English | [简体中文](README_CN.md) # PPOCRv3 C++ Deployment Example This directory provides examples that `infer.cc` fast finishes the deployment of PPOCRv3 on CPU/GPU and GPU accelerated by TensorRT. Two steps before deployment - 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../../docs/en/build_and_install/download_prebuilt_libraries.md) - 2. Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../../docs/en/build_and_install/download_prebuilt_libraries.md) Taking the CPU inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 0.7.0 or above (x.x.x>=0.7.0) is required to support this model. ``` mkdir build cd build # Download the FastDeploy precompiled library. Users can choose your appropriate version in the `FastDeploy Precompiled Library` mentioned above cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x make -j # Download model, image, and dictionary files wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/doc/imgs/12.jpg wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/ppocr/utils/ppocr_keys_v1.txt # CPU推理 ./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \ ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \ ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \ ./ppocr_keys_v1.txt \ ./12.jpg \ 0 # RKNPU推理 ./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer_rk3588_unquantized.rknn \ ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v20_cls_infer_rk3588_unquantized.rknn \ ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer_rk3588_unquantized.rknn \ ./ppocr_keys_v1.txt \ ./12.jpg \ 1 ``` The above command works for Linux or MacOS. For SDK in Windows, refer to: - [How to use FastDeploy C++ SDK in Windows](../../../../../../docs/cn/faq/use_sdk_on_windows.md) The visualized result after running is as follows ## Other Documents - [C++ API Reference](https://baidu-paddle.github.io/fastdeploy-api/cpp/html/) - [PPOCR Model Description](../README.md) - [PPOCRv3 Python Deployment](../python) - [Model Prediction Results](../../../../../../docs/en/faq/how_to_change_backend.md) - [How to switch the model inference backend engine](../../../../../../docs/en/faq/how_to_change_backend.md)