Refactoring for detection NN

Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>

include/tkDNN/DetectionNN.h

@@ -0,0 +1,99 @@
+#ifndef DETECTIONNN_H
+#define DETECTIONNN_H
+
+#include <iostream>
+#include <signal.h>
+#include <stdlib.h>     /* srand, rand */
+#include <unistd.h>
+#include <mutex>
+#include "utils.h"
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+#include "tkdnn.h"
+
+// #define OPENCV_CUDA //if OPENCV has been compiled with CUDA and contrib.
+
+namespace tk { namespace dnn {
+
+enum networkType_t{
+    NETWORK_YOLO3,
+    NETWORK_MOBILENETSSDLITE,
+    NETWORK_CENTERNET
+};
+
+class DetectionNN {
+
+    protected:
+        tk::dnn::NetworkRT *netRT = nullptr;
+        dnnType *input_d;
+
+        cv::Size originalSize;
+
+        cv::Scalar colors[256];
+
+#ifdef OPENCV_CUDA
+        cv::cuda::GpuMat bgr[3];
+        cv::cuda::GpuMat imagePreproc;
+#else
+        cv::Mat bgr[3];
+        cv::Mat imagePreproc;
+        dnnType *input;
+#endif
+
+    public:
+        int classes = 0;
+        float confThreshold = 0.3; /*threshold on the confidence of the boxes*/
+
+        std::vector<tk::dnn::box> detected; /*bounding boxes in output*/
+        std::vector<double> stats; /*keeps track of inference times (ms)*/
+
+        DetectionNN() {};
+        ~DetectionNN(){};
+
+        /**
+         * Method used to inialize the class, allocate memory and compute 
+         * needed data.
+         * 
+         * @param path to the rt file og the NN.
+         * @return true if everything is correct, false otherwise.
+         */
+        virtual bool init(const std::string& tensor_path, const int n_classes=80) = 0;
+        
+        /**
+         * This method preprocess the image, before feeding it to the NN.
+         *
+         * @param original frame to adapt for inference.
+         */
+        virtual void preprocess(cv::Mat &frame) = 0;
+
+        /**
+         * This method performs the inference of the NN.
+         * 
+         * @param frame to run inference on.
+         */
+        virtual void update(cv::Mat &frame) = 0;
+
+        /**
+         * This method postprocess the output of the NN to obtain the correct 
+         * boundig boxes. 
+         * 
+         * @param outputs of the inference
+         * @param number of outputs of the inference
+         */
+        virtual void postprocess(dnnType **rt_out, const int n_out) = 0;
+
+        /**
+         * Method to draw boundixg boxes and labels on a frame.
+         * 
+         * @param orginal frame to draw bounding box on.
+         * @return frame with boundig boxes.
+         */
+        virtual cv::Mat draw(cv::Mat &frame) = 0;
+};
+
+}}
+
+#endif /* DETECTIONNN_H*/