add demo

deploy/cpp/demo/classifier.cpp

+//   Copyright (c) 2020 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 <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+
+DEFINE_string(model_dir, "", "Path of inference model");
+DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
+DEFINE_bool(use_trt, false, "Infering with TensorRT");
+DEFINE_int32(gpu_id, 0, "GPU card id");
+DEFINE_string(key, "", "key of encryption");
+DEFINE_string(image, "", "Path of test image file");
+DEFINE_string(image_list, "", "Path of test image list file");
+
+int main(int argc, char** argv) {
+  // Parsing command-line
+  google::ParseCommandLineFlags(&argc, &argv, true);
+
+  if (FLAGS_model_dir == "") {
+    std::cerr << "--model_dir need to be defined" << std::endl;
+    return -1;
+  }
+  if (FLAGS_image == "" & FLAGS_image_list == "") {
+    std::cerr << "--image or --image_list need to be defined" << std::endl;
+    return -1;
+  }
+
+  // 加载模型
+  PaddleX::Model model;
+  model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
+
+  // 进行预测
+  if (FLAGS_image_list != "") {
+    std::ifstream inf(FLAGS_image_list);
+    if (!inf) {
+      std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
+      return -1;
+    }
+    std::string image_path;
+    while (getline(inf, image_path)) {
+      PaddleX::ClsResult result;
+      cv::Mat im = cv::imread(image_path, 1);
+      model.predict(im, &result);
+      std::cout << "Predict label: " << result.category
+                << ", label_id:" << result.category_id
+                << ", score: " << result.score << std::endl;
+    }
+  } else {
+    PaddleX::ClsResult result;
+    cv::Mat im = cv::imread(FLAGS_image, 1);
+    model.predict(im, &result);
+    std::cout << "Predict label: " << result.category
+              << ", label_id:" << result.category_id
+              << ", score: " << result.score << std::endl;
+  }
+
+  return 0;
+}

deploy/cpp/demo/detector.cpp

+//   Copyright (c) 2020 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 <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+#include "include/paddlex/visualize.h"
+
+DEFINE_string(model_dir, "", "Path of inference model");
+DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
+DEFINE_bool(use_trt, false, "Infering with TensorRT");
+DEFINE_int32(gpu_id, 0, "GPU card id");
+DEFINE_string(key, "", "key of encryption");
+DEFINE_string(image, "", "Path of test image file");
+DEFINE_string(image_list, "", "Path of test image list file");
+DEFINE_string(save_dir, "output", "Path to save visualized image");
+
+int main(int argc, char** argv) {
+  // 解析命令行参数
+  google::ParseCommandLineFlags(&argc, &argv, true);
+
+  if (FLAGS_model_dir == "") {
+    std::cerr << "--model_dir need to be defined" << std::endl;
+    return -1;
+  }
+  if (FLAGS_image == "" & FLAGS_image_list == "") {
+    std::cerr << "--image or --image_list need to be defined" << std::endl;
+    return -1;
+  }
+
+  // 加载模型
+  PaddleX::Model model;
+  model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
+
+  auto colormap = PaddleX::GenerateColorMap(model.labels.size());
+  std::string save_dir = "output";
+  // 进行预测
+  if (FLAGS_image_list != "") {
+    std::ifstream inf(FLAGS_image_list);
+    if (!inf) {
+      std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
+      return -1;
+    }
+    std::string image_path;
+    while (getline(inf, image_path)) {
+      PaddleX::DetResult result;
+      cv::Mat im = cv::imread(image_path, 1);
+      model.predict(im, &result);
+      for (int i = 0; i < result.boxes.size(); ++i) {
+        std::cout << "image file: " << image_path
+                  << ", predict label: " << result.boxes[i].category
+                  << ", label_id:" << result.boxes[i].category_id
+                  << ", score: " << result.boxes[i].score << ", box:("
+                  << result.boxes[i].coordinate[0] << ", "
+                  << result.boxes[i].coordinate[1] << ", "
+                  << result.boxes[i].coordinate[2] << ", "
+                  << result.boxes[i].coordinate[3] << ")" << std::endl;
+      }
+
+      // 可视化
+      cv::Mat vis_img =
+          PaddleX::Visualize(im, result, model.labels, colormap, 0.5);
+      std::string save_path =
+          PaddleX::generate_save_path(FLAGS_save_dir, image_path);
+      cv::imwrite(save_path, vis_img);
+      result.clear();
+      std::cout << "Visualized output saved as " << save_path << std::endl;
+    }
+  } else {
+    PaddleX::DetResult result;
+    cv::Mat im = cv::imread(FLAGS_image, 1);
+    model.predict(im, &result);
+    for (int i = 0; i < result.boxes.size(); ++i) {
+      std::cout << ", predict label: " << result.boxes[i].category
+                << ", label_id:" << result.boxes[i].category_id
+                << ", score: " << result.boxes[i].score << ", box:("
+                << result.boxes[i].coordinate[0] << ", "
+                << result.boxes[i].coordinate[1] << ", "
+                << result.boxes[i].coordinate[2] << ", "
+                << result.boxes[i].coordinate[3] << ")" << std::endl;
+    }
+
+    // 可视化
+    cv::Mat vis_img =
+        PaddleX::Visualize(im, result, model.labels, colormap, 0.5);
+    std::string save_path =
+        PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
+    cv::imwrite(save_path, vis_img);
+    result.clear();
+    std::cout << "Visualized output saved as " << save_path << std::endl;
+  }
+
+  return 0;
+}

deploy/cpp/demo/segmenter.cpp

+//   Copyright (c) 2020 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 <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+#include "include/paddlex/visualize.h"
+
+DEFINE_string(model_dir, "", "Path of inference model");
+DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
+DEFINE_bool(use_trt, false, "Infering with TensorRT");
+DEFINE_int32(gpu_id, 0, "GPU card id");
+DEFINE_string(key, "", "key of encryption");
+DEFINE_string(image, "", "Path of test image file");
+DEFINE_string(image_list, "", "Path of test image list file");
+DEFINE_string(save_dir, "output", "Path to save visualized image");
+
+int main(int argc, char** argv) {
+  // 解析命令行参数
+  google::ParseCommandLineFlags(&argc, &argv, true);
+
+  if (FLAGS_model_dir == "") {
+    std::cerr << "--model_dir need to be defined" << std::endl;
+    return -1;
+  }
+  if (FLAGS_image == "" & FLAGS_image_list == "") {
+    std::cerr << "--image or --image_list need to be defined" << std::endl;
+    return -1;
+  }
+
+  // 加载模型
+  PaddleX::Model model;
+  model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
+
+  auto colormap = PaddleX::GenerateColorMap(model.labels.size());
+  // 进行预测
+  if (FLAGS_image_list != "") {
+    std::ifstream inf(FLAGS_image_list);
+    if (!inf) {
+      std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
+      return -1;
+    }
+    std::string image_path;
+    while (getline(inf, image_path)) {
+      PaddleX::SegResult result;
+      cv::Mat im = cv::imread(image_path, 1);
+      model.predict(im, &result);
+      // 可视化
+      cv::Mat vis_img =
+          PaddleX::Visualize(im, result, model.labels, colormap);
+      std::string save_path =
+          PaddleX::generate_save_path(FLAGS_save_dir, image_path);
+      cv::imwrite(save_path, vis_img);
+      result.clear();
+      std::cout << "Visualized output saved as " << save_path << std::endl;
+    }
+  } else {
+    PaddleX::SegResult result;
+    cv::Mat im = cv::imread(FLAGS_image, 1);
+    model.predict(im, &result);
+    // 可视化
+    cv::Mat vis_img = PaddleX::Visualize(im, result, model.labels, colormap);
+    std::string save_path =
+        PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
+    cv::imwrite(save_path, vis_img);
+    result.clear();
+    std::cout << "Visualized output saved as " << save_path << std::endl;
+  }
+
+  return 0;
+}