diff --git a/include/detection.hpp b/include/detection.hpp
index 46930d3..afa107f 100644
--- a/include/detection.hpp
+++ b/include/detection.hpp
@@ -2,8 +2,8 @@
 
 #include <memory>
 #include <string>
-
 #include "opencv2/core/core.hpp"
+#include "opencv2/objdetect.hpp"
 
 class Detector {
  public:
@@ -12,3 +12,12 @@ class Detector {
   virtual void Detect(const cv::Mat& frame, std::vector<cv::Rect>& objects,
                       std::vector<double>& scores) = 0;
 };
+
+class CascadeDetector : public Detector
+{
+	public:
+	cv::CascadeClassifier ccdetector;
+	virtual bool Init(const std::string& model_file_path);
+	virtual void Detect(const cv::Mat& frame, std::vector<cv::Rect>& objects,
+		std::vector<double>& scores);
+};
\ No newline at end of file
diff --git a/samples/detection_demo.cpp b/samples/detection_demo.cpp
new file mode 100644
index 0000000..e012476
--- /dev/null
+++ b/samples/detection_demo.cpp
@@ -0,0 +1,122 @@
+#include <iostream>
+#include <string>
+
+#include "opencv2/core/core.hpp"
+#include "opencv2/opencv.hpp"
+
+#include "detection.hpp"
+
+using namespace std;
+using namespace cv;
+
+const char* kAbout =
+    "detection app";
+
+const char* kOptions =
+"{ i image        | <none> | image to process                         }"
+"{ v video        | <none> | video to process                         }"
+"{ c camera       | <none> | camera to get video from                 }"
+"{ m model        | <none> | path to detector file                    }"
+"{ h ? help usage |        | print help message                       }";
+
+int main(int argc, const char** argv) {
+  // Parse command line arguments.
+  CommandLineParser parser(argc, argv, kOptions);
+  parser.about(kAbout);
+
+  // If help option is given, print help message and exit.
+  if (parser.get<bool>("help")) {
+    parser.printMessage();
+    return 0;
+  }
+
+  // init
+  std::string vidName, imgName, detectName;
+  Mat frame;
+  CascadeDetector obj;
+  std::vector<Rect> logos;
+  std::vector<double> scores;
+  VideoCapture capture;
+  //
+ 
+  if (parser.has("m"))
+  {
+	  detectName = parser.get<string>("m");
+	  cout << detectName << endl;
+	  obj.Init(detectName);
+  }
+  
+  if (parser.has("i"))
+  {
+	  imgName = parser.get<std::string>("i");
+	  frame = imread(imgName);
+	  imshow("Detection", frame);
+	  obj.Detect(frame, logos, scores);
+	  if (scores.size() > 0)
+		  for (int i = 0; i < logos.size(); i++)
+		  {
+			  rectangle(frame, logos[i], Scalar(255, 0, 0));
+			  imshow("Detection", frame);
+		  }
+	  else
+		  std::cout << "objects haven`t been detected";
+  }
+  else
+  {
+	  if (parser.has("v"))
+	  {		
+		  vidName = parser.get<std::string>("v");
+		  
+		  bool flag = capture.open(vidName);
+		  
+		  if (flag)
+		  {	
+			  flag = capture.read(frame);
+			  while (true)
+			  {
+				 if (frame.empty())
+					 {
+						 cout << " --(!) No captured frame -- Break!";
+						 break;
+					 }
+				 //Apply the classifier to the frame
+			     obj.Detect(frame, logos, scores);
+				 if (scores.size()> 0)
+		        	 for(int i = 0; i < logos.size(); i++)
+	   					rectangle(frame, logos[i], Scalar(255, 0, 0));
+                 imshow("Detection", frame);
+			     capture >> frame;
+				 int c = cv::waitKey(100);
+			     if ((char)c == 27) break;  // escape	
+			  }
+			  capture.release();
+		  }
+		  else
+			  cout << "--(!)Error opening video capture" << endl ;
+		  
+	  }
+	  else
+		  if (parser.has("c"))
+		  {
+			  capture.open(0);
+			  if (!capture.isOpened())
+				   return 0;
+			  capture.read(frame);
+			  for (;;)
+			  {	
+				  obj.Detect(frame, logos, scores);
+				  if (scores.size() > 0)
+					  for (int i = 0; i < logos.size(); i++)
+						  rectangle(frame, logos[i], Scalar(255, 0, 0));
+				  capture >> frame;
+				  if (frame.empty()) break; // end of video stream
+				  imshow("Web", frame);
+				  if (waitKey(10) == 27) break; // stop capturing by pressing ESC 
+			  }
+			  capture.release();
+		  }
+  }
+  cv::waitKey(0);
+
+  return 0;
+}
diff --git a/samples/devtools_demo.cpp b/samples/devtools_demo.cpp
deleted file mode 100644
index 8c40769..0000000
--- a/samples/devtools_demo.cpp
+++ /dev/null
@@ -1,64 +0,0 @@
-#include <iostream>
-#include <string>
-
-#include "opencv2/core.hpp"
-#include "opencv2/highgui.hpp"
-
-#include "workaround.hpp"
-
-using namespace std;
-using namespace cv;
-
-const char* kAbout = "Application for practice #1.";
-
-const char* kOptions =
-    "{ @image         |        | image to process         }"
-    "{ t              |  128   | threshold                }"
-    "{ h ? help usage |        | print help message       }";
-
-int main(int argc, const char** argv) {
-  // Parse command line arguments.
-  CommandLineParser parser(argc, argv, kOptions);
-  parser.about(kAbout);
-
-  // If help option is given, print help message and exit.
-  if (parser.has("help")) {
-    parser.printMessage();
-    return 0;
-  }
-
-  // Read image.
-  Mat src = imread(parser.get<string>(0), CV_LOAD_IMAGE_GRAYSCALE);
-  if (src.empty()) {
-    cout << "Failed to open image file '" + parser.get<string>(0) + "'."
-         << endl;
-    return 0;
-  }
-
-  // Show source image.
-  const string kSrcWindowName = "Source image";
-  const int kWaitKeyDelay = 1;
-  namedWindow(kSrcWindowName, WINDOW_NORMAL);
-  resizeWindow(kSrcWindowName, 640, 480);
-  imshow(kSrcWindowName, src);
-  waitKey(kWaitKeyDelay);
-
-  // Threshold data.
-  MatrixProcessor processor;
-  const int threshold = parser.get<int>("t");
-  try {
-    processor.Threshold(src.data, src.cols, src.rows, threshold);
-  } catch (const std::exception& ex) {
-    cout << ex.what() << endl;
-    return 0;
-  }
-
-  // Show destination image.
-  const string kDstWindowName = "Destination image";
-  namedWindow(kDstWindowName, WINDOW_NORMAL);
-  resizeWindow(kDstWindowName, 640, 480);
-  imshow(kDstWindowName, src);
-  waitKey();
-
-  return 0;
-}
diff --git a/samples/template_demo.cpp b/samples/template_demo.cpp
deleted file mode 100644
index 3b9eb74..0000000
--- a/samples/template_demo.cpp
+++ /dev/null
@@ -1,33 +0,0 @@
-#include <iostream>
-#include <string>
-
-#include "opencv2/core.hpp"
-
-using namespace std;
-using namespace cv;
-
-const char* kAbout =
-    "This is an empty application that can be treated as a template for your "
-    "own doing-something-cool applications.";
-
-const char* kOptions =
-    "{ v video        |        | video to process         }"
-    "{ h ? help usage |        | print help message       }";
-
-
-int main(int argc, const char** argv) {
-  // Parse command line arguments.
-  CommandLineParser parser(argc, argv, kOptions);
-  parser.about(kAbout);
-
-  // If help option is given, print help message and exit.
-  if (parser.get<bool>("help")) {
-    parser.printMessage();
-    return 0;
-  }
-
-  // Do something cool.
-  cout << "This is empty template sample." << endl;
-
-  return 0;
-}
diff --git a/src/detection.cpp b/src/detection.cpp
index 15e7fd1..855ae0c 100644
--- a/src/detection.cpp
+++ b/src/detection.cpp
@@ -1,13 +1,40 @@
 #include "detection.hpp"
 
-#include <iostream>
-
 using std::string;
 using std::shared_ptr;
 using namespace cv;
 
-shared_ptr<Detector> Detector::CreateDetector(const string& name) {
-  std::cerr << "Failed to create detector with name '" << name << "'"
-            << std::endl;
-  return nullptr;
+shared_ptr<Detector> Detector::CreateDetector(const string& name) 
+{
+	if (name == "cascade")
+	{
+		return std::make_shared<CascadeDetector>();
+	}
+	else
+		return nullptr;
+
+}
+
+bool CascadeDetector::Init(const std::string & model_file_path)
+{
+	bool flag = false;
+	if (ccdetector.load(model_file_path))
+		flag = true;
+	return flag;
+}
+
+void CascadeDetector::Detect(const cv::Mat & frame, std::vector<cv::Rect>& ccdetectorects,
+	std::vector<double>& scores)
+{
+	std::vector<int> numDetections;
+
+	if (ccdetector.empty()) return ;
+	if (frame.empty()) throw "Matrix is empty";
+
+	//ccdetectorects.clear();
+
+	ccdetector.detectMultiScale(frame, ccdetectorects, numDetections);
+	
+	scores.assign(numDetections.begin(), numDetections.end());
+
 }
diff --git a/training_logo/cascade.xml b/training_logo/cascade.xml
new file mode 100644
index 0000000..c426d6d
--- /dev/null
+++ b/training_logo/cascade.xml
@@ -0,0 +1,186 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<cascade>
+  <stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>32</height>
+  <width>32</width>
+  <stageParams>
+    <boostType>GAB</boostType>
+    <minHitRate>9.9500000476837158e-01</minHitRate>
+    <maxFalseAlarm>1.0000000149011612e-01</maxFalseAlarm>
+    <weightTrimRate>9.4999999999999996e-01</weightTrimRate>
+    <maxDepth>1</maxDepth>
+    <maxWeakCount>100</maxWeakCount></stageParams>
+  <featureParams>
+    <maxCatCount>0</maxCatCount>
+    <featSize>1</featSize>
+    <mode>BASIC</mode></featureParams>
+  <stageNum>4</stageNum>
+  <stages>
+    <!-- stage 0 -->
+    <_>
+      <maxWeakCount>1</maxWeakCount>
+      <stageThreshold>9.7528421878814697e-01</stageThreshold>
+      <weakClassifiers>
+        <_>
+          <internalNodes>
+            0 -1 10 4.0812580846250057e-03</internalNodes>
+          <leafValues>
+            -9.9797672033309937e-01 9.7528421878814697e-01</leafValues></_></weakClassifiers></_>
+    <!-- stage 1 -->
+    <_>
+      <maxWeakCount>2</maxWeakCount>
+      <stageThreshold>-7.0796445012092590e-02</stageThreshold>
+      <weakClassifiers>
+        <_>
+          <internalNodes>
+            0 -1 8 -3.7780940532684326e-02</internalNodes>
+          <leafValues>
+            9.3385213613510132e-01 -9.8765432834625244e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 7 2.7387058362364769e-03</internalNodes>
+          <leafValues>
+            -9.4651961326599121e-01 9.1685789823532104e-01</leafValues></_></weakClassifiers></_>
+    <!-- stage 2 -->
+    <_>
+      <maxWeakCount>4</maxWeakCount>
+      <stageThreshold>-1.6588573157787323e-01</stageThreshold>
+      <weakClassifiers>
+        <_>
+          <internalNodes>
+            0 -1 4 3.4338846802711487e-02</internalNodes>
+          <leafValues>
+            -9.0086209774017334e-01 7.7985072135925293e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 9 -1.1945048347115517e-02</internalNodes>
+          <leafValues>
+            8.0718630552291870e-01 -8.6200785636901855e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 11 -3.9666537195444107e-03</internalNodes>
+          <leafValues>
+            8.0437922477722168e-01 -8.1469124555587769e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 2 -9.5642581582069397e-03</internalNodes>
+          <leafValues>
+            7.4248123168945313e-01 -8.1557685136795044e-01</leafValues></_></weakClassifiers></_>
+    <!-- stage 3 -->
+    <_>
+      <maxWeakCount>5</maxWeakCount>
+      <stageThreshold>-5.8510094881057739e-02</stageThreshold>
+      <weakClassifiers>
+        <_>
+          <internalNodes>
+            0 -1 6 7.1976799517869949e-03</internalNodes>
+          <leafValues>
+            -8.5774058103561401e-01 7.8544062376022339e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 1 1.7477976158261299e-02</internalNodes>
+          <leafValues>
+            -8.3842450380325317e-01 6.1052769422531128e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 3 -5.3416676819324493e-03</internalNodes>
+          <leafValues>
+            4.8253062367439270e-01 -9.9687421321868896e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 0 1.4424304477870464e-02</internalNodes>
+          <leafValues>
+            -7.6333725452423096e-01 7.3217594623565674e-01</leafValues></_>
+        <_>
+          <internalNodes>
+            0 -1 5 -5.0397003069519997e-03</internalNodes>
+          <leafValues>
+            4.6950939297676086e-01 -9.3885457515716553e-01</leafValues></_></weakClassifiers></_></stages>
+  <features>
+    <_>
+      <rects>
+        <_>
+          1 10 6 13 -1.</_>
+        <_>
+          3 10 2 13 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          2 20 24 3 -1.</_>
+        <_>
+          10 20 8 3 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          6 13 6 6 -1.</_>
+        <_>
+          8 13 2 6 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          7 11 10 8 -1.</_>
+        <_>
+          12 11 5 8 2.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          12 6 10 9 -1.</_>
+        <_>
+          12 9 10 3 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          12 9 18 2 -1.</_>
+        <_>
+          21 9 9 2 2.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          12 15 3 2 -1.</_>
+        <_>
+          13 15 1 2 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          12 16 3 1 -1.</_>
+        <_>
+          13 16 1 1 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          14 9 5 15 -1.</_>
+        <_>
+          14 14 5 5 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          14 20 5 6 -1.</_>
+        <_>
+          14 23 5 3 2.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          15 15 3 2 -1.</_>
+        <_>
+          16 15 1 2 3.</_></rects>
+      <tilted>0</tilted></_>
+    <_>
+      <rects>
+        <_>
+          15 17 2 3 -1.</_>
+        <_>
+          15 18 2 1 3.</_></rects>
+      <tilted>0</tilted></_></features></cascade>
+</opencv_storage>
diff --git a/training_logo/params.xml b/training_logo/params.xml
new file mode 100644
index 0000000..cd15c34
--- /dev/null
+++ b/training_logo/params.xml
@@ -0,0 +1,19 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<params>
+  <stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>32</height>
+  <width>32</width>
+  <stageParams>
+    <boostType>GAB</boostType>
+    <minHitRate>9.9500000476837158e-01</minHitRate>
+    <maxFalseAlarm>1.0000000149011612e-01</maxFalseAlarm>
+    <weightTrimRate>9.4999999999999996e-01</weightTrimRate>
+    <maxDepth>1</maxDepth>
+    <maxWeakCount>100</maxWeakCount></stageParams>
+  <featureParams>
+    <maxCatCount>0</maxCatCount>
+    <featSize>1</featSize>
+    <mode>BASIC</mode></featureParams></params>
+</opencv_storage>
diff --git a/training_logo/stage0.xml b/training_logo/stage0.xml
new file mode 100644
index 0000000..76acb3a
--- /dev/null
+++ b/training_logo/stage0.xml
@@ -0,0 +1,12 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<stage0>
+  <maxWeakCount>1</maxWeakCount>
+  <stageThreshold>9.7528421878814697e-01</stageThreshold>
+  <weakClassifiers>
+    <_>
+      <internalNodes>
+        0 -1 377013 4.0812580846250057e-03</internalNodes>
+      <leafValues>
+        -9.9797672033309937e-01 9.7528421878814697e-01</leafValues></_></weakClassifiers></stage0>
+</opencv_storage>
diff --git a/training_logo/stage1.xml b/training_logo/stage1.xml
new file mode 100644
index 0000000..9b1b1fe
--- /dev/null
+++ b/training_logo/stage1.xml
@@ -0,0 +1,17 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<stage1>
+  <maxWeakCount>2</maxWeakCount>
+  <stageThreshold>-7.0796445012092590e-02</stageThreshold>
+  <weakClassifiers>
+    <_>
+      <internalNodes>
+        0 -1 356598 -3.7780940532684326e-02</internalNodes>
+      <leafValues>
+        9.3385213613510132e-01 -9.8765432834625244e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 324572 2.7387058362364769e-03</internalNodes>
+      <leafValues>
+        -9.4651961326599121e-01 9.1685789823532104e-01</leafValues></_></weakClassifiers></stage1>
+</opencv_storage>
diff --git a/training_logo/stage2.xml b/training_logo/stage2.xml
new file mode 100644
index 0000000..b9d59f4
--- /dev/null
+++ b/training_logo/stage2.xml
@@ -0,0 +1,27 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<stage2>
+  <maxWeakCount>4</maxWeakCount>
+  <stageThreshold>-1.6588573157787323e-01</stageThreshold>
+  <weakClassifiers>
+    <_>
+      <internalNodes>
+        0 -1 317326 3.4338846802711487e-02</internalNodes>
+      <leafValues>
+        -9.0086209774017334e-01 7.7985072135925293e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 363124 -1.1945048347115517e-02</internalNodes>
+      <leafValues>
+        8.0718630552291870e-01 -8.6200785636901855e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 378057 -3.9666537195444107e-03</internalNodes>
+      <leafValues>
+        8.0437922477722168e-01 -8.1469124555587769e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 189290 -9.5642581582069397e-03</internalNodes>
+      <leafValues>
+        7.4248123168945313e-01 -8.1557685136795044e-01</leafValues></_></weakClassifiers></stage2>
+</opencv_storage>
diff --git a/training_logo/stage3.xml b/training_logo/stage3.xml
new file mode 100644
index 0000000..0600f91
--- /dev/null
+++ b/training_logo/stage3.xml
@@ -0,0 +1,32 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<stage3>
+  <maxWeakCount>5</maxWeakCount>
+  <stageThreshold>-5.8510094881057739e-02</stageThreshold>
+  <weakClassifiers>
+    <_>
+      <internalNodes>
+        0 -1 323965 7.1976799517869949e-03</internalNodes>
+      <leafValues>
+        -8.5774058103561401e-01 7.8544062376022339e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 87119 1.7477976158261299e-02</internalNodes>
+      <leafValues>
+        -8.3842450380325317e-01 6.1052769422531128e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 212211 -5.3416676819324493e-03</internalNodes>
+      <leafValues>
+        4.8253062367439270e-01 -9.9687421321868896e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 47236 1.4424304477870464e-02</internalNodes>
+      <leafValues>
+        -7.6333725452423096e-01 7.3217594623565674e-01</leafValues></_>
+    <_>
+      <internalNodes>
+        0 -1 319968 -5.0397003069519997e-03</internalNodes>
+      <leafValues>
+        4.6950939297676086e-01 -9.3885457515716553e-01</leafValues></_></weakClassifiers></stage3>
+</opencv_storage>