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Refactoring & documentation

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Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>
This commit is contained in:
Micaela Verucchi
2020-04-08 11:20:48 +02:00
parent 326c7e0940
commit ae1d8cd9e6
9 changed files with 133 additions and 168 deletions
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src/MobilenetDetection.cpp
+6 -12
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@@ -6,8 +6,7 @@ bool boxProbCmp(const tk::dnn::box &a, const tk::dnn::box &b){
namespace tk{ namespace dnn{
void MobilenetDetection::generate_ssd_priors(const SSDSpec *specs, const int n_specs, bool clamp)
{
void MobilenetDetection::generate_ssd_priors(const SSDSpec *specs, const int n_specs, bool clamp){
nPriors = 0;
for (int i = 0; i < n_specs; i++){
nPriors += specs[i].featureSize * specs[i].featureSize * 6;
@@ -86,8 +85,7 @@ void MobilenetDetection::generate_ssd_priors(const SSDSpec *specs, const int n_s
}
}
void MobilenetDetection::convert_locatios_to_boxes_and_center()
{
void MobilenetDetection::convert_locatios_to_boxes_and_center(){
float cur_x, cur_y;
for (int i = 0; i < nPriors; i++){
locations_h[i * N_COORDS + 0] = locations_h[i * N_COORDS + 0] * centerVariance * priors[i * N_COORDS + 2] + priors[i * N_COORDS + 0];
@@ -105,8 +103,7 @@ void MobilenetDetection::convert_locatios_to_boxes_and_center()
}
}
float MobilenetDetection::iou(const tk::dnn::box &a, const tk::dnn::box &b)
{
float MobilenetDetection::iou(const tk::dnn::box &a, const tk::dnn::box &b){
float max_x = a.x > b.x ? a.x : b.x;
float max_y = a.y > b.y ? a.y : b.y;
float min_w = a.w < b.w ? a.w : b.w;
@@ -129,8 +126,7 @@ float MobilenetDetection::iou(const tk::dnn::box &a, const tk::dnn::box &b)
return iou;
}
bool MobilenetDetection::init(const std::string& tensor_path, const int n_classes)
{
bool MobilenetDetection::init(const std::string& tensor_path, const int n_classes){
std::cout<<(tensor_path).c_str()<<"\n";
netRT = new tk::dnn::NetworkRT(NULL, (tensor_path).c_str());
imageSize = netRT->input_dim.h;
@@ -207,8 +203,7 @@ bool MobilenetDetection::init(const std::string& tensor_path, const int n_classe
return 1;
}
void MobilenetDetection::preprocess(cv::Mat &frame)
{
void MobilenetDetection::preprocess(cv::Mat &frame){
#ifdef OPENCV_CUDACONTRIB
//move original image on GPU
cv::cuda::GpuMat orig_img, frame_nomean;
@@ -243,8 +238,7 @@ void MobilenetDetection::preprocess(cv::Mat &frame)
#endif
}
void MobilenetDetection::postprocess()
{
void MobilenetDetection::postprocess(){
//get confidences and locations_h
dnnType *rt_out[2];
rt_out[0] = (dnnType *)netRT->buffersRT[3];