fix return type for bool functions

include/tkDNN/SegmentationNN.h

@@ -183,6 +183,7 @@ class SegmentationNN {
 
             checkCuda(cudaMemcpyAsync(mean_d, mean.data(), mean.size() * sizeof(float), cudaMemcpyHostToDevice, netRT->stream));
             checkCuda(cudaMemcpyAsync(stddev_d, stddev.data(), stddev.size() * sizeof(float), cudaMemcpyHostToDevice, netRT->stream));
+            return true;
 
         }
         

src/CenterTrack.cpp

@@ -60,6 +60,7 @@ bool CenterTrack::init_preprocessing(){
     checkCuda( cudaMalloc(&input_d, sizeof(dnnType)*netRT->input_dim.tot() * nBatches));
     checkCuda( cudaMalloc(&input_pre_inf_d, sizeof(dnnType)*dim.tot()));
     checkCuda( cudaMalloc(&d_ptrs, dim.tot() * sizeof(float)) );
+    return true;
 }
 
 bool CenterTrack::init_pre_inf(){
@@ -203,6 +204,7 @@ bool CenterTrack::init_postprocessing(){
     trRes.resize(nBatches);
     countTr.resize(nBatches, 0);
     trackId.resize(nBatches, 0);
+    return true;
 }
 
 bool CenterTrack::init_visualization(const int n_classes){
@@ -311,7 +313,7 @@ void CenterTrack::preprocess(cv::Mat &frame, const int bi){
         }
         
         float c[] = {new_width / 2.0f, new_height /2.0f};
-        float s[] = {dim.w, dim.h};
+        float s[] = {static_cast<float>(dim.w), static_cast<float>(dim.h)};
         // float s = new_width >= new_height ? new_width : new_height;
         // ----------- get_affine_transform
         // rot_rad = pi * 0 / 100 --> 0

src/CenternetDetection.cpp

@@ -118,6 +118,7 @@ bool CenternetDetection::init(const std::string& tensor_path, const int n_classe
     
     dst2.at<float>(2,0)=dst2.at<float>(1,0) + (-dst2.at<float>(0,1)+dst2.at<float>(1,1) );
     dst2.at<float>(2,1)=dst2.at<float>(1,1) + (dst2.at<float>(0,0)-dst2.at<float>(1,0) );
+    return true;
     
 }
 

src/CenternetDetection3D.cpp

@@ -167,6 +167,7 @@ bool CenternetDetection3D::init(const std::string& tensor_path, const int n_clas
     faceId.push_back({2,3,7,6});
     faceId.push_back({3,0,4,7});
     // ([[0,1,5,4], [1,2,6, 5], [2,3,7,6], [3,0,4,7]]);
+    return true;
 }
 
 void CenternetDetection3D::preprocess(cv::Mat &frame, const int bi){