[Docs] Pick seg fastdeploy docs from PaddleSeg (#1482)

* [Docs] Pick seg fastdeploy docs from PaddleSeg

* [Docs] update seg docs

* [Docs] Add c&csharp examples for seg

* [Docs] Add c&csharp examples for seg

* [Doc] Update paddleseg README.md

* Update README.md

examples/vision/segmentation/paddleseg/semantic_segmentation/sophgo/cpp/CMakeLists.txt

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+PROJECT(infer_demo C CXX)
+CMAKE_MINIMUM_REQUIRED (VERSION 3.10)
+# 指定下载解压后的fastdeploy库路径
+option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.")
+
+set(ENABLE_LITE_BACKEND OFF)
+#set(FDLIB ${FASTDEPLOY_INSTALL_DIR})
+
+include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake)
+
+# 添加FastDeploy依赖头文件
+include_directories(${FASTDEPLOY_INCS})
+include_directories(${FastDeploy_INCLUDE_DIRS})
+
+add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc)
+# 添加FastDeploy库依赖
+target_link_libraries(infer_demo ${FASTDEPLOY_LIBS})

examples/vision/segmentation/paddleseg/semantic_segmentation/sophgo/cpp/README.md

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+[English](README.md) | 简体中文
+# PaddleSeg 算能 C++ 部署示例
+
+本目录下提供`infer.cc`快速完成PP-LiteSeg在SOPHGO BM1684x板子上加速部署的示例。
+
+## 1. 部署环境准备
+在部署前，需自行编译基于算能硬件的预测库，参考文档[算能硬件部署环境](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#算能硬件部署环境)
+
+## 2. 部署模型准备  
+在部署前，请准备好您所需要运行的推理模型，你可以选择使用[预导出的推理模型](../README.md)或者[自行导出PaddleSeg部署模型](../README.md)。
+
+## 3. 生成基本目录文件
+
+该例程由以下几个部分组成
+```text
+.
+├── CMakeLists.txt
+├── fastdeploy-sophgo  # 编译文件夹
+├── image  # 存放图片的文件夹
+├── infer.cc
+└── model  # 存放模型文件的文件夹
+```
+
+## 4. 运行部署示例
+
+### 4.1 编译FastDeploy
+
+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
+
+### 4.2 下载部署示例代码
+```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy/examples/vision/segmentation/semantic_segmentation/sophgo/cpp
+# # 如果您希望从PaddleSeg下载示例代码，请运行
+# git clone https://github.com/PaddlePaddle/PaddleSeg.git
+# # 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+# # git checkout develop
+# cd PaddleSeg/deploy/fastdeploy/semantic_segmentation/sophgo/cpp
+```
+
+### 4.3 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.md)
+
+将转换后的SOPHGO bmodel模型文件拷贝至model中
+
+### 4.4 准备测试图片至image文件夹
+```bash
+wget https://paddleseg.bj.bcebos.com/dygraph/demo/cityscapes_demo.png
+cp cityscapes_demo.png ./images
+```
+
+### 4.5 编译example
+
+```bash
+cd build
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-sophgo
+make
+```
+
+### 4.6 运行例程
+
+```bash
+./infer_demo model images/cityscapes_demo.png
+```
+
+## 5. 更多指南
+- [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.md)

examples/vision/segmentation/paddleseg/semantic_segmentation/sophgo/cpp/infer.cc

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+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+#include <iostream>
+#include <string>
+
+#include "fastdeploy/vision.h"
+
+void SophgoInfer(const std::string& model_dir, const std::string& image_file) {
+  std::string model_file = model_dir + "/pp_liteseg_1684x_f32.bmodel";
+  std::string params_file;
+  std::string config_file = model_dir + "/deploy.yaml";
+  auto option = fastdeploy::RuntimeOption();
+  option.UseSophgo();
+  auto model_format = fastdeploy::ModelFormat::SOPHGO;
+
+  auto model = fastdeploy::vision::segmentation::PaddleSegModel(
+      model_file, params_file, config_file, option, model_format);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+  // model.GetPreprocessor().DisableNormalizeAndPermute();
+
+  fastdeploy::TimeCounter tc;
+  tc.Start();
+  auto im_org = cv::imread(image_file);
+
+  // the input of bmodel should be fixed
+  int new_width = 512;
+  int new_height = 512;
+  cv::Mat im;
+  cv::resize(im_org, im, cv::Size(new_width, new_height), cv::INTER_LINEAR);
+
+  fastdeploy::vision::SegmentationResult res;
+  if (!model.Predict(&im, &res)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+  auto vis_im = fastdeploy::vision::VisSegmentation(im, res);
+  tc.End();
+  tc.PrintInfo("PPSeg in Sophgo");
+
+  cv::imwrite("infer_sophgo.jpg", vis_im);
+  std::cout << "Visualized result saved in ./infer_sophgo.jpg" << std::endl;
+}
+
+int main(int argc, char* argv[]) {
+  if (argc < 3) {
+    std::cout
+        << "Usage: infer_demo path/to/model_dir path/to/image run_option, "
+           "e.g ./infer_model ./bmodel ./test.jpeg"
+        << std::endl;
+    return -1;
+  }
+
+  SophgoInfer(argv[1], argv[2]);
+  return 0;
+}