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Add the calibration matrix reading for CenterTrack

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
This commit is contained in:
Davide Sapienza
2021-04-30 17:10:51 +02:00
parent be6ad27c11
commit 2367519799
6 changed files with 75 additions and 44 deletions
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include/tkDNN/CenternetDetection3D.h
+2 -2
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@@ -82,8 +82,8 @@ public:
CenternetDetection3D() {};
~CenternetDetection3D() {};
bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3);
void preprocess(cv::Mat &frame, const int bi=0);
bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3, const std::vector<cv::Mat>& k_calibs=std::vector<cv::Mat>());
void preprocess(cv::Mat &frame, const int bi=0, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>());
void postprocess(const int bi=0,const bool mAP=false);
void draw(std::vector<cv::Mat>& frames);
};
include/tkDNN/CenternetDetection3DTrack.h
+7 -3
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@@ -74,6 +74,10 @@ private:
#endif
float *d_ptrs;
std::vector<cv::Mat> inputCalibs;
std::vector<cv::Size> sz_old;
cv::Mat src;
cv::Mat dst;
cv::Mat dst2;
@@ -124,7 +128,7 @@ private:
/* visualization */
cv::Mat r;
cv::Mat calibs;
std::vector<cv::Mat> calibs;
cv::Mat corners, pts3DHomo;
std::vector<std::vector<int>> face_id;
@@ -163,8 +167,8 @@ public:
tk::dnn::Network *pre_phase_net = nullptr;
CenternetDetection3DTrack() {};
~CenternetDetection3DTrack() {};
bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3);
void preprocess(cv::Mat &frame, const int bi=0);
bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3, const std::vector<cv::Mat>& k_calibs=std::vector<cv::Mat>());
void preprocess(cv::Mat &frame, const int bi=0, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>());
void postprocess(const int bi=0,const bool mAP=false);
void draw(std::vector<cv::Mat>& frames);
};
include/tkDNN/DetectionNN3D.h
+6 -4
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@@ -54,7 +54,7 @@ class DetectionNN3D {
* @param frame original frame to adapt for inference.
* @param bi batch index
*/
virtual void preprocess(cv::Mat &frame, const int bi=0) = 0;
virtual void preprocess(cv::Mat &frame, const int bi=0 , const std::vector<cv::Size>& stream_size=std::vector<cv::Size>()) = 0;
/**
* This method postprocess the output of the NN to obtain the correct
@@ -87,7 +87,8 @@ class DetectionNN3D {
* @param n_batches maximum number of batches to use in inference.
* @return true if everything is correct, false otherwise.
*/
virtual bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3) = 0;
virtual bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1,
const float conf_thresh=0.3, const std::vector<cv::Mat>& k_calibs=std::vector<cv::Mat>()) = 0;
/**
* This method performs the whole detection of the NN.
@@ -100,7 +101,8 @@ class DetectionNN3D {
* @param mAP set to true only if all the probabilities for a bounding
* box are needed, as in some cases for the mAP calculation.
*/
void update(std::vector<cv::Mat>& frames, const int cur_batches=1, bool save_times=false, std::ofstream *times=nullptr, const bool mAP=false){
void update(std::vector<cv::Mat>& frames, const int cur_batches=1, bool save_times=false,
std::ofstream *times=nullptr, const bool mAP=false, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>()){
if(save_times && times==nullptr)
FatalError("save_times set to true, but no valid ofstream given");
if(cur_batches > nBatches)
@@ -114,7 +116,7 @@ class DetectionNN3D {
if(!frames[bi].data)
FatalError("No image data feed to detection");
originalSize.push_back(frames[bi].size());
preprocess(frames[bi], bi);
preprocess(frames[bi], bi, stream_size);
}
TKDNN_TSTOP
pre_stats.push_back(t_ns);