaoJianQiang) )
#### 1.1.1 UNIVERSAL TOOL
- [DangoOCR offline version](https://github.com/PantsuDango/DangoOCR)：Universal desktop instant translation tool (@ [PantsuDango](https://github.com/PantsuDango))
- [scr2txt](https://github.com/lstwzd/scr2txt)：Screenshot to Text tool (@ [lstwzd](https://github.com/lstwzd))
- [AI Studio project](https://aistudio.baidu.com/aistudio/projectdetail/1054614?channelType=0&channel=0)：English video automatically generates subtitles( @ [叶月水狐](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/322052))
#### 1.1.2 VERTICAL SCENE TOOLS
- [id_card_ocr](https://github.com/baseli/id_card_ocr)：Identification of copy of ID card(@ [baseli](https://github.com/baseli))
- [Paddle_Table_Image_Reader](https://github.com/thunder95/Paddle_Table_Image_Reader): A data assistant that can read tables and pictures(@ [thunder95](https://github.com/thunder95]))
#### 1.1.3 PRE AND POST PROCESSING
- [paddleOCRCorrectOutputs](https://github.com/yuranusduke/paddleOCRCorrectOutputs)：Get the key-value of OCR recognition result (@ [yuranusduke](https://github.com/yuranusduke))
### 1.2 NEW FEATURES FOR PaddleOCR
- Thanks [authorfu](https://github.com/authorfu) for contributing Android([#340](https://github.com/PaddlePaddle/PaddleOCR/pull/340)) and [xiadeye](https://github.com/xiadeye) for contributing IOS demo code([#325](https://github.com/PaddlePaddle/PaddleOCR/pull/325)).
- Thanks [tangmq](https://gitee.com/tangmq) for adding docker deployment service to PaddleOCR to support quick release of callable restful API services([#507](https://github.com/PaddlePaddle/PaddleOCR/pull/507)).
- Thanks [lijinhan](https://github.com/lijinhan) for adding Java springboot to PaddleOCR and call OCR hubserving interface to complete the use of OCR service deployment([#1027](https://github.com/PaddlePaddle/PaddleOCR/pull/1027)).
- Thanks [Evezerest](https://github.com/Evezerest), [ninetailskim](https://github.com/ninetailskim), [edencfc](https://github.com/edencfc), [BeyondYourself](https://github.com/BeyondYourself), [1084667371](https://github.com/1084667371) for contributing complete code of [PPOCRLabel](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.3/PPOCRLabel/README_ch.md).
### 1.3 CODE AND DOCUMENT OPTIMIZATION
- Thanks [zhangxin](https://github.com/ZhangXinNan)([Blog](https://blog.csdn.net/sdlypyzq)) for contributing new visualization methods and adding .gitgnore, handling the problem of manually setting the PYTHONPATH environment variable([#210](https://github.com/PaddlePaddle/PaddleOCR/pull/210)).
- Thanks [lyl120117](https://github.com/lyl120117) for contributing code to print network structure([#304](https://github.com/PaddlePaddle/PaddleOCR/pull/304)).
- Thanks [BeyondYourself](https://github.com/BeyondYourself) for making a lot of great suggestions for PaddleOCR and simplifying some code styles of paddleocr([so many commits)](https://github.com/PaddlePaddle/PaddleOCR/commits?author=BeyondYourself).
- Thanks [Khanh Tran](https://github.com/xxxpsyduck) and [Karl Horky](https://github.com/karlhorky) for contributing modifing English documents.
### 1.4 MULTILINGUAL CORPUS
- Thanks [xiangyubo](https://github.com/xiangyubo) for contributing handwritting Chinese OCR dataset([#321](https://github.com/PaddlePaddle/PaddleOCR/pull/321)).
- Thanks [Mejans](https://github.com/Mejans) for contributing dictionary and corpus of the new language Occitan to PaddleOCR([#954](https://github.com/PaddlePaddle/PaddleOCR/pull/954)).
## 2. CONTRIBUTION ILLUSTRATING
### 2.1 NEW FUNCTION CLASS
PaddleOCR welcomes community contributions to various services, deployment examples and software applications with paddleOCR as the core. Certified community contributions will be added to the above community contribution table to increase exposure for the majority of developers, which is also the glory of PaddleOCR, including:
- Project form: the project code certified by the official community shall have good specifications and structure, and shall be equipped with a detailed README.md, which describes how to use the project. Through add a line 'paddleocr' to the requirements.txt, which can be automatically included in the usedby of paddleocr.
- Integration method: if it is an update to the existing PaddleOCR tool, it will be integrated into the main repo. If a new function is expanded for paddleocr, please contact the official personnel first to confirm whether the project is integrated into the master repo, *even if the new function is not integrated into the master repo, we will also increase the exposure of your personal project in the way of community contribution.*
### 2.2 CODE OPTIMIZATION
If you encounter code bugs and unexpected functions when using PaddleOCR, you can contribute your modifications to PaddleOCR, including:
- Python code specifications are available for reference [Appendix 1:Python code specifications](./code_and_doc.md/#Appendix1).
- Before submitting the code, please confirm again and again that no new bugs will be introduced, and describe the optimization points in the PR. If the PR solves an issue, please connect to the issue in the PR. All PR shall comply with the requirements in Appendix [3.2.10 Some conventions for submitting code.](./code_and_doc.md/#Some conventions for submitting code)
- Please refer to the below before submitting. If you are not familiar with the git submission process, you can also refer to Section 3.2 of [Appendix 3: description of Pull Request](./code_and_doc.md/#Appendix3).If you are not familiar with the git submission process, you can also refer to Section 3.2 of Appendix 3.
**Finally, please add the label Third Party in the title of PR and @ Everest in the description , PR with this label will be treated with high priority`[third-part]`.**
### 2.3 DOCUMENT OPTIMIZATION
If you encounter problems such as unclear document description, missing description and invalid link when using PaddleOCR, you can contribute your modifications to PaddleOCR. For document writing specifications, please refer to [Appendix 2: document specifications](./code_and_doc.md/#Appendix2). **Finally, please add the label Third Party in the title of PR and @ Everest in the description , PR with this label will be treated with high priority`[third-party].**
## 3. MORE CONTRIBUTION OPPORTUNITIES
We encourage developers to use PaddleOCR to realize their ideas. At the same time, we also list some valuable development directions after analysis, which are collected in the regular season of community projects as a whole.
## 4. CONTACT US
We very much welcome developers to contact us before they intend to contribute code, documents, corpus and other contents to PaddleOCR, which can greatly reduce the communication cost in the PR process. At the same time, if you find some ideas difficult to realize personally, we can also recruit like-minded developers for the project in the form of SIG. Projects funded through SIG channels will receive deep R &amp; D support and operational resources (such as official account publicity, live broadcast lessons, etc.).
Our recommended contribution process is:
- By adding the `[Third Party]` mark in the topic of GitHub issue, explain the problems encountered (and the ideas to solve) or the functions to be expanded, and wait for the reply of the person on duty. For example, ` [Third Party] contributes IOS examples to PaddleOCR`.
- After communicating with us and confirming that the technical scheme or bugs and optimization points are correct, add functions or modify them accordingly, and the codes and documents shall comply with relevant specifications.
- PR links to the above issue and waits for review.
## 5. THANKS AND FOLLOW-UP
- After the code is combined, the information will be updated in the first section of this document. The default link is GitHub name and home page. If you need to change the home page, you can also contact us.
- New important function classes will be advertised in the user group and enjoy the honor of the open source community.
- **If you have a PaddleOCR based project that does not appear in the above list, follow `4. CONTACT US` .**
doc/doc_en/config_en.md
View file @ 41a1b292
# Configuration # Configuration
- [1. Optional Parameter List](#1-optional-parameter-list) - [1. Optional Parameter List](#1-optional-parameter-list)
- [2. Intorduction to Global Parameters of Configuration File](#2-intorduction-to-global-parameters-of-configuration-file) - [2. Introduction to Global Parameters of Configuration File](#2-introduction-to-global-parameters-of-configuration-file)
- [3. Multilingual Config File Generation](#3-multilingual-config-file-generation) - [3. Multilingual Config File Generation](#3-multilingual-config-file-generation)
<a name="1-optional-parameter-list"></a> <a name="1-optional-parameter-list"></a>
...@@ -15,9 +15,9 @@ The following list can be viewed through `--help` ...@@ -15,9 +15,9 @@ The following list can be viewed through `--help`
| -c | ALL | Specify configuration file to use | None | **Please refer to the parameter introduction for configuration file usage** | | -c | ALL | Specify configuration file to use | None | **Please refer to the parameter introduction for configuration file usage** |
| -o | ALL | set configuration options | None | Configuration using -o has higher priority than the configuration file selected with -c. E.g: -o Global.use_gpu=false | | -o | ALL | set configuration options | None | Configuration using -o has higher priority than the configuration file selected with -c. E.g: -o Global.use_gpu=false |
<a name="2-intorduction-to-global-parameters-of-configuration-file"></a> <a name="2-introduction-to-global-parameters-of-configuration-file"></a>
## 2. Intorduction to Global Parameters of Configuration File ## 2. Introduction to Global Parameters of Configuration File
Take rec_chinese_lite_train_v2.0.yml as an example Take rec_chinese_lite_train_v2.0.yml as an example
### Global ### Global
...@@ -30,7 +30,7 @@ Take rec_chinese_lite_train_v2.0.yml as an example ...@@ -30,7 +30,7 @@ Take rec_chinese_lite_train_v2.0.yml as an example
| print_batch_step | Set print log interval | 10 | \ | | print_batch_step | Set print log interval | 10 | \ |
| save_model_dir | Set model save path | output/{算法名称} | \ | | save_model_dir | Set model save path | output/{算法名称} | \ |
| save_epoch_step | Set model save interval | 3 | \ | | save_epoch_step | Set model save interval | 3 | \ |
| eval_batch_step | Set the model evaluation interval | 2000 or [1000, 2000] | runing evaluation every 2000 iters or evaluation is run every 2000 iterations after the 1000th iteration | | eval_batch_step | Set the model evaluation interval | 2000 or [1000, 2000] | running evaluation every 2000 iters or evaluation is run every 2000 iterations after the 1000th iteration |
| cal_metric_during_train | Set whether to evaluate the metric during the training process. At this time, the metric of the model under the current batch is evaluated | true | \ | | cal_metric_during_train | Set whether to evaluate the metric during the training process. At this time, the metric of the model under the current batch is evaluated | true | \ |
| load_static_weights | Set whether the pre-training model is saved in static graph mode (currently only required by the detection algorithm) | true | \ | | load_static_weights | Set whether the pre-training model is saved in static graph mode (currently only required by the detection algorithm) | true | \ |
| pretrained_model | Set the path of the pre-trained model | ./pretrain_models/CRNN/best_accuracy | \ | | pretrained_model | Set the path of the pre-trained model | ./pretrain_models/CRNN/best_accuracy | \ |
...@@ -65,7 +65,7 @@ In PaddleOCR, the network is divided into four stages: Transform, Backbone, Neck ...@@ -65,7 +65,7 @@ In PaddleOCR, the network is divided into four stages: Transform, Backbone, Neck
| Parameter | Use | Defaults | Note | | Parameter | Use | Defaults | Note |
| :---------------------: | :---------------------: | :--------------: | :--------------------: | | :---------------------: | :---------------------: | :--------------: | :--------------------: |
| model_type | Network Type | rec | Currently support`rec`,`det`,`cls` | | model_type | Network Type | rec | Currently support`rec`,`det`,`cls` |
| algorithm | Model name | CRNN | See [algorithm_overview](./algorithm_overview.md) for the support list | | algorithm | Model name | CRNN | See [algorithm_overview](./algorithm_overview_en.md) for the support list |
| **Transform** | Set the transformation method | - | Currently only recognition algorithms are supported, see [ppocr/modeling/transform](../../ppocr/modeling/transform) for details | | **Transform** | Set the transformation method | - | Currently only recognition algorithms are supported, see [ppocr/modeling/transform](../../ppocr/modeling/transform) for details |
| name | Transformation class name | TPS | Currently supports `TPS` | | name | Transformation class name | TPS | Currently supports `TPS` |
| num_fiducial | Number of TPS control points | 20 | Ten on the top and bottom | | num_fiducial | Number of TPS control points | 20 | Ten on the top and bottom |
...@@ -134,14 +134,14 @@ In PaddleOCR, the network is divided into four stages: Transform, Backbone, Neck ...@@ -134,14 +134,14 @@ In PaddleOCR, the network is divided into four stages: Transform, Backbone, Neck
## 3. Multilingual Config File Generation ## 3. Multilingual Config File Generation
PaddleOCR currently supports 80 (except Chinese) language recognition. A multi-language configuration file template is PaddleOCR currently supports recognition for 80 languages (besides Chinese). A multi-language configuration file template is
provided under the path `configs/rec/multi_languages`: [rec_multi_language_lite_train.yml](../../configs/rec/multi_language/rec_multi_language_lite_train.yml)。 provided under the path `configs/rec/multi_languages`: [rec_multi_language_lite_train.yml](../../configs/rec/multi_language/rec_multi_language_lite_train.yml)。
There are two ways to create the required configuration file:： There are two ways to create the required configuration file:
1. Automatically generated by script 1. Automatically generated by script
[generate_multi_language_configs.py](../../configs/rec/multi_language/generate_multi_language_configs.py) Can help you generate configuration files for multi-language models Script [generate_multi_language_configs.py](../../configs/rec/multi_language/generate_multi_language_configs.py) can help you generate configuration files for multi-language models.
- Take Italian as an example, if your data is prepared in the following format: - Take Italian as an example, if your data is prepared in the following format:
``` ```
...@@ -196,21 +196,21 @@ Italian is made up of Latin letters, so after executing the command, you will ge ...@@ -196,21 +196,21 @@ Italian is made up of Latin letters, so after executing the command, you will ge
epoch_num: 500 epoch_num: 500
... ...
character_dict_path: {path/of/dict} # path of dict character_dict_path: {path/of/dict} # path of dict
Train: Train:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: train_data/ # root directory of training data data_dir: train_data/ # root directory of training data
label_file_list: ["./train_data/train_list.txt"] # train label path label_file_list: ["./train_data/train_list.txt"] # train label path
... ...
Eval: Eval:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: train_data/ # root directory of val data data_dir: train_data/ # root directory of val data
label_file_list: ["./train_data/val_list.txt"] # val label path label_file_list: ["./train_data/val_list.txt"] # val label path
... ...
``` ```
......
doc/doc_en/customize_en.md
View file @ 41a1b292
...@@ -22,7 +22,7 @@ For more details about data preparation and training tutorials, refer to the doc ...@@ -22,7 +22,7 @@ For more details about data preparation and training tutorials, refer to the doc
PaddleOCR provides a concatenation tool for detection and recognition models, which can connect any trained detection model and any recognition model into a two-stage text recognition system. The input image goes through four main stages: text detection, text rectification, text recognition, and score filtering to output the text position and recognition results, and at the same time, you can choose to visualize the results. PaddleOCR provides a concatenation tool for detection and recognition models, which can connect any trained detection model and any recognition model into a two-stage text recognition system. The input image goes through four main stages: text detection, text rectification, text recognition, and score filtering to output the text position and recognition results, and at the same time, you can choose to visualize the results.
When performing prediction, you need to specify the path of a single image or a image folder through the parameter `image_dir`, the parameter `det_model_dir` specifies the path of detection model, and the parameter `rec_model_dir` specifies the path of recogniton model. The visualized results are saved to the `./inference_results` folder by default. When performing prediction, you need to specify the path of a single image or a image folder through the parameter `image_dir`, the parameter `det_model_dir` specifies the path of detection model, and the parameter `rec_model_dir` specifies the path of recognition model. The visualized results are saved to the `./inference_results` folder by default.
``` ```
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/" python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"
......
doc/doc_en/detection_en.md
View file @ 41a1b292
...@@ -4,7 +4,7 @@ This section uses the icdar2015 dataset as an example to introduce the training, ...@@ -4,7 +4,7 @@ This section uses the icdar2015 dataset as an example to introduce the training,
- [1. Data and Weights Preparation](#1-data-and-weights-preparatio) - [1. Data and Weights Preparation](#1-data-and-weights-preparatio)
* [1.1 Data Preparation](#11-data-preparation) * [1.1 Data Preparation](#11-data-preparation)
* [1.2 Download Pretrained Model](#12-download-pretrained-model) * [1.2 Download Pre-trained Model](#12-download-pretrained-model)
- [2. Training](#2-training) - [2. Training](#2-training)
* [2.1 Start Training](#21-start-training) * [2.1 Start Training](#21-start-training)
* [2.2 Load Trained Model and Continue Training](#22-load-trained-model-and-continue-training) * [2.2 Load Trained Model and Continue Training](#22-load-trained-model-and-continue-training)
...@@ -45,7 +45,7 @@ After decompressing the data set and downloading the annotation file, PaddleOCR/ ...@@ -45,7 +45,7 @@ After decompressing the data set and downloading the annotation file, PaddleOCR/
└─ test_icdar2015_label.txt Test annotation of icdar dataset └─ test_icdar2015_label.txt Test annotation of icdar dataset
``` ```
The provided annotation file format is as follow, seperated by "\t": The provided annotation file format is as follow, separated by "\t":
``` ```
" Image file name Image annotation information encoded by json.dumps" " Image file name Image annotation information encoded by json.dumps"
ch4_test_images/img_61.jpg [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}] ch4_test_images/img_61.jpg [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}]
...@@ -59,19 +59,19 @@ The `points` in the dictionary represent the coordinates (x, y) of the four poin ...@@ -59,19 +59,19 @@ The `points` in the dictionary represent the coordinates (x, y) of the four poin
If you want to train PaddleOCR on other datasets, please build the annotation file according to the above format. If you want to train PaddleOCR on other datasets, please build the annotation file according to the above format.
### 1.2 Download Pretrained Model ### 1.2 Download Pre-trained Model
First download the pretrained model. The detection model of PaddleOCR currently supports 3 backbones, namely MobileNetV3, ResNet18_vd and ResNet50_vd. You can use the model in [PaddleClas](https://github.com/PaddlePaddle/PaddleClas/tree/release/2.0/ppcls/modeling/architectures) to replace backbone according to your needs. First download the pre-trained model. The detection model of PaddleOCR currently supports 3 backbones, namely MobileNetV3, ResNet18_vd and ResNet50_vd. You can use the model in [PaddleClas](https://github.com/PaddlePaddle/PaddleClas/tree/release/2.0/ppcls/modeling/architectures) to replace backbone according to your needs.
And the responding download link of backbone pretrain weights can be found in (https://github.com/PaddlePaddle/PaddleClas/blob/release%2F2.0/README_cn.md#resnet%E5%8F%8A%E5%85%B6vd%E7%B3%BB%E5%88%97). And the responding download link of backbone pre-trained weights can be found in (https://github.com/PaddlePaddle/PaddleClas/blob/release%2F2.0/README_cn.md#resnet%E5%8F%8A%E5%85%B6vd%E7%B3%BB%E5%88%97).
```shell ```shell
cd PaddleOCR/ cd PaddleOCR/
# Download the pre-trained model of MobileNetV3 # Download the pre-trained model of MobileNetV3
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams
# or, download the pre-trained model of ResNet18_vd # or, download the pre-trained model of ResNet18_vd
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet18_vd_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet18_vd_pretrained.pdparams
# or, download the pre-trained model of ResNet50_vd # or, download the pre-trained model of ResNet50_vd
wget -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet50_vd_ssld_pretrained.pdparams
``` ```
......
doc/doc_en/distributed_training.md
View file @ 41a1b292
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
## Introduction ## Introduction
The high performance of distributed training is one of the core advantages of PaddlePaddle. In the classification task, distributed training can achieve almost linear speedup ratio. Generally, OCR training task need massive training data. Such as recognition, ppocrv2.0 model is trained based on 1800W dataset, which is very time-consuming if using single machine. Therefore, the distributed training is used in paddleocr to speedup the training task. For more information about distributed training, please refer to [distributed training quick start tutorial](https://fleet-x.readthedocs.io/en/latest/paddle_fleet_rst/parameter_server/ps_quick_start.html). The high performance of distributed training is one of the core advantages of PaddlePaddle. In the classification task, distributed training can achieve almost linear speedup ratio. Generally, OCR training task need massive training data. Such as recognition, PP-OCR v2.0 model is trained based on 1800W dataset, which is very time-consuming if using single machine. Therefore, the distributed training is used in PaddleOCR to speedup the training task. For more information about distributed training, please refer to [distributed training quick start tutorial](https://fleet-x.readthedocs.io/en/latest/paddle_fleet_rst/parameter_server/ps_quick_start.html).
## Quick Start ## Quick Start
...@@ -35,7 +35,7 @@ python3 -m paddle.distributed.launch \ ...@@ -35,7 +35,7 @@ python3 -m paddle.distributed.launch \
**Notice:** **Notice:**
* The IP addresses of different machines need to be separated by commas, which can be queried through `ifconfig` or `ipconfig`. * The IP addresses of different machines need to be separated by commas, which can be queried through `ifconfig` or `ipconfig`.
* Different machines need to be set to be secret free and can `ping` success with others directly, otherwise communication cannot establish between them. * Different machines need to be set to be secret free and can `ping` success with others directly, otherwise communication cannot establish between them.
* The code, data and start command betweent different machines must be completely consistent and then all machines need to run start command. The first machine in the `ip_list` is set to `trainer0`, and so on. * The code, data and start command between different machines must be completely consistent and then all machines need to run start command. The first machine in the `ip_list` is set to `trainer0`, and so on.
## Performance comparison ## Performance comparison
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment