--- typora-copy-images-to: images comments: true hide: - toc --- # Paddle2ONNX模型转化与预测 本章节介绍 PaddleOCR 模型如何转化为 ONNX 模型，并基于 ONNXRuntime 引擎预测。同时我们准备了一个[在线 AI Studio 项目](https://aistudio.baidu.com/projectdetail/8808858)，可以方便用户进行测试。 ## 1. 环境准备 需要准备 PaddleOCR、Paddle2ONNX 模型转化环境，和 ONNXRuntime 预测环境。 ### PaddleOCR 克隆PaddleOCR的仓库，使用 main 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。 ```bash linenums="1" git clone -b main https://github.com/PaddlePaddle/PaddleOCR.git cd PaddleOCR && python3 -m pip install -e . ``` ### Paddle2ONNX 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 7~19，部分Paddle算子支持更低的ONNX Opset转换。 更多细节可参考 [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX.git) - 安装 Paddle2ONNX ```bash linenums="1" python3 -m pip install paddle2onnx ``` - 安装 ONNXRuntime ```bash linenums="1" python3 -m pip install onnxruntime ``` ## 2. 模型转换 ### 获取 Paddle 静态图模型 有两种方式获取Paddle静态图模型：在 [model_list](../ppocr/model_list.md) 中下载PaddleOCR提供的预测模型；参考[模型导出说明](./python_infer.md#inference)把训练好的权重转为推理模型。 #### 下载准备好的静态图模型 以 PP-OCR 系列中文检测、识别、分类模型为例： === "PP-OCRv3" ```bash linenums="1" wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && cd .. wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar cd ./inference && tar xf ch_PP-OCRv3_rec_infer.tar && cd .. wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar cd ./inference && tar xf ch_ppocr_mobile_v2.0_cls_infer.tar && cd .. ``` === "PP-OCRv4" ```bash linenums="1" wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar cd ./inference && tar xf ch_PP-OCRv4_det_infer.tar && cd .. wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar cd ./inference && tar xf ch_PP-OCRv4_rec_infer.tar && cd .. wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar cd ./inference && tar xf ch_ppocr_mobile_v2.0_cls_infer.tar && cd .. ``` #### 将动态图导出为静态图模型 (可选) 下载动态图模型： ```bash linenums="1" wget -nc -P pretrained https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_train.tar cd pretrained && tar xf ch_PP-OCRv4_det_train.tar && cd .. wget -nc -P pretrained https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_train.tar cd pretrained && tar xf ch_PP-OCRv4_rec_train.tar && cd .. wget -nc -P pretrained https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar cd pretrained && tar xf ch_ppocr_mobile_v2.0_cls_train.tar && cd .. ``` 转换为静态图模型： ```bash linenums="1" python3 tools/export_model.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_student.yml \ -o Global.pretrained_model=./pretrained/ch_PP-OCRv4_det_train/best_accuracy \ Global.save_inference_dir=./inference/ch_PP-OCRv4_det_infer/ python3 tools/export_model.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec.yml \ -o Global.pretrained_model=./pretrained/ch_PP-OCRv4_rec_train/student \ Global.save_inference_dir=./inference/ch_PP-OCRv4_rec_infer/ python3 tools/export_model.py -c configs/cls/cls_mv3.yml \ -o Global.pretrained_model=./pretrained/ch_ppocr_mobile_v2.0_cls_train/best_accuracy \ Global.save_inference_dir=./inference/ch_ppocr_mobile_v2.0_cls_infer/ ``` ### 模型转换 使用 Paddle2ONNX 将Paddle静态图模型转换为ONNX模型格式： === "PP-OCRv3" ```bash linenums="1" paddle2onnx --model_dir ./inference/ch_PP-OCRv3_det_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/det_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True paddle2onnx --model_dir ./inference/ch_PP-OCRv3_rec_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/rec_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True paddle2onnx --model_dir ./inference/ch_ppocr_mobile_v2.0_cls_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/cls_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True ``` === "PP-OCRv4" ```bash linenums="1" paddle2onnx --model_dir ./inference/ch_PP-OCRv4_det_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/det_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True paddle2onnx --model_dir ./inference/ch_PP-OCRv4_rec_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/rec_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True paddle2onnx --model_dir ./inference/ch_ppocr_mobile_v2.0_cls_infer \ --model_filename inference.pdmodel \ --params_filename inference.pdiparams \ --save_file ./inference/cls_onnx/model.onnx \ --opset_version 11 \ --enable_onnx_checker True ``` 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 - 注意：对于OCR模型，转化过程中必须采用动态shape的形式，否则预测结果可能与直接使用Paddle预测有细微不同。 另外，以下几个模型暂不支持转换为 ONNX 模型： NRTR、SAR、RARE、SRN - 注意：[Paddle2ONNX 版本 v1.2.3](https://github.com/PaddlePaddle/Paddle2ONNX/releases/tag/v1.2.3)后已默认支持动态shape，即 `float32[p2o.DynamicDimension.0,3,p2o.DynamicDimension.1,p2o.DynamicDimension.2]`，选项 `--input_shape_dict` 已废弃。如果有shape调整需求可使用如下命令进行Paddle模型输入shape调整。 ```bash linenums="1" python3 -m paddle2onnx.optimize --input_model inference/det_onnx/model.onnx \ --output_model inference/det_onnx/model.onnx \ --input_shape_dict "{'x': [-1,3,-1,-1]}" ``` 如你对导出的 ONNX 模型有优化的需求，推荐使用 [onnxslim](https://github.com/inisis/OnnxSlim) 对模型进行优化: ```bash linenums="1" pip install onnxslim onnxslim model.onnx slim.onnx ``` ## 3. 推理预测 以中文OCR模型为例，使用 ONNXRuntime 预测可执行如下命令： ```bash linenums="1" python3 tools/infer/predict_system.py --use_gpu=False --use_onnx=True \ --det_model_dir=./inference/det_onnx/model.onnx \ --rec_model_dir=./inference/rec_onnx/model.onnx \ --cls_model_dir=./inference/cls_onnx/model.onnx \ --image_dir=./docs/infer_deploy/images/lite_demo.png ``` 以中文OCR模型为例，使用 Paddle Inference 预测可执行如下命令： === "PP-OCRv3" ```bash linenums="1" python3 tools/infer/predict_system.py --use_gpu=False \ --cls_model_dir=./inference/ch_ppocr_mobile_v2.0_cls_infer \ --rec_model_dir=./inference/ch_PP-OCRv3_rec_infer \ --det_model_dir=./inference/ch_PP-OCRv3_det_infer \ --image_dir=./docs/infer_deploy/images/lite_demo.png ``` === "PP-OCRv4" ```bash linenums="1" python3 tools/infer/predict_system.py --use_gpu=False \ --cls_model_dir=./inference/ch_ppocr_mobile_v2.0_cls_infer \ --rec_model_dir=./inference/ch_PP-OCRv4_rec_infer \ --det_model_dir=./inference/ch_PP-OCRv4_det_infer \ --image_dir=./docs/infer_deploy/images/lite_demo.png ``` 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。 ONNXRuntime 执行效果： ![](./images/lite_demo_onnx.png) Paddle Inference 执行效果： ![](./images/lite_demo_paddle.png) 使用 ONNXRuntime 预测，终端输出： ```bash linenums="1" [2022/02/22 17:48:27] root DEBUG: dt_boxes num : 38, elapse : 0.043187856674194336 [2022/02/22 17:48:27] root DEBUG: rec_res num : 38, elapse : 0.592170000076294 [2022/02/22 17:48:27] root DEBUG: 0 Predict time of ./deploy/lite/imgs/lite_demo.png: 0.642s [2022/02/22 17:48:27] root DEBUG: The, 0.984 [2022/02/22 17:48:27] root DEBUG: visualized, 0.882 [2022/02/22 17:48:27] root DEBUG: etect18片, 0.720 [2022/02/22 17:48:27] root DEBUG: image saved in./vis.jpg, 0.947 [2022/02/22 17:48:27] root DEBUG: 纯臻营养护发素0.993604, 0.996 [2022/02/22 17:48:27] root DEBUG: 产品信息/参数, 0.922 [2022/02/22 17:48:27] root DEBUG: 0.992728, 0.914 [2022/02/22 17:48:27] root DEBUG: （45元／每公斤，100公斤起订）, 0.926 [2022/02/22 17:48:27] root DEBUG: 0.97417, 0.977 [2022/02/22 17:48:27] root DEBUG: 每瓶22元，1000瓶起订）0.993976, 0.962 [2022/02/22 17:48:27] root DEBUG: 【品牌】：代加工方式/0EMODM, 0.945 [2022/02/22 17:48:27] root DEBUG: 0.985133, 0.980 [2022/02/22 17:48:27] root DEBUG: 【品名】：纯臻营养护发素, 0.921 [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 [2022/02/22 17:48:27] root DEBUG: 【净含量】：220ml, 0.943 [2022/02/22 17:48:27] root DEBUG: Q.996577, 0.932 [2022/02/22 17:48:27] root DEBUG: 【适用人群】：适合所有肤质, 0.913 [2022/02/22 17:48:27] root DEBUG: 0.995842, 0.969 [2022/02/22 17:48:27] root DEBUG: 【主要成分】：鲸蜡硬脂醇、燕麦B-葡聚, 0.883 [2022/02/22 17:48:27] root DEBUG: 0.961928, 0.964 [2022/02/22 17:48:27] root DEBUG: 10, 0.812 [2022/02/22 17:48:27] root DEBUG: 糖、椰油酰胺丙基甜菜碱、泛醒, 0.866 [2022/02/22 17:48:27] root DEBUG: 0.925898, 0.943 [2022/02/22 17:48:27] root DEBUG: （成品包材）, 0.974 [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 [2022/02/22 17:48:27] root DEBUG: 0.994448, 0.952 [2022/02/22 17:48:27] root DEBUG: 13, 0.998 [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 [2022/02/22 17:48:27] root DEBUG: 0.990198, 0.975 [2022/02/22 17:48:27] root DEBUG: 14, 0.977 [2022/02/22 17:48:27] root DEBUG: 发足够的滋养, 0.991 [2022/02/22 17:48:27] root DEBUG: 0.997668, 0.918 [2022/02/22 17:48:27] root DEBUG: 花费了0.457335秒, 0.901 [2022/02/22 17:48:27] root DEBUG: The visualized image saved in ./inference_results/lite_demo.png [2022/02/22 17:48:27] root INFO: The predict total time is 0.7003889083862305 ``` 使用 Paddle Inference 预测，终端输出： ```bash linenums="1" [2022/02/22 17:47:25] root DEBUG: dt_boxes num : 38, elapse : 0.11791276931762695 [2022/02/22 17:47:27] root DEBUG: rec_res num : 38, elapse : 2.6206860542297363 [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 ```