[Hackthon_4th 177] Support PP-YOLOE-R with BM1684 (#1809)

* first draft

* add robx iou

* add benchmark for ppyoloe_r

* remove trash code

* fix bugs

* add pybind nms rotated option

* add missing head file

* fix bug

* fix bug2

* fix shape bug

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

examples/vision/detection/paddledetection/cpp/CMakeLists.txt

@@ -15,6 +15,9 @@ target_link_libraries(infer_faster_rcnn_demo ${FASTDEPLOY_LIBS})
 add_executable(infer_ppyoloe_demo ${PROJECT_SOURCE_DIR}/infer_ppyoloe.cc)
 target_link_libraries(infer_ppyoloe_demo ${FASTDEPLOY_LIBS})
 
+add_executable(infer_ppyoloe_r_demo ${PROJECT_SOURCE_DIR}/infer_ppyoloe_r.cc)
+target_link_libraries(infer_ppyoloe_r_demo ${FASTDEPLOY_LIBS})
+
 add_executable(infer_picodet_demo ${PROJECT_SOURCE_DIR}/infer_picodet.cc)
 target_link_libraries(infer_picodet_demo ${FASTDEPLOY_LIBS})
 

examples/vision/detection/paddledetection/cpp/infer_ppyoloe_r.cc

@@ -0,0 +1,98 @@
+// 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 "fastdeploy/vision.h"
+
+#ifdef WIN32
+const char sep = '\\';
+#else
+const char sep = '/';
+#endif
+
+void CpuInfer(const std::string& model_dir, const std::string& image_file) {
+  auto model_file = model_dir + sep + "model.pdmodel";
+  auto params_file = model_dir + sep + "model.pdiparams";
+  auto config_file = model_dir + sep + "infer_cfg.yml";
+  auto option = fastdeploy::RuntimeOption();
+  option.UseCpu();
+  auto model = fastdeploy::vision::detection::PPYOLOER(model_file, params_file,
+                                                        config_file, option);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+
+  auto im = cv::imread(image_file);
+  std::cout << im.cols << " vs " << im.rows << std::endl;
+  fastdeploy::vision::DetectionResult res;
+  if (!model.Predict(im, &res)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+
+  std::cout << res.Str() << std::endl;
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
+  cv::imwrite("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+void GpuInfer(const std::string& model_dir, const std::string& image_file) {
+  auto model_file = model_dir + sep + "model.pdmodel";
+  auto params_file = model_dir + sep + "model.pdiparams";
+  auto config_file = model_dir + sep + "infer_cfg.yml";
+
+  auto option = fastdeploy::RuntimeOption();
+  option.UseGpu();
+  auto model = fastdeploy::vision::detection::PPYOLOER(model_file, params_file,
+                                                        config_file, option);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+
+  const cv::Mat im = cv::imread(image_file);
+
+  fastdeploy::vision::DetectionResult res;
+  if (!model.Predict(im, &res)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+
+  std::cout << res.Str() << std::endl;
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.1);
+  cv::imwrite("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+int main(int argc, char* argv[]) {
+  if (argc < 4) {
+    std::cout
+        << "Usage: infer_ppyoloe_r path/to/model_dir path/to/image run_option, "
+           "e.g ./infer_ppyoloe_r ./ppyoloe_model_dir ./test.jpeg 0"
+        << std::endl;
+    std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
+                 "with gpu; 2: run with gpu and use tensorrt backend; 3: run "
+                 "with kunlunxin."
+              << std::endl;
+    return -1;
+  }
+
+  if (std::atoi(argv[3]) == 0) {
+    CpuInfer(argv[1], argv[2]);
+  } else if (std::atoi(argv[3]) == 1) {
+    GpuInfer(argv[1], argv[2]);
+  }
+
+  return 0;
+}