From dbd27878cb59789b52affff3556ee070d2c65cfa Mon Sep 17 00:00:00 2001 From: LDOUBLEV Date: Tue, 22 Dec 2020 10:09:51 +0800 Subject: [PATCH] update cpp_infer readme --- deploy/cpp_infer/readme.md | 15 +++++++-------- deploy/cpp_infer/readme_en.md | 19 ++++++++++--------- 2 files changed, 17 insertions(+), 17 deletions(-) diff --git a/deploy/cpp_infer/readme.md b/deploy/cpp_infer/readme.md index 66302a01..b563ecf4 100644 --- a/deploy/cpp_infer/readme.md +++ b/deploy/cpp_infer/readme.md @@ -122,10 +122,10 @@ build/paddle_inference_install_dir/ * 下载之后使用下面的方法解压。 ``` -tar -xf fluid_inference.tgz +tar -xf paddle_inference.tgz ``` -最终会在当前的文件夹中生成`fluid_inference/`的子文件夹。 +最终会在当前的文件夹中生成`paddle_inference/`的子文件夹。 ## 2 开始运行 @@ -137,11 +137,11 @@ tar -xf fluid_inference.tgz ``` inference/ |-- det_db -| |--model -| |--params +| |--inference.pdparams +| |--inference.pdimodel |-- rec_rcnn -| |--model -| |--params +| |--inference.pdparams +| |--inference.pdparams ``` @@ -180,7 +180,7 @@ cmake .. \ make -j ``` -`OPENCV_DIR`为opencv编译安装的地址；`LIB_DIR`为下载(`fluid_inference`文件夹)或者编译生成的Paddle预测库地址(`build/fluid_inference_install_dir`文件夹)；`CUDA_LIB_DIR`为cuda库文件地址，在docker中；为`/usr/local/cuda/lib64`；`CUDNN_LIB_DIR`为cudnn库文件地址，在docker中为`/usr/lib/x86_64-linux-gnu/`。 +`OPENCV_DIR`为opencv编译安装的地址；`LIB_DIR`为下载(`paddle_inference`文件夹)或者编译生成的Paddle预测库地址(`build/paddle_inference_install_dir`文件夹)；`CUDA_LIB_DIR`为cuda库文件地址，在docker中；为`/usr/local/cuda/lib64`；`CUDNN_LIB_DIR`为cudnn库文件地址，在docker中为`/usr/lib/x86_64-linux-gnu/`。 * 编译完成之后，会在`build`文件夹下生成一个名为`ocr_system`的可执行文件。 @@ -202,7 +202,6 @@ gpu_id 0 # GPU id，使用GPU时有效 gpu_mem 4000 # 申请的GPU内存 cpu_math_library_num_threads 10 # CPU预测时的线程数，在机器核数充足的情况下，该值越大，预测速度越快 use_mkldnn 1 # 是否使用mkldnn库 -use_zero_copy_run 1 # 是否使用use_zero_copy_run进行预测 # det config max_side_len 960 # 输入图像长宽大于960时，等比例缩放图像，使得图像最长边为960 diff --git a/deploy/cpp_infer/readme_en.md b/deploy/cpp_infer/readme_en.md index 8bd76c04..41c764bc 100644 --- a/deploy/cpp_infer/readme_en.md +++ b/deploy/cpp_infer/readme_en.md @@ -130,10 +130,10 @@ Among them, `paddle` is the Paddle library required for C++ prediction later, an * After downloading, use the following method to uncompress. ``` -tar -xf fluid_inference.tgz +tar -xf paddle_inference.tgz ``` -Finally you can see the following files in the folder of `fluid_inference/`. +Finally you can see the following files in the folder of `paddle_inference/`. ## 2. Compile and run the demo @@ -145,11 +145,11 @@ Finally you can see the following files in the folder of `fluid_inference/`. ``` inference/ |-- det_db -| |--model -| |--params +| |--inference.pdparams +| |--inference.pdimodel |-- rec_rcnn -| |--model -| |--params +| |--inference.pdparams +| |--inference.pdparams ``` @@ -188,7 +188,9 @@ cmake .. \ make -j ``` -`OPENCV_DIR` is the opencv installation path; `LIB_DIR` is the download (`fluid_inference` folder) or the generated Paddle inference library path (`build/fluid_inference_install_dir` folder); `CUDA_LIB_DIR` is the cuda library file path, in docker; it is `/usr/local/cuda/lib64`; `CUDNN_LIB_DIR` is the cudnn library file path, in docker it is `/usr/lib/x86_64-linux-gnu/`. +`OPENCV_DIR` is the opencv installation path; `LIB_DIR` is the download (`paddle_inference` folder) +or the generated Paddle inference library path (`build/paddle_inference_install_dir` folder); +`CUDA_LIB_DIR` is the cuda library file path, in docker; it is `/usr/local/cuda/lib64`; `CUDNN_LIB_DIR` is the cudnn library file path, in docker it is `/usr/lib/x86_64-linux-gnu/`. * After the compilation is completed, an executable file named `ocr_system` will be generated in the `build` folder. @@ -211,7 +213,6 @@ gpu_id 0 # GPU id when use_gpu is 1 gpu_mem 4000 # GPU memory requested cpu_math_library_num_threads 10 # Number of threads when using CPU inference. When machine cores is enough, the large the value, the faster the inference speed use_mkldnn 1 # Whether to use mkdlnn library -use_zero_copy_run 1 # Whether to use use_zero_copy_run for inference max_side_len 960 # Limit the maximum image height and width to 960 det_db_thresh 0.3 # Used to filter the binarized image of DB prediction, setting 0.-0.3 has no obvious effect on the result @@ -244,4 +245,4 @@ The detection results will be shown on the screen, which is as follows. ### 2.3 Notes -* Paddle2.0.0-beta0 inference model library is recommanded for this tuturial. +* Paddle2.0.0-beta0 inference model library is recommended for this toturial. -- GitLab