1 files changed, 16 insertions, 26 deletions
diff --git a/source/application/api/use_case/object_detection/src/DetectorPostProcessing.cc b/source/application/api/use_case/object_detection/src/DetectorPostProcessing.cc
index 7610c4f..f555fbb 100644
--- a/source/application/api/use_case/object_detection/src/DetectorPostProcessing.cc
+++ b/source/application/api/use_case/object_detection/src/DetectorPostProcessing.cc
@@ -26,31 +26,21 @@ namespace app {
         TfLiteTensor* modelOutput0,
         TfLiteTensor* modelOutput1,
         std::vector<object_detection::DetectionResult>& results,
-        int inputImgRows,
-        int inputImgCols,
-        const float threshold,
-        const float nms,
-        int numClasses,
-        int topN)
+        const object_detection::PostProcessParams& postProcessParams)
         :   m_outputTensor0{modelOutput0},
             m_outputTensor1{modelOutput1},
             m_results{results},
-            m_inputImgRows{inputImgRows},
-            m_inputImgCols{inputImgCols},
-            m_threshold(threshold),
-            m_nms(nms),
-            m_numClasses(numClasses),
-            m_topN(topN)
+            m_postProcessParams{postProcessParams}
 {
     /* Init PostProcessing */
     this->m_net = object_detection::Network{
-        .inputWidth  = inputImgCols,
-        .inputHeight = inputImgRows,
-        .numClasses  = numClasses,
+        .inputWidth  = postProcessParams.inputImgCols,
+        .inputHeight = postProcessParams.inputImgRows,
+        .numClasses  = postProcessParams.numClasses,
         .branches =
-            {object_detection::Branch{.resolution  = inputImgCols / 32,
+            {object_detection::Branch{.resolution  = postProcessParams.inputImgCols / 32,
                                       .numBox      = 3,
-                                      .anchor      = arm::app::object_detection::anchor1,
+                                      .anchor      = postProcessParams.anchor1,
                                       .modelOutput = this->m_outputTensor0->data.int8,
                                       .scale       = (static_cast<TfLiteAffineQuantization*>(
                                                     this->m_outputTensor0->quantization.params))
@@ -59,9 +49,9 @@ namespace app {
                                                         this->m_outputTensor0->quantization.params))
                                                        ->zero_point->data[0],
                                       .size = this->m_outputTensor0->bytes},
-             object_detection::Branch{.resolution  = inputImgCols / 16,
+             object_detection::Branch{.resolution  = postProcessParams.inputImgCols / 16,
                                       .numBox      = 3,
-                                      .anchor      = arm::app::object_detection::anchor2,
+                                      .anchor      = postProcessParams.anchor2,
                                       .modelOutput = this->m_outputTensor1->data.int8,
                                       .scale       = (static_cast<TfLiteAffineQuantization*>(
                                                     this->m_outputTensor1->quantization.params))
@@ -70,21 +60,21 @@ namespace app {
                                                         this->m_outputTensor1->quantization.params))
                                                        ->zero_point->data[0],
                                       .size = this->m_outputTensor1->bytes}},
-        .topN = m_topN};
+        .topN = postProcessParams.topN};
     /* End init */
 }
 
 bool DetectorPostProcess::DoPostProcess()
 {
     /* Start postprocessing */
-    int originalImageWidth  = arm::app::object_detection::originalImageSize;
-    int originalImageHeight = arm::app::object_detection::originalImageSize;
+    int originalImageWidth  = m_postProcessParams.originalImageSize;
+    int originalImageHeight = m_postProcessParams.originalImageSize;
 
     std::forward_list<image::Detection> detections;
-    GetNetworkBoxes(this->m_net, originalImageWidth, originalImageHeight, m_threshold, detections);
+    GetNetworkBoxes(this->m_net, originalImageWidth, originalImageHeight, m_postProcessParams.threshold, detections);
 
     /* Do nms */
-    CalculateNMS(detections, this->m_net.numClasses, m_nms);
+    CalculateNMS(detections, this->m_net.numClasses, this->m_postProcessParams.nms);
 
     for (auto& it: detections) {
         float xMin = it.bbox.x - it.bbox.w / 2.0f;
@@ -219,10 +209,10 @@ void DetectorPostProcess::GetNetworkBoxes(
                             num += 1;
                         } else if (num == net.topN) {
                             detections.sort(det_objectness_comparator);
-                            InsertTopNDetections(detections,det);
+                            InsertTopNDetections(detections, det);
                             num += 1;
                         } else {
-                            InsertTopNDetections(detections,det);
+                            InsertTopNDetections(detections, det);
                         }
                     }
                 }