Merge pull request #7855 from tink2123/updata_paddle2onnx_doc
updata paddle2onnx en docpull/7832/head
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# Paddle2ONNX模型转化与预测
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# Paddle2ONNX model transformation and prediction
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本章节介绍 PaddleOCR 模型如何转化为 ONNX 模型，并基于 ONNXRuntime 引擎预测。
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This chapter describes how the PaddleOCR model is converted into an ONNX model and predicted based on the ONNXRuntime engine.
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## 1. 环境准备
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## 1. Environment preparation
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需要准备 PaddleOCR、Paddle2ONNX 模型转化环境，和 ONNXRuntime 预测环境
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Need to prepare PaddleOCR, Paddle2ONNX model conversion environment, and ONNXRuntime prediction environment
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### PaddleOCR
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克隆PaddleOCR的仓库，使用release/2.4分支，并进行安装，由于PaddleOCR仓库比较大，git clone速度比较慢，所以本教程已下载
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Clone the PaddleOCR repository, use the release/2.6 branch, and install it.
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```
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git clone -b release/2.4 https://github.com/PaddlePaddle/PaddleOCR.git
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git clone -b release/2.6 https://github.com/PaddlePaddle/PaddleOCR.git
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cd PaddleOCR && python3.7 setup.py install
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```
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### Paddle2ONNX
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Paddle2ONNX 支持将 PaddlePaddle 模型格式转化到 ONNX 模型格式，算子目前稳定支持导出 ONNX Opset 9~11，部分Paddle算子支持更低的ONNX Opset转换。
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更多细节可参考 [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX/blob/develop/README_zh.md)
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Paddle2ONNX supports converting the PaddlePaddle model format to the ONNX model format. The operator currently supports exporting ONNX Opset 9~11 stably, and some Paddle operators support lower ONNX Opset conversion.
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For more details, please refer to [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX/blob/develop/README_en.md)
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- 安装 Paddle2ONNX
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- install Paddle2ONNX
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```
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python3.7 -m pip install paddle2onnx
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```
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- 安装 ONNXRuntime
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- install ONNXRuntime
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```
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# 建议安装 1.9.0 版本，可根据环境更换版本号
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# It is recommended to install version 1.9.0, and the version number can be changed according to the environment
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python3.7 -m pip install onnxruntime==1.9.0
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```
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## 2. 模型转换
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## 2. Model conversion
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- Paddle 模型下载
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- Paddle model download
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有两种方式获取Paddle静态图模型：在 [model_list](../../doc/doc_ch/models_list.md) 中下载PaddleOCR提供的预测模型；
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参考[模型导出说明](../../doc/doc_ch/inference.md#训练模型转inference模型)把训练好的权重转为 inference_model。
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There are two ways to obtain the Paddle model: Download the prediction model provided by PaddleOCR in [model_list](../../doc/doc_en/models_list_en.md);
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Refer to [Model Export Instructions](../../doc/doc_en/inference_en.md#1-convert-training-model-to-inference-model) to convert the trained weights to inference_model.
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以 ppocr 中文检测、识别、分类模型为例：
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Take the PP-OCRv3 detection, recognition, and classification model as an example:
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```
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wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar
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cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && cd ..
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wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar
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cd ./inference && tar xf en_PP-OCRv3_det_infer.tar && cd ..
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wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar
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cd ./inference && tar xf ch_PP-OCRv2_rec_infer.tar && cd ..
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wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar
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cd ./inference && tar xf en_PP-OCRv3_rec_infer.tar && cd ..
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wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar
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cd ./inference && tar xf ch_ppocr_mobile_v2.0_cls_infer.tar && cd ..
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```
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- 模型转换
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- convert model
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使用 Paddle2ONNX 将Paddle静态图模型转换为ONNX模型格式：
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Convert Paddle inference model to ONNX model format using Paddle2ONNX:
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```
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paddle2onnx --model_dir ./inference/ch_PP-OCRv2_det_infer \
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paddle2onnx --model_dir ./inference/en_PP-OCRv3_det_infer \
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--model_filename inference.pdmodel \
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--params_filename inference.pdiparams \
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--save_file ./inference/det_onnx/model.onnx \
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@ -65,7 +66,7 @@ paddle2onnx --model_dir ./inference/ch_PP-OCRv2_det_infer \
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--input_shape_dict="{'x':[-1,3,-1,-1]}" \
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--enable_onnx_checker True
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paddle2onnx --model_dir ./inference/ch_PP-OCRv2_rec_infer \
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paddle2onnx --model_dir ./inference/en_PP-OCRv3_rec_infer \
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--model_filename inference.pdmodel \
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--params_filename inference.pdiparams \
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--save_file ./inference/rec_onnx/model.onnx \
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@ -81,136 +82,89 @@ paddle2onnx --model_dir ./inference/ch_ppocr_mobile_v2.0_cls_infer \
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--input_shape_dict="{'x':[-1,3,-1,-1]}" \
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--enable_onnx_checker True
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```
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After execution, the ONNX model will be saved in `./inference/det_onnx/`, `./inference/rec_onnx/`, `./inference/cls_onnx/` paths respectively
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执行完毕后，ONNX 模型会被分别保存在 `./inference/det_onnx/`，`./inference/rec_onnx/`，`./inference/cls_onnx/`路径下
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* Note: For the OCR model, the conversion process must be in the form of dynamic shape, that is, add the option --input_shape_dict="{'x': [-1, 3, -1, -1]}", otherwise the prediction result may be the same as Predicting directly with Paddle is slightly different.
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In addition, the following models do not currently support conversion to ONNX models:
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NRTR, SAR, RARE, SRN
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* 注意：对于OCR模型，转化过程中必须采用动态shape的形式，即加入选项--input_shape_dict="{'x': [-1, 3, -1, -1]}"，否则预测结果可能与直接使用Paddle预测有细微不同。
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另外，以下几个模型暂不支持转换为 ONNX 模型：
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NRTR、SAR、RARE、SRN
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## 3. prediction
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## 3. 推理预测
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以中文OCR模型为例，使用 ONNXRuntime 预测可执行如下命令：
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Take the English OCR model as an example, use **ONNXRuntime** to predict and execute the following commands:
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```
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python3.7 tools/infer/predict_system.py --use_gpu=False --use_onnx=True \
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--det_model_dir=./inference/det_onnx/model.onnx \
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--rec_model_dir=./inference/rec_onnx/model.onnx \
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--cls_model_dir=./inference/cls_onnx/model.onnx \
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--image_dir=./deploy/lite/imgs/lite_demo.png
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--image_dir=doc/imgs_en/img_12.jpg \
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--rec_char_dict_path=ppocr/utils/en_dict.txt
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```
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以中文OCR模型为例，使用 Paddle Inference 预测可执行如下命令：
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Taking the English OCR model as an example, use **Paddle Inference** to predict and execute the following commands:
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```
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python3.7 tools/infer/predict_system.py --use_gpu=False \
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--cls_model_dir=./inference/ch_ppocr_mobile_v2.0_cls_infer \
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--rec_model_dir=./inference/ch_PP-OCRv2_rec_infer \
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--det_model_dir=./inference/ch_PP-OCRv2_det_infer \
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--image_dir=./deploy/lite/imgs/lite_demo.png
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--rec_model_dir=./inference/en_PP-OCRv3_rec_infer \
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--det_model_dir=./inference/en_PP-OCRv3_det_infer \
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--image_dir=doc/imgs_en/img_12.jpg \
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--rec_char_dict_path=ppocr/utils/en_dict.txt
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```
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执行命令后在终端会打印出预测的识别信息，并在 `./inference_results/` 下保存可视化结果。
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After executing the command, the predicted identification information will be printed out in the terminal, and the visualization results will be saved under `./inference_results/`.
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ONNXRuntime 执行效果：
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ONNXRuntime result：
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<div align="center">
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<img src="./images/lite_demo_onnx.png" width=800">
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<img src="../../doc/imgs_results/multi_lang/img_12.jpg" width=800">
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</div>
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Paddle Inference 执行效果：
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Paddle Inference result：
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<div align="center">
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<img src="./images/lite_demo_paddle.png" width=800">
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<img src="../../doc/imgs_results/multi_lang/img_12.jpg" width=800">
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</div>
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使用 ONNXRuntime 预测，终端输出：
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Using ONNXRuntime to predict, terminal output:
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```
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[2022/02/22 17:48:27] root DEBUG: dt_boxes num : 38, elapse : 0.043187856674194336
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[2022/02/22 17:48:27] root DEBUG: rec_res num : 38, elapse : 0.592170000076294
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[2022/02/22 17:48:27] root DEBUG: 0 Predict time of ./deploy/lite/imgs/lite_demo.png: 0.642s
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[2022/02/22 17:48:27] root DEBUG: The, 0.984
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[2022/02/22 17:48:27] root DEBUG: visualized, 0.882
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[2022/02/22 17:48:27] root DEBUG: etect18片, 0.720
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[2022/02/22 17:48:27] root DEBUG: image saved in./vis.jpg, 0.947
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[2022/02/22 17:48:27] root DEBUG: 纯臻营养护发素0.993604, 0.996
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[2022/02/22 17:48:27] root DEBUG: 产品信息/参数, 0.922
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[2022/02/22 17:48:27] root DEBUG: 0.992728, 0.914
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[2022/02/22 17:48:27] root DEBUG: （45元／每公斤，100公斤起订）, 0.926
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[2022/02/22 17:48:27] root DEBUG: 0.97417, 0.977
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[2022/02/22 17:48:27] root DEBUG: 每瓶22元，1000瓶起订）0.993976, 0.962
|
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[2022/02/22 17:48:27] root DEBUG: 【品牌】：代加工方式/0EMODM, 0.945
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[2022/02/22 17:48:27] root DEBUG: 0.985133, 0.980
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[2022/02/22 17:48:27] root DEBUG: 【品名】：纯臻营养护发素, 0.921
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[2022/02/22 17:48:27] root DEBUG: 0.995007, 0.883
|
||||
[2022/02/22 17:48:27] root DEBUG: 【产品编号】：YM-X-30110.96899, 0.955
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[2022/02/22 17:48:27] root DEBUG: 【净含量】：220ml, 0.943
|
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[2022/02/22 17:48:27] root DEBUG: Q.996577, 0.932
|
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[2022/02/22 17:48:27] root DEBUG: 【适用人群】：适合所有肤质, 0.913
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[2022/02/22 17:48:27] root DEBUG: 0.995842, 0.969
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[2022/02/22 17:48:27] root DEBUG: 【主要成分】：鲸蜡硬脂醇、燕麦B-葡聚, 0.883
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[2022/02/22 17:48:27] root DEBUG: 0.961928, 0.964
|
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[2022/02/22 17:48:27] root DEBUG: 10, 0.812
|
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[2022/02/22 17:48:27] root DEBUG: 糖、椰油酰胺丙基甜菜碱、泛醒, 0.866
|
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[2022/02/22 17:48:27] root DEBUG: 0.925898, 0.943
|
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[2022/02/22 17:48:27] root DEBUG: （成品包材）, 0.974
|
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[2022/02/22 17:48:27] root DEBUG: 0.972573, 0.961
|
||||
[2022/02/22 17:48:27] root DEBUG: 【主要功能】：可紧致头发磷层，从而达到, 0.936
|
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[2022/02/22 17:48:27] root DEBUG: 0.994448, 0.952
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[2022/02/22 17:48:27] root DEBUG: 13, 0.998
|
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[2022/02/22 17:48:27] root DEBUG: 即时持久改善头发光泽的效果，给干燥的头, 0.994
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[2022/02/22 17:48:27] root DEBUG: 0.990198, 0.975
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[2022/02/22 17:48:27] root DEBUG: 14, 0.977
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[2022/02/22 17:48:27] root DEBUG: 发足够的滋养, 0.991
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[2022/02/22 17:48:27] root DEBUG: 0.997668, 0.918
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[2022/02/22 17:48:27] root DEBUG: 花费了0.457335秒, 0.901
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[2022/02/22 17:48:27] root DEBUG: The visualized image saved in ./inference_results/lite_demo.png
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[2022/02/22 17:48:27] root INFO: The predict total time is 0.7003889083862305
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[2022/10/10 12:06:28] ppocr DEBUG: dt_boxes num : 11, elapse : 0.3568880558013916
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[2022/10/10 12:06:31] ppocr DEBUG: rec_res num : 11, elapse : 2.6445000171661377
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[2022/10/10 12:06:31] ppocr DEBUG: 0 Predict time of doc/imgs_en/img_12.jpg: 3.021s
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[2022/10/10 12:06:31] ppocr DEBUG: ACKNOWLEDGEMENTS, 0.997
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[2022/10/10 12:06:31] ppocr DEBUG: We would like to thank all the designers and, 0.976
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[2022/10/10 12:06:31] ppocr DEBUG: contributors who have been involved in the, 0.979
|
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[2022/10/10 12:06:31] ppocr DEBUG: production of this book; their contributions, 0.989
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[2022/10/10 12:06:31] ppocr DEBUG: have been indispensable to its creation. We, 0.956
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[2022/10/10 12:06:31] ppocr DEBUG: would also like to express our gratitude to all, 0.991
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[2022/10/10 12:06:31] ppocr DEBUG: the producers for their invaluable opinions, 0.978
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[2022/10/10 12:06:31] ppocr DEBUG: and assistance throughout this project. And to, 0.988
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[2022/10/10 12:06:31] ppocr DEBUG: the many others whose names are not credited, 0.958
|
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[2022/10/10 12:06:31] ppocr DEBUG: but have made specific input in this book, we, 0.970
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[2022/10/10 12:06:31] ppocr DEBUG: thank you for your continuous support., 0.998
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[2022/10/10 12:06:31] ppocr DEBUG: The visualized image saved in ./inference_results/img_12.jpg
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[2022/10/10 12:06:31] ppocr INFO: The predict total time is 3.2482550144195557
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```
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使用 Paddle Inference 预测，终端输出：
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Using Paddle Inference to predict, terminal output:
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```
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[2022/02/22 17:47:25] root DEBUG: dt_boxes num : 38, elapse : 0.11791276931762695
|
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[2022/02/22 17:47:27] root DEBUG: rec_res num : 38, elapse : 2.6206860542297363
|
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[2022/02/22 17:47:27] root DEBUG: 0 Predict time of ./deploy/lite/imgs/lite_demo.png: 2.746s
|
||||
[2022/02/22 17:47:27] root DEBUG: The, 0.984
|
||||
[2022/02/22 17:47:27] root DEBUG: visualized, 0.882
|
||||
[2022/02/22 17:47:27] root DEBUG: etect18片, 0.720
|
||||
[2022/02/22 17:47:27] root DEBUG: image saved in./vis.jpg, 0.947
|
||||
[2022/02/22 17:47:27] root DEBUG: 纯臻营养护发素0.993604, 0.996
|
||||
[2022/02/22 17:47:27] root DEBUG: 产品信息/参数, 0.922
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.992728, 0.914
|
||||
[2022/02/22 17:47:27] root DEBUG: （45元／每公斤，100公斤起订）, 0.926
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.97417, 0.977
|
||||
[2022/02/22 17:47:27] root DEBUG: 每瓶22元，1000瓶起订）0.993976, 0.962
|
||||
[2022/02/22 17:47:27] root DEBUG: 【品牌】：代加工方式/0EMODM, 0.945
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.985133, 0.980
|
||||
[2022/02/22 17:47:27] root DEBUG: 【品名】：纯臻营养护发素, 0.921
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.995007, 0.883
|
||||
[2022/02/22 17:47:27] root DEBUG: 【产品编号】：YM-X-30110.96899, 0.955
|
||||
[2022/02/22 17:47:27] root DEBUG: 【净含量】：220ml, 0.943
|
||||
[2022/02/22 17:47:27] root DEBUG: Q.996577, 0.932
|
||||
[2022/02/22 17:47:27] root DEBUG: 【适用人群】：适合所有肤质, 0.913
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.995842, 0.969
|
||||
[2022/02/22 17:47:27] root DEBUG: 【主要成分】：鲸蜡硬脂醇、燕麦B-葡聚, 0.883
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.961928, 0.964
|
||||
[2022/02/22 17:47:27] root DEBUG: 10, 0.812
|
||||
[2022/02/22 17:47:27] root DEBUG: 糖、椰油酰胺丙基甜菜碱、泛醒, 0.866
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.925898, 0.943
|
||||
[2022/02/22 17:47:27] root DEBUG: （成品包材）, 0.974
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.972573, 0.961
|
||||
[2022/02/22 17:47:27] root DEBUG: 【主要功能】：可紧致头发磷层，从而达到, 0.936
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.994448, 0.952
|
||||
[2022/02/22 17:47:27] root DEBUG: 13, 0.998
|
||||
[2022/02/22 17:47:27] root DEBUG: 即时持久改善头发光泽的效果，给干燥的头, 0.994
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.990198, 0.975
|
||||
[2022/02/22 17:47:27] root DEBUG: 14, 0.977
|
||||
[2022/02/22 17:47:27] root DEBUG: 发足够的滋养, 0.991
|
||||
[2022/02/22 17:47:27] root DEBUG: 0.997668, 0.918
|
||||
[2022/02/22 17:47:27] root DEBUG: 花费了0.457335秒, 0.901
|
||||
[2022/02/22 17:47:27] root DEBUG: The visualized image saved in ./inference_results/lite_demo.png
|
||||
[2022/02/22 17:47:27] root INFO: The predict total time is 2.8338775634765625
|
||||
[2022/10/10 12:06:28] ppocr DEBUG: dt_boxes num : 11, elapse : 0.3568880558013916
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: rec_res num : 11, elapse : 2.6445000171661377
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: 0 Predict time of doc/imgs_en/img_12.jpg: 3.021s
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: ACKNOWLEDGEMENTS, 0.997
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: We would like to thank all the designers and, 0.976
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: contributors who have been involved in the, 0.979
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: production of this book; their contributions, 0.989
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: have been indispensable to its creation. We, 0.956
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: would also like to express our gratitude to all, 0.991
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: the producers for their invaluable opinions, 0.978
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: and assistance throughout this project. And to, 0.988
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: the many others whose names are not credited, 0.958
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: but have made specific input in this book, we, 0.970
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: thank you for your continuous support., 0.998
|
||||
[2022/10/10 12:06:31] ppocr DEBUG: The visualized image saved in ./inference_results/img_12.jpg
|
||||
[2022/10/10 12:06:31] ppocr INFO: The predict total time is 3.2482550144195557
|
||||
```
|
||||
|
|
|
|||
Loading…
Reference in New Issue