From 745d0018fae12c1675044a6caaf638a5db6ce493 Mon Sep 17 00:00:00 2001 From: CoolCola <49013063+CoolKbh@users.noreply.github.com> Date: Tue, 14 Mar 2023 10:22:52 +0800 Subject: [PATCH] [DOC]fix death url (#1598) fix death url --- docs/cn/build_and_install/a311d.md | 2 +- docs/cn/build_and_install/rv1126.md | 2 +- docs/cn/faq/rknpu2/rknpu2.md | 6 +++--- docs/en/build_and_install/a311d.md | 2 +- docs/en/build_and_install/rv1126.md | 2 +- .../tiny_pose/rknpu2/cpp/README.md | 4 ++-- .../tiny_pose/rknpu2/python/README_CN.md | 6 +++--- examples/vision/matting/ppmatting/README.md | 4 ++-- examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md | 2 +- .../paddleseg/amlogic/a311d/cpp/README.md | 4 ++-- .../segmentation/paddleseg/cpu-gpu/c/README.md | 12 ++++++------ .../segmentation/paddleseg/cpu-gpu/c/README_CN.md | 14 +++++++------- .../paddleseg/cpu-gpu/csharp/README.md | 12 ++++++------ .../paddleseg/cpu-gpu/csharp/README_CN.md | 12 ++++++------ .../vision/segmentation/paddleseg/kunlun/README.md | 2 +- .../segmentation/paddleseg/kunlun/cpp/README.md | 2 +- .../segmentation/paddleseg/quantize/README.md | 6 +++--- .../paddleseg/rockchip/rknpu2/cpp/README.md | 4 ++-- .../paddleseg/rockchip/rknpu2/python/README.md | 2 +- .../paddleseg/rockchip/rv1126/cpp/README.md | 4 ++-- .../paddleseg/serving/fastdeploy_serving/README.md | 2 +- .../segmentation/paddleseg/sophgo/cpp/README.md | 4 ++-- .../segmentation/paddleseg/sophgo/python/README.md | 2 +- .../segmentation/ppmatting/cpu-gpu/cpp/README.md | 2 +- 24 files changed, 57 insertions(+), 57 deletions(-) diff --git a/docs/cn/build_and_install/a311d.md b/docs/cn/build_and_install/a311d.md index 03b0a05ef0..67060114cf 100755 --- a/docs/cn/build_and_install/a311d.md +++ b/docs/cn/build_and_install/a311d.md @@ -118,4 +118,4 @@ tar -xf PaddleLite-generic-demo.tar.gz 3. A311D 上部署 YOLOv5 检测模型请参考：[YOLOv5 检测模型在 A311D 上的 C++ 部署示例](../../../examples/vision/detection/yolov5/a311d/README.md) -4. A311D 上部署 PP-LiteSeg 分割模型请参考：[PP-LiteSeg 分割模型在 A311D 上的 C++ 部署示例](../../../examples/vision/segmentation/paddleseg/a311d/README.md) +4. A311D 上部署 PP-LiteSeg 分割模型请参考：[PP-LiteSeg 分割模型在 A311D 上的 C++ 部署示例](../../../examples/vision/segmentation/paddleseg/amlogic/a311d/README.md) diff --git a/docs/cn/build_and_install/rv1126.md b/docs/cn/build_and_install/rv1126.md index 669050c308..79c3efa102 100755 --- a/docs/cn/build_and_install/rv1126.md +++ b/docs/cn/build_and_install/rv1126.md @@ -118,4 +118,4 @@ tar -xf PaddleLite-generic-demo.tar.gz 3. RV1126 上部署 YOLOv5 检测模型请参考：[YOLOv5 检测模型在 RV1126 上的 C++ 部署示例](../../../examples/vision/detection/yolov5/rv1126/README.md) -4. RV1126 上部署 PP-LiteSeg 分割模型请参考：[PP-LiteSeg 分割模型在 RV1126 上的 C++ 部署示例](../../../examples/vision/segmentation/paddleseg/rv1126/README.md) +4. RV1126 上部署 PP-LiteSeg 分割模型请参考：[PP-LiteSeg 分割模型在 RV1126 上的 C++ 部署示例](../../../examples/vision/segmentation/paddleseg/rockchip/rv1126/README.md) diff --git a/docs/cn/faq/rknpu2/rknpu2.md b/docs/cn/faq/rknpu2/rknpu2.md index 1426e0cd3d..cb482fbf2d 100644 --- a/docs/cn/faq/rknpu2/rknpu2.md +++ b/docs/cn/faq/rknpu2/rknpu2.md @@ -25,9 +25,9 @@ FastDeploy在RK3588s上进行了测试，测试环境如下: | Detection | [RKYOLOV5](../../../../examples/vision/detection/rkyolo/README.md) | YOLOV5-S-Relu(int8) | 是 | 57 | | Detection | [RKYOLOX](../../../../examples/vision/detection/rkyolo/README.md) | yolox-s | 是 | 130 | | Detection | [RKYOLOV7](../../../../examples/vision/detection/rkyolo/README.md) | yolov7-tiny | 是 | 58 | -| Segmentation | [Unet](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | Unet-cityscapes | 否 | - | -| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | portrait(int8) | 是 | 43 | -| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | human(int8) | 是 | 43 | +| Segmentation | [Unet](../../../../examples/vision/segmentation/paddleseg/rockchip/rknpu2/README.md) | Unet-cityscapes | 否 | - | +| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rockchip/rknpu2/README.md) | portrait(int8) | 是 | 43 | +| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rockchip/rknpu2/README.md) | human(int8) | 是 | 43 | | Face Detection | [SCRFD](../../../../examples/vision/facedet/scrfd/rknpu2/README.md) | SCRFD-2.5G-kps-640(int8) | 是 | 42 | | Face FaceRecognition | [InsightFace](../../../../examples/vision/faceid/insightface/rknpu2/README_CN.md) | ms1mv3_arcface_r18(int8) | 是 | 12 | diff --git a/docs/en/build_and_install/a311d.md b/docs/en/build_and_install/a311d.md index f431f55c28..f909ab350d 100755 --- a/docs/en/build_and_install/a311d.md +++ b/docs/en/build_and_install/a311d.md @@ -105,4 +105,4 @@ For more details, please refer to: [Paddle Lite prepares the device environment] 3. For deploying YOLOv5 detection model on A311D, please refer to: [C++ Deployment Example of YOLOv5 Detection Model on A311D](../../../examples/vision/detection/yolov5/a311d/README.md) -4. For deploying PP-LiteSeg segmentation model on A311D, please refer to: [C++ Deployment Example of PP-LiteSeg Segmentation Model on A311D](../../../examples/vision/segmentation/paddleseg/a311d/README.md) +4. For deploying PP-LiteSeg segmentation model on A311D, please refer to: [C++ Deployment Example of PP-LiteSeg Segmentation Model on A311D](../../../examples/vision/segmentation/paddleseg/amlogic/a311d/README.md) diff --git a/docs/en/build_and_install/rv1126.md b/docs/en/build_and_install/rv1126.md index de9c563ab5..0796c6337a 100755 --- a/docs/en/build_and_install/rv1126.md +++ b/docs/en/build_and_install/rv1126.md @@ -105,4 +105,4 @@ For more details, please refer to: [Paddle Lite prepares the device environment] 3. For deploying YOLOv5 detection model on RV1126, please refer to: [C++ Deployment Example of YOLOv5 Detection Model on RV1126](../../../examples/vision/detection/yolov5/rv1126/README.md) -4. For deploying PP-LiteSeg segmentation model on RV1126, please refer to: [C++ Deployment Example of PP-LiteSeg Segmentation Model on RV1126](../../../examples/vision/segmentation/paddleseg/rv1126/README.md) +4. For deploying PP-LiteSeg segmentation model on RV1126, please refer to: [C++ Deployment Example of PP-LiteSeg Segmentation Model on RV1126](../../../examples/vision/segmentation/paddleseg/rockchip/rv1126/README.md) diff --git a/examples/vision/keypointdetection/tiny_pose/rknpu2/cpp/README.md b/examples/vision/keypointdetection/tiny_pose/rknpu2/cpp/README.md index 843ebe6829..117fe69d74 100644 --- a/examples/vision/keypointdetection/tiny_pose/rknpu2/cpp/README.md +++ b/examples/vision/keypointdetection/tiny_pose/rknpu2/cpp/README.md @@ -35,7 +35,7 @@ sudo ./infer_tinypose_demo ./PP_TinyPose_256x192_infer ./hrnet_demo.jpg 以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考: -- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) +- [如何在Windows中使用FastDeploy C++ SDK](../../../../../../docs/cn/faq/use_sdk_on_windows.md) ## PP-TinyPose C++接口 @@ -79,5 +79,5 @@ PPTinyPose模型加载和初始化，其中model_file为导出的Paddle模型格 - [模型介绍](../../../) - [Python部署](../../python) -- [视觉模型预测结果](../../../../../../docs/api/vision_results/) +- [视觉模型预测结果](../../../../../../../docs/api/vision_results/) - [如何切换模型推理后端引擎](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/keypointdetection/tiny_pose/rknpu2/python/README_CN.md b/examples/vision/keypointdetection/tiny_pose/rknpu2/python/README_CN.md index 1a0f37d0bc..5ecac3557b 100644 --- a/examples/vision/keypointdetection/tiny_pose/rknpu2/python/README_CN.md +++ b/examples/vision/keypointdetection/tiny_pose/rknpu2/python/README_CN.md @@ -53,7 +53,7 @@ PP-TinyPose模型加载和初始化，其中model_file, params_file以及config_ > **返回** > -> > 返回`fastdeploy.vision.KeyPointDetectionResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/) +> > 返回`fastdeploy.vision.KeyPointDetectionResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../../docs/api/vision_results/) ### 类成员属性 #### 后处理参数 @@ -66,5 +66,5 @@ PP-TinyPose模型加载和初始化，其中model_file, params_file以及config_ - [PP-TinyPose 模型介绍](..) - [PP-TinyPose C++部署](../cpp) -- [模型预测结果说明](../../../../../docs/api/vision_results/) -- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) +- [模型预测结果说明](../../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/matting/ppmatting/README.md b/examples/vision/matting/ppmatting/README.md index 2a54d53c78..cbf61bed85 100644 --- a/examples/vision/matting/ppmatting/README.md +++ b/examples/vision/matting/ppmatting/README.md @@ -1,3 +1,3 @@ -PaddleSeg Matting deployment examples, please refer to [document](../../segmentation/ppmatting/README_CN.md). +PaddleSeg Matting deployment examples, please refer to [document](../../segmentation/ppmatting/README.md). -PaddleSeg Matting的部署示例，请参考[文档](../../segmentation/ppmatting/README_CN.md). +PaddleSeg Matting的部署示例，请参考[文档](../../segmentation/ppmatting/README.md). diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md index 9864627811..93f9b8a9cd 100755 --- a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md +++ b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md @@ -40,7 +40,7 @@ wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/ppocr/utils/ppocr_ ``` 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) +- [How to use FastDeploy C++ SDK in Windows](../../../../../../docs/cn/faq/use_sdk_on_windows.md) The visualized result after running is as follows diff --git a/examples/vision/segmentation/paddleseg/amlogic/a311d/cpp/README.md b/examples/vision/segmentation/paddleseg/amlogic/a311d/cpp/README.md index 57a71f86f2..4240c7e1f9 100644 --- a/examples/vision/segmentation/paddleseg/amlogic/a311d/cpp/README.md +++ b/examples/vision/segmentation/paddleseg/amlogic/a311d/cpp/README.md @@ -8,8 +8,8 @@ 软硬件环境满足要求，以及交叉编译环境的准备，请参考：[FastDeploy](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#自行编译安装) ### 模型准备 -1. 用户可以直接使用由[FastDeploy 提供的量化模型](../README_CN.md#晶晨a311d支持的paddleseg模型)进行部署。 -2. 若FastDeploy没有提供满足要求的量化模型，用户可以参考[PaddleSeg动态图模型导出为A311D支持的INT8模型](../README_CN.md#paddleseg动态图模型导出为a311d支持的int8模型)自行导出或训练量化模型 +1. 用户可以直接使用由[FastDeploy 提供的量化模型](../README.md#晶晨a311d支持的paddleseg模型)进行部署。 +2. 若FastDeploy没有提供满足要求的量化模型，用户可以参考[PaddleSeg动态图模型导出为A311D支持的INT8模型](../README.md#paddleseg动态图模型导出为a311d支持的int8模型)自行导出或训练量化模型 3. 若上述导出或训练的模型出现精度下降或者报错，则需要使用异构计算，使得模型算子部分跑在A311D的ARM CPU上进行调试以及精度验证，其中异构计算所需的文件是subgraph.txt。具体关于异构计算可参考：[异构计算](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/faq/heterogeneous_computing_on_timvx_npu.md)。 ## 在 A311D 上部署量化后的 PP-LiteSeg 分割模型 diff --git a/examples/vision/segmentation/paddleseg/cpu-gpu/c/README.md b/examples/vision/segmentation/paddleseg/cpu-gpu/c/README.md index 3d4b099d93..e991593572 100755 --- a/examples/vision/segmentation/paddleseg/cpu-gpu/c/README.md +++ b/examples/vision/segmentation/paddleseg/cpu-gpu/c/README.md @@ -5,8 +5,8 @@ This directory provides `infer.c` to finish the deployment of PaddleSeg on CPU/G Before deployment, two steps require confirmation -- 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) +- 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 inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 1.0.4 or above (x.x.x>=1.0.4) is required to support this model. @@ -32,7 +32,7 @@ wget https://paddleseg.bj.bcebos.com/dygraph/demo/cityscapes_demo.png ``` The above command works for Linux or MacOS. For SDK in Windows, refer to: -- [How to use FastDeploy C++ SDK in Windows](../../../../../docs/en/faq/use_sdk_on_windows.md) +- [How to use FastDeploy C++ SDK in Windows](../../../../../../docs/en/faq/use_sdk_on_windows.md) The visualized result after running is as follows @@ -154,7 +154,7 @@ FD_C_Bool FD_C_PaddleSegWrapperPredict( > **Params** > * **fd_c_ppseg_wrapper**(FD_C_PaddleSegWrapper*): Pointer to manipulate PaddleSeg object. > * **img**（FD_C_Mat）: pointer to cv::Mat object, which can be obained by FD_C_Imread interface -> * **result**(FD_C_SegmentationResult*): Segmentation prediction results, Refer to [Vision Model Prediction Results](../../../../../docs/api/vision_results/) for SegmentationResult +> * **result**(FD_C_SegmentationResult*): Segmentation prediction results, Refer to [Vision Model Prediction Results](../../../../../../docs/api/vision_results/) for SegmentationResult #### Result @@ -180,5 +180,5 @@ FD_C_Mat FD_C_VisSegmentation(FD_C_Mat im, - [PPSegmentation Model Description](../../) - [PaddleSeg Python Deployment](../python) -- [Model Prediction Results](../../../../../docs/api/vision_results/) -- [How to switch the model inference backend engine](../../../../../docs/cn/faq/how_to_change_backend.md) +- [Model Prediction Results](../../../../../../docs/api/vision_results/) +- [How to switch the model inference backend engine](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/segmentation/paddleseg/cpu-gpu/c/README_CN.md b/examples/vision/segmentation/paddleseg/cpu-gpu/c/README_CN.md index 677e4be977..e33b2c44fb 100644 --- a/examples/vision/segmentation/paddleseg/cpu-gpu/c/README_CN.md +++ b/examples/vision/segmentation/paddleseg/cpu-gpu/c/README_CN.md @@ -5,8 +5,8 @@ 在部署前，需确认以下两个步骤 -- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) -- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) 以Linux上推理为例，在本目录执行如下命令即可完成编译测试，支持此模型需保证FastDeploy版本1.0.4以上(x.x.x>=1.0.4) @@ -32,10 +32,10 @@ wget https://paddleseg.bj.bcebos.com/dygraph/demo/cityscapes_demo.png ``` 以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考: -- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) +- [如何在Windows中使用FastDeploy C++ SDK](../../../../../../docs/cn/faq/use_sdk_on_windows.md) 如果用户使用华为昇腾NPU部署, 请参考以下方式在部署前初始化部署环境: -- [如何使用华为昇腾NPU部署](../../../../../docs/cn/faq/use_sdk_on_ascend.md) +- [如何使用华为昇腾NPU部署](../../../../../../docs/cn/faq/use_sdk_on_ascend.md) 运行完成可视化结果如下图所示 @@ -155,7 +155,7 @@ FD_C_Bool FD_C_PaddleSegWrapperPredict( > **参数** > * **fd_c_ppseg_wrapper**(FD_C_PaddleSegWrapper*): 指向PaddleSeg模型的指针 > * **img**（FD_C_Mat）: 输入图像的指针，指向cv::Mat对象，可以调用FD_C_Imread读取图像获取 -> * **result**FD_C_SegmentationResult*): Segmentation检测结果，SegmentationResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/) +> * **result**FD_C_SegmentationResult*): Segmentation检测结果，SegmentationResult说明参考[视觉模型预测结果](../../../../../../docs/api/vision_results/) #### Predict结果 @@ -181,5 +181,5 @@ FD_C_Mat FD_C_VisSegmentation(FD_C_Mat im, - [PPSegmentation 系列模型介绍](../../) - [PaddleSeg Python部署](../python) -- [模型预测结果说明](../../../../../docs/api/vision_results/) -- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) +- [模型预测结果说明](../../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README.md b/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README.md index 490538a7e5..db4aeee4a4 100755 --- a/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README.md +++ b/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README.md @@ -5,8 +5,8 @@ This directory provides `infer.cs` to finish the deployment of PaddleSeg on CPU/ Before deployment, two steps require confirmation -- 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) +- 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) Please follow below instructions to compile and test in Windows. FastDeploy version 1.0.4 or above (x.x.x>=1.0.4) is required to support this model. @@ -35,7 +35,7 @@ msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64 ``` For more information about how to use FastDeploy SDK to compile a project with Visual Studio 2019. Please refer to -- [Using the FastDeploy C++ SDK on Windows Platform](../../../../../docs/en/faq/use_sdk_on_windows.md) +- [Using the FastDeploy C++ SDK on Windows Platform](../../../../../../docs/en/faq/use_sdk_on_windows.md) ## 4. Execute compiled program @@ -93,12 +93,12 @@ fastdeploy.SegmentationResult Predict(OpenCvSharp.Mat im) >> > **Return** > ->> * **result**: Segmentation prediction results, refer to [Vision Model Prediction Results](../../../../../docs/api/vision_results/) for SegmentationResult +>> * **result**: Segmentation prediction results, refer to [Vision Model Prediction Results](../../../../../../docs/api/vision_results/) for SegmentationResult ## Other Documents - [PPSegmentation Model Description](../../) - [PaddleSeg Python Deployment](../python) -- [Model Prediction Results](../../../../../docs/api/vision_results/) -- [How to switch the model inference backend engine](../../../../../docs/cn/faq/how_to_change_backend.md) +- [Model Prediction Results](../../../../../../docs/api/vision_results/) +- [How to switch the model inference backend engine](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README_CN.md b/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README_CN.md index 7f7aae726a..ecdfd667f5 100644 --- a/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README_CN.md +++ b/examples/vision/segmentation/paddleseg/cpu-gpu/csharp/README_CN.md @@ -5,8 +5,8 @@ 在部署前，需确认以下两个步骤 -- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) -- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) 在本目录执行如下命令即可在Windows完成编译测试，支持此模型需保证FastDeploy版本1.0.4以上(x.x.x>=1.0.4) @@ -35,8 +35,8 @@ msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64 ``` 关于使用Visual Studio 2019创建sln工程，或者CMake工程等方式编译的更详细信息，可参考如下文档 -- [在 Windows 使用 FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) -- [FastDeploy C++库在Windows上的多种使用方式](../../../../../docs/cn/faq/use_sdk_on_windows_build.md) +- [在 Windows 使用 FastDeploy C++ SDK](../../../../../../docs/cn/faq/use_sdk_on_windows.md) +- [FastDeploy C++库在Windows上的多种使用方式](../../../../../../docs/cn/faq/use_sdk_on_windows_build.md) ## 4. 运行可执行程序 @@ -98,5 +98,5 @@ fastdeploy.SegmentationResult Predict(OpenCvSharp.Mat im) - [模型介绍](../../) - [Python部署](../python) -- [视觉模型预测结果](../../../../../docs/api/vision_results/) -- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) +- [视觉模型预测结果](../../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/segmentation/paddleseg/kunlun/README.md b/examples/vision/segmentation/paddleseg/kunlun/README.md index 305ce688c3..9b6adfadd6 100644 --- a/examples/vision/segmentation/paddleseg/kunlun/README.md +++ b/examples/vision/segmentation/paddleseg/kunlun/README.md @@ -28,7 +28,7 @@ PaddleSeg支持利用FastDeploy在昆仑芯片上部署Segmentation模型 - [DeepLabV3系列模型](https://github.com/PaddlePaddle/PaddleSeg/blob/develop/configs/deeplabv3/README.md) - [SegFormer系列模型](https://github.com/PaddlePaddle/PaddleSeg/blob/develop/configs/segformer/README.md) ->>**注意** 若需要在华为昇腾上部署**PP-Matting**、**PP-HumanMatting**请从[Matting模型部署](../../ppmating/)下载对应模型，部署过程与此文档一致 +>>**注意** 若需要在华为昇腾上部署**PP-Matting**、**PP-HumanMatting**请从[Matting模型部署](../../../ppmating/)下载对应模型，部署过程与此文档一致 ## 准备PaddleSeg部署模型 PaddleSeg模型导出，请参考其文档说明[模型导出](https://github.com/PaddlePaddle/PaddleSeg/blob/develop/docs/model_export_cn.md) diff --git a/examples/vision/segmentation/paddleseg/kunlun/cpp/README.md b/examples/vision/segmentation/paddleseg/kunlun/cpp/README.md index b85e3874e0..c5b20ec998 100644 --- a/examples/vision/segmentation/paddleseg/kunlun/cpp/README.md +++ b/examples/vision/segmentation/paddleseg/kunlun/cpp/README.md @@ -6,7 +6,7 @@ ## 昆仑芯XPU编译FastDeploy环境准备 在部署前，需自行编译基于昆仑芯XPU的预测库，参考文档[昆仑芯XPU部署环境编译安装](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#自行编译安装) ->>**注意** **PP-Matting**、**PP-HumanMatting**的模型，请从[Matting模型部署](../../../matting)下载 +>>**注意** **PP-Matting**、**PP-HumanMatting**的模型，请从[Matting模型部署](../../../../matting)下载 ```bash #下载部署示例代码 diff --git a/examples/vision/segmentation/paddleseg/quantize/README.md b/examples/vision/segmentation/paddleseg/quantize/README.md index 6327722479..067f34cd6d 100644 --- a/examples/vision/segmentation/paddleseg/quantize/README.md +++ b/examples/vision/segmentation/paddleseg/quantize/README.md @@ -22,6 +22,6 @@ FastDeploy 量化模型部署的过程大致都与FP32模型类似，只是模 | 硬件支持列表 | | | | |:----- | :-- | :-- | :-- | -| [NVIDIA GPU](cpu-gpu) | [X86 CPU](cpu-gpu)| [飞腾CPU](cpu-gpu) | [ARM CPU](cpu-gpu) | -| [Intel GPU(独立显卡/集成显卡)](cpu-gpu) | [昆仑](kunlun) | [昇腾](ascend) | [瑞芯微](rockchip) | -| [晶晨](amlogic) | [算能](sophgo) | +| [NVIDIA GPU](../cpu-gpu) | [X86 CPU](../cpu-gpu)| [飞腾CPU](../cpu-gpu) | [ARM CPU](../cpu-gpu) | +| [Intel GPU(独立显卡/集成显卡)](../cpu-gpu) | [昆仑](../kunlun) | [昇腾](../ascend) | [瑞芯微](../rockchip) | +| [晶晨](../amlogic) | [算能](../sophgo) | diff --git a/examples/vision/segmentation/paddleseg/rockchip/rknpu2/cpp/README.md b/examples/vision/segmentation/paddleseg/rockchip/rknpu2/cpp/README.md index 41da935791..6bb08d5020 100644 --- a/examples/vision/segmentation/paddleseg/rockchip/rknpu2/cpp/README.md +++ b/examples/vision/segmentation/paddleseg/rockchip/rknpu2/cpp/README.md @@ -12,11 +12,11 @@ ## 转换模型 -模型转换代码请参考[模型转换文档](../README_CN.md) +模型转换代码请参考[模型转换文档](../README.md) ## 编译SDK -请参考[RK2代NPU部署库编译](../../../../../../docs/cn/faq/rknpu2/build.md)编译SDK. +请参考[RK2代NPU部署库编译](../../../../../../../docs/cn/faq/rknpu2/build.md)编译SDK. ### 编译example diff --git a/examples/vision/segmentation/paddleseg/rockchip/rknpu2/python/README.md b/examples/vision/segmentation/paddleseg/rockchip/rknpu2/python/README.md index 7524b6c604..288409e196 100644 --- a/examples/vision/segmentation/paddleseg/rockchip/rknpu2/python/README.md +++ b/examples/vision/segmentation/paddleseg/rockchip/rknpu2/python/README.md @@ -32,7 +32,7 @@ RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作 - [FastDeploy部署PaddleSeg模型概览](..) - [PaddleSeg C++部署](../cpp) -- [转换PaddleSeg模型至RKNN模型文档](../README_CN.md#准备paddleseg部署模型以及转换模型) +- [转换PaddleSeg模型至RKNN模型文档](../README.md#准备paddleseg部署模型以及转换模型) ## 常见问题 - [如何将模型预测结果SegmentationResult转为numpy格式](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/faq/vision_result_related_problems.md) diff --git a/examples/vision/segmentation/paddleseg/rockchip/rv1126/cpp/README.md b/examples/vision/segmentation/paddleseg/rockchip/rv1126/cpp/README.md index aacad9ab1b..0b47d04b9f 100644 --- a/examples/vision/segmentation/paddleseg/rockchip/rv1126/cpp/README.md +++ b/examples/vision/segmentation/paddleseg/rockchip/rv1126/cpp/README.md @@ -8,8 +8,8 @@ 软硬件环境满足要求，以及交叉编译环境的准备，请参考：[瑞芯微RV1126部署环境](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#自行编译安装) ### 模型准备 -1. 用户可以直接使用由[FastDeploy 提供的量化模型](../README_CN.md#瑞芯微-rv1126-支持的paddleseg模型)进行部署。 -2. 若FastDeploy没有提供满足要求的量化模型，用户可以参考[PaddleSeg动态图模型导出为RV1126支持的INT8模型](../README_CN.md#paddleseg动态图模型导出为rv1126支持的int8模型)自行导出或训练量化模型 +1. 用户可以直接使用由[FastDeploy 提供的量化模型](../README.md#瑞芯微-rv1126-支持的paddleseg模型)进行部署。 +2. 若FastDeploy没有提供满足要求的量化模型，用户可以参考[PaddleSeg动态图模型导出为RV1126支持的INT8模型](../README.md#paddleseg动态图模型导出为rv1126支持的int8模型)自行导出或训练量化模型 3. 若上述导出或训练的模型出现精度下降或者报错，则需要使用异构计算，使得模型算子部分跑在RV1126的ARM CPU上进行调试以及精度验证，其中异构计算所需的文件是subgraph.txt。具体关于异构计算可参考：[异构计算](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/faq/heterogeneous_computing_on_timvx_npu.md)。 ## 在 RV1126 上部署量化后的 PP-LiteSeg 分割模型 diff --git a/examples/vision/segmentation/paddleseg/serving/fastdeploy_serving/README.md b/examples/vision/segmentation/paddleseg/serving/fastdeploy_serving/README.md index 120b3994a6..e48c27c5d2 100644 --- a/examples/vision/segmentation/paddleseg/serving/fastdeploy_serving/README.md +++ b/examples/vision/segmentation/paddleseg/serving/fastdeploy_serving/README.md @@ -65,4 +65,4 @@ When the request is sent successfully, the results are returned in json format a -The default is to run ONNXRuntime on CPU. If developers need to run it on GPU or other inference engines, please see the [Configs File](../../../../../serving/docs/EN/model_configuration-en.md) to modify the configs in `models/runtime/config.pbtxt`. +The default is to run ONNXRuntime on CPU. If developers need to run it on GPU or other inference engines, please see the [Configs File](../../../../../../serving/docs/EN/model_configuration-en.md) to modify the configs in `models/runtime/config.pbtxt`. diff --git a/examples/vision/segmentation/paddleseg/sophgo/cpp/README.md b/examples/vision/segmentation/paddleseg/sophgo/cpp/README.md index 3f33c398ca..8711d6a683 100644 --- a/examples/vision/segmentation/paddleseg/sophgo/cpp/README.md +++ b/examples/vision/segmentation/paddleseg/sophgo/cpp/README.md @@ -25,7 +25,7 @@ 请参考[SOPHGO部署库编译](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install/sophgo.md)编译SDK，编译完成后，将在build目录下生成fastdeploy-sophgo目录。拷贝fastdeploy-sophgo至当前目录 ### 拷贝模型文件，以及配置文件至model文件夹 -将Paddle模型转换为SOPHGO bmodel模型，转换步骤参考[文档](../README_CN.md#将paddleseg推理模型转换为bmodel模型步骤) +将Paddle模型转换为SOPHGO bmodel模型，转换步骤参考[文档](../README.md#将paddleseg推理模型转换为bmodel模型步骤) 将转换后的SOPHGO bmodel模型文件拷贝至model中 @@ -53,4 +53,4 @@ make - [PaddleSeg C++ API文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/namespacefastdeploy_1_1vision_1_1segmentation.html) - [FastDeploy部署PaddleSeg模型概览](../../) - [Python部署](../python) -- [模型转换](../README_CN.md#将paddleseg推理模型转换为bmodel模型步骤) +- [模型转换](../README.md#将paddleseg推理模型转换为bmodel模型步骤) diff --git a/examples/vision/segmentation/paddleseg/sophgo/python/README.md b/examples/vision/segmentation/paddleseg/sophgo/python/README.md index 55abb90f77..0649b01292 100644 --- a/examples/vision/segmentation/paddleseg/sophgo/python/README.md +++ b/examples/vision/segmentation/paddleseg/sophgo/python/README.md @@ -27,7 +27,7 @@ python3 infer.py --model_file ./bmodel/pp_liteseg_1684x_f32.bmodel --config_file ## 快速链接 - [pp_liteseg C++部署](../cpp) -- [转换 pp_liteseg SOPHGO模型文档](../README_CN.md#导出bmodel模型) +- [转换 pp_liteseg SOPHGO模型文档](../README.md#导出bmodel模型) ## 常见问题 - [如何将模型预测结果SegmentationResult转为numpy格式](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/faq/vision_result_related_problems.md) diff --git a/examples/vision/segmentation/ppmatting/cpu-gpu/cpp/README.md b/examples/vision/segmentation/ppmatting/cpu-gpu/cpp/README.md index b88b799428..a60aa3ffa2 100644 --- a/examples/vision/segmentation/ppmatting/cpu-gpu/cpp/README.md +++ b/examples/vision/segmentation/ppmatting/cpu-gpu/cpp/README.md @@ -45,7 +45,7 @@ wget https://bj.bcebos.com/paddlehub/fastdeploy/matting_bgr.jpg 以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考: -- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) +- [如何在Windows中使用FastDeploy C++ SDK](../../../../../../docs/cn/faq/use_sdk_on_windows.md) ## 快速链接 - [PaddleSeg C++ API文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/namespacefastdeploy_1_1vision_1_1segmentation.html)