Mixed updates and improvements.

scripts/.gitignore

@@ -1 +0,0 @@
-test_skelda_dataset

scripts/test_skelda_dataset_cpp.cpp

@@ -1,12 +1,12 @@
 #include <chrono>
-#include <memory>
-#include <string>
-#include <vector>
 #include <cmath>
-#include <iostream>
 #include <fstream>
+#include <iostream>
+#include <memory>
 #include <sstream>
 #include <stdexcept>
+#include <string>
+#include <vector>
 
 // OpenCV
 #include <opencv2/opencv.hpp>
@@ -15,10 +15,10 @@
 #include "/RapidPoseTriangulation/extras/include/nlohmann/json.hpp"
 using json = nlohmann::json;
 
-#include "/RapidPoseTriangulation/scripts/utils_pipeline.hpp"
-#include "/RapidPoseTriangulation/scripts/utils_2d_pose.hpp"
-#include "/RapidPoseTriangulation/rpt/interface.hpp"
 #include "/RapidPoseTriangulation/rpt/camera.hpp"
+#include "/RapidPoseTriangulation/rpt/interface.hpp"
+#include "/RapidPoseTriangulation/scripts/utils_2d_pose.hpp"
+#include "/RapidPoseTriangulation/scripts/utils_pipeline.hpp"
 
 // =================================================================================================
 
@@ -232,12 +232,12 @@ int main(int argc, char **argv)
 
         all_poses_3d.push_back(std::move(poses_3d));
         all_ids.push_back(item["id"].get<std::string>());
+        old_id = item["index"];
     }
     std::cout << std::endl;
 
     // Print timing stats
     std::cout << "\nMetrics:" << std::endl;
-    tri_model->print_stats();
     size_t warmup = 10;
     double avg_time_image = time_image / (time_count - warmup);
     double avg_time_pose2d = time_pose2d / (time_count - warmup);
@@ -249,6 +249,7 @@ int main(int argc, char **argv)
               << "  \"avg_time_3d\": " << avg_time_pose3d << ",\n"
               << "  \"fps\": " << fps << "\n"
               << "}" << std::endl;
+    tri_model->print_stats();
 
     // Store the results as json
     json all_results;

scripts/test_skelda_dataset_cpp.py

@@ -361,7 +361,7 @@ def main():
     save_json(config, config_path)
 
     # Call the CPP binary
-    os.system("/RapidPoseTriangulation/scripts/test_skelda_dataset")
+    os.system("/RapidPoseTriangulation/scripts/test_skelda_dataset.bin")
 
     # Load the results
     print("Loading exports ...")

scripts/test_skelda_dataset_py.py

@@ -330,7 +330,9 @@ def main():
 
     # Load 2D pose model
     if utils_pipeline.use_whole_body(whole_body):
-        kpt_model = utils_2d_pose.load_wb_model(min_bbox_score, min_bbox_area, batch_poses)
+        kpt_model = utils_2d_pose.load_wb_model(
+            min_bbox_score, min_bbox_area, batch_poses
+        )
     else:
         kpt_model = utils_2d_pose.load_model(min_bbox_score, min_bbox_area, batch_poses)
 
@@ -446,10 +448,7 @@ def main():
         all_ids.append(label["id"])
         times[i][2] = time_3d
 
-    # Print per-step triangulation timings
-    print("")
-    triangulator.print_stats()
-
+    # Print per-step timings
     warmup_iters = 10
     if len(times) > warmup_iters:
         times = times[warmup_iters:]
@@ -464,6 +463,7 @@ def main():
     }
     print("\nMetrics:")
     print(json.dumps(tstats, indent=2))
+    triangulator.print_stats()
 
     _ = evals.mpjpe.run_eval(
         labels,

scripts/utils_2d_pose.hpp

@@ -1,13 +1,13 @@
 #pragma once
 
 #include <filesystem>
-#include <vector>
-#include <string>
 #include <memory>
+#include <string>
+#include <vector>
 
-#include <opencv2/opencv.hpp>
 #include <onnxruntime_cxx_api.h>
 #include <onnxruntime_c_api.h>
+#include <opencv2/opencv.hpp>
 #include <tensorrt_provider_options.h>
 
 // =================================================================================================
@@ -646,27 +646,10 @@ namespace utils_2d_pose
 
     std::vector<std::array<float, 5>> RTMDet::call(const cv::Mat &image)
     {
-        auto stime = std::chrono::high_resolution_clock::now();
-        std::chrono::duration<float> elapsed;
-
         cv::Mat preprocessed = preprocess(image);
         std::vector<cv::Mat> inputs = {preprocessed};
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Preprocess time: " << elapsed.count() << "s\n";
-        stime = std::chrono::high_resolution_clock::now();
-
         auto results = call_by_image(inputs);
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Inference time: " << elapsed.count() << "s\n";
-        stime = std::chrono::high_resolution_clock::now();
-
         auto outputs = postprocess(results, image);
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Postprocess time: " << elapsed.count() << "s\n";
-
         return outputs;
     }
 
@@ -818,26 +801,9 @@ namespace utils_2d_pose
     std::vector<std::vector<std::array<float, 3>>> RTMPose::call(
         const cv::Mat &image, const std::vector<std::array<float, 5>> &bboxes)
     {
-        auto stime = std::chrono::high_resolution_clock::now();
-        std::chrono::duration<float> elapsed;
-
         std::vector<cv::Mat> inputs = preprocess(image, bboxes);
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Preprocess time: " << elapsed.count() << "s\n";
-        stime = std::chrono::high_resolution_clock::now();
-
         auto results = call_by_image(inputs);
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Inference time: " << elapsed.count() << "s\n";
-        stime = std::chrono::high_resolution_clock::now();
-
         auto outputs = postprocess(results, image, bboxes);
-
-        elapsed = std::chrono::high_resolution_clock::now() - stime;
-        std::cout << "Postprocess time: " << elapsed.count() << "s\n";
-
         return outputs;
     }
 

scripts/utils_2d_pose.py

@@ -20,6 +20,7 @@ class BaseModel(ABC):
             raise FileNotFoundError("File not found:", model_path)
 
         if model_path.endswith(".onnx"):
+            print("Loading model:", model_path)
             self.init_onnxruntime(model_path)
             self.runtime = "ort"
         else: