Anton Kuzhelev

data/squeezenet1.1.labels

@@ -997,4 +997,4 @@ earthstar
 hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa
 bolete
 ear, spike, capitulum
-toilet tissue, toilet paper, bathroom tissue
+toilet tissue, toilet paper, bathroom tissue

include/classificator.h

@@ -16,4 +16,15 @@ class Classificator
 public:
     vector<string> classesNames;
     virtual Mat Classify(Mat image) = 0 {}
+};
+
+class DnnClassificator :public Classificator {
+	string path_to_model, path_to_config, path_to_labels;
+	int width, height;
+	Scalar mean;
+	bool swap;
+	Net net;
+public:
+	DnnClassificator(string ptm, string ptc, string ptl, int nwidth, int nheight, Scalar nmean = (0, 0, 0, 0), bool srb = 0);
+	Mat Classify(Mat image);
 };

include/tracking_by_matching.hpp

@@ -57,6 +57,7 @@ using TrackedObjects = std::deque<TrackedObject>;
 bool operator==(const TrackedObject& first, const TrackedObject& second);
 bool operator!=(const TrackedObject& first, const TrackedObject& second);
 /// (object id, detected objects) pairs collection.
+
 using ObjectTracks = std::unordered_map<int, TrackedObjects>;
 
 ///

samples/practice1_Anton.cpp

@@ -0,0 +1,63 @@
+#include <iostream>
+#include <string>
+
+#include <opencv2/imgproc.hpp>
+#include <opencv2/highgui.hpp>
+
+#include "filter.h"
+
+using namespace cv;
+using namespace std;
+
+const char* cmdAbout = "Sample of OpenCV usage. ";
+
+const char* cmdOptions =
+"{ i  image         | <none> | image to process        }"
+"{ w  width         | <none> | width for image resize  }"
+"{ f filter         | <none> | G - gray, R - resize    }"
+"{ h  height        | <none> | height for image resize }"
+"{ q ? help usage   | <none> | print help message      }";
+
+int main(int argc, char** argv)
+{
+    // Process input arguments
+    CommandLineParser parser(argc, argv, cmdOptions);
+    parser.about(cmdAbout);
+	string filter;
+    if (parser.has("help"))
+    {
+        parser.printMessage();
+        return 0;
+    }
+    if (!parser.check())
+    {
+        parser.printErrors();
+        return 0;
+    }
+	if (parser.has("filter")) {
+		filter = parser.get<string>("filter");
+	}
+
+    // Load image
+    String imgName(parser.get<String>("image"));
+	cv::Mat src;
+	src = imread(imgName, 1);
+
+
+    // Filter image
+	if (filter.find('g') != string::npos) {
+		GrayFilter f;
+		src = f.ProcessImage(src);
+	}
+	if (filter.find('r') != string::npos) {
+		ResizeFilter filt(parser.get<int>("width"), parser.get<int>("height"));
+		src = filt.ProcessImage(src);
+	}
+    // Show image
+	cv::imshow("image", src);
+	cv::waitKey();
+
+
+
+    return 0;
+}

samples/practice2_Anton.cpp

@@ -0,0 +1,78 @@
+#include <iostream>
+#include <fstream>
+#include <string>
+#include <set>
+
+#include <opencv2/imgproc.hpp>
+#include <opencv2/highgui.hpp>
+
+#include "classificator.h"
+
+using namespace cv;
+using namespace std;
+
+const char* cmdAbout = "Sample of OpenCV usage. ";
+
+const char* cmdOptions =
+"{ i  image                             | <none> | image to process                  }"
+"{ w  width                             |        | image width for classification    }"
+"{ h  heigth                            |        | image heigth for classification   }"
+"{ model_path                           |        | path to model                     }"
+"{ config_path                          |        | path to model configuration       }"
+"{ label_path                           |        | path to class labels              }"
+"{ mean                                 |        | vector of mean model values       }"
+"{ swap                                 |        | swap R and B channels. TRUE|FALSE }"
+"{ q ? help usage                       |        | print help message                }";
+
+int main(int argc, char** argv)
+{
+	// Process input arguments
+	CommandLineParser parser(argc, argv, cmdOptions);
+	parser.about(cmdAbout);
+
+	if (parser.has("help"))
+	{
+		parser.printMessage();
+		return 0;
+	}
+	if (!parser.check())
+	{
+		parser.printErrors();
+		return 0;
+	}
+
+	// Load image and init parameters
+	String imgName(parser.get<String>("image"));
+	cv::Mat src;
+	src = imread(imgName);
+//	cv::imshow("image",src);
+	//waitKey();
+
+	//Image classification
+	string mp = parser.get<string>("model_path");
+	string cp = parser.get<string>("config_path");
+	string lp = parser.get<string>("label_path");
+	int wid = parser.get<int>("width");
+	int hei = parser.get<int>("heigth");
+	Scalar me = parser.get<Scalar>("mean");
+	int sw = parser.get<int>("swap");
+	Point classIdPoint;
+	double confidence;
+	DnnClassificator ds(mp, cp, lp, wid,hei, me, sw);
+	Mat res = ds.Classify(src);
+	minMaxLoc(res, 0, &confidence, 0, &classIdPoint);
+	int classId = classIdPoint.x;
+
+	//Show result
+
+	/*ifstream ifs("labels.labels");
+	int s = 0;
+	while (s <= classId || !ifs.eof())s++;
+	string buff;
+	getline(ifs, buff);*/
+	cout << "Class:" << classId<< endl;
+	cout << "Confidence:" << confidence << endl;
+
+
+	return 0;
+}