[Benchmark] add PaddleDetection to benchmark (#1675)

* 添加paddleclas模型 * 更新README_CN * 更新README_CN * 更新README * update get_model.sh * update get_models.sh * update paddleseg models * update paddle_seg models * update paddle_seg models * modified test resources * update benchmark_gpu_trt.sh * add paddle detection * add paddledetection to benchmark * modified benchmark cmakelists * update benchmark scripts * modified benchmark function calling --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
2025-10-30 11:26:39 +08:00 · 2023-04-13 10:29:49 +08:00
parent d1da460230
commit 60a44f5af1
19 changed files with 1320 additions and 50 deletions
--- a/benchmark/cpp/benchmark_yolov3.cc
+++ b/benchmark/cpp/benchmark_yolov3.cc
@@ -0,0 +1,79 @@
+// Copyright (c) 2023 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 "flags.h"
+#include "macros.h"
+#include "option.h"
+
+namespace vision = fastdeploy::vision;
+namespace benchmark = fastdeploy::benchmark;
+
+DEFINE_bool(no_nms, false, "Whether the model contains nms.");
+
+int main(int argc, char* argv[]) {
+#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
+  // Initialization
+  auto option = fastdeploy::RuntimeOption();
+  if (!CreateRuntimeOption(&option, argc, argv, true)) {
+    return -1;
+  }
+  auto im = cv::imread(FLAGS_image);
+  std::unordered_map<std::string, std::string> config_info;
+  benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
+                                                &config_info);
+  std::string model_name, params_name, config_name;
+  auto model_format = fastdeploy::ModelFormat::PADDLE;
+  if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
+                               &model_format, config_info)) {
+    return -1;
+  }
+  auto model_file = FLAGS_model + sep + model_name;
+  auto params_file = FLAGS_model + sep + params_name;
+  auto config_file = FLAGS_model + sep + config_name;
+  auto model_yolov3 = vision::detection::YOLOv3(
+      model_file, params_file, config_file, option, model_format);
+  vision::DetectionResult res;
+  if (config_info["precision_compare"] == "true") {
+    // Run once at least
+    model_yolov3.Predict(im, &res);
+    // 1. Test result diff
+    std::cout << "=============== Test result diff =================\n";
+    // Save result to -> disk.
+    std::string det_result_path = "yolov3_result.txt";
+    benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
+    // Load result from <- disk.
+    vision::DetectionResult res_loaded;
+    benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
+    // Calculate diff between two results.
+    auto det_diff =
+        benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
+    std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
+              << ", max=" << det_diff.boxes.max
+              << ", min=" << det_diff.boxes.min << std::endl;
+    std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
+              << ", max=" << det_diff.labels.max
+              << ", min=" << det_diff.labels.min << std::endl;
+  }
+  // Run profiling
+  if (FLAGS_no_nms) {
+    model_yolov3.GetPostprocessor().ApplyNMS();
+  }
+  BENCHMARK_MODEL(model_yolov3, model_yolov3.Predict(im, &res))
+  auto vis_im = vision::VisDetection(im, res);
+  cv::imwrite("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+#endif
+
+  return 0;
+}