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[HELP] HOGDescriptor Error! Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

[HELP] HOGDescriptor Error! Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/objdetect/objdetect.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

click to hide/show revision 3
No.3 Revision

updated 2013-06-13 01:53:18 -0600

SR gravatar image

[HELP] HOGDescriptor Error! Error: Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/objdetect/objdetect.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

(Resolved) HOGDescriptor Error: Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/objdetect/objdetect.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

==============

edited: resolved!

I've changed...

cv::HOGDescriptor body;

to...

cv::CascadeClassifier body;

it works like a charm! it can detect the pedestrian! :)

but there's another problem, this program run slowly! SO LAGGY! :))

(Resolved) [Resolved] HOGDescriptor Error: Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/objdetect/objdetect.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

==============

edited: resolved!

I've changed...

cv::HOGDescriptor body;

to...

cv::CascadeClassifier body;

it works like a charm! it can detect the pedestrian! :)

but there's another problem, this program run slowly! SO LAGGY! :))

[Resolved] [RESOLVED] HOGDescriptor Error: Assertion Failed!

Hi, I've just added HOG Descriptor to my object detection code to tracking the pedestrian. Here we go my code:

#include"stdafx.h"
#include<vector>
#include<iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/objdetect/objdetect.hpp>

int main(int argc, char *argv[])
{
    cv::Mat frame;                                              
    cv::Mat fg;     
    cv::Mat blurred;
    cv::Mat thresholded;
    cv::Mat gray;
    cv::Mat blob;
    cv::Mat bgmodel;                                            
    cv::namedWindow("Frame");   
    cv::namedWindow("Background Model");
    cv::namedWindow("Blob");
    cv::VideoCapture cap("campus3.avi");    

    cv::BackgroundSubtractorMOG2 bgs;                           

        bgs.nmixtures = 3;
        bgs.history = 1000;
        bgs.varThresholdGen = 15;
        bgs.bShadowDetection = true;                            
        bgs.nShadowDetection = 0;                               
        bgs.fTau = 0.5;                                         

    std::vector<std::vector<cv::Point>> contours;               

    cv::HOGDescriptor human;
    assert(human.load("hogcascade_pedestrians.xml"));

    for(;;)
    {
        cap >> frame;                                           

        cv::GaussianBlur(frame,blurred,cv::Size(3,3),0,0,cv::BORDER_DEFAULT);

        bgs.operator()(blurred,fg);                         
        bgs.getBackgroundImage(bgmodel);                                

        cv::threshold(fg,thresholded,70.0f,255,CV_THRESH_BINARY);

        cv::Mat elementCLOSE(5,5,CV_8U,cv::Scalar(255,255,255));
        cv::morphologyEx(thresholded,thresholded,cv::MORPH_CLOSE,elementCLOSE);

        cv::findContours(thresholded,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);
        cv::cvtColor(thresholded,blob,CV_GRAY2RGB);
        cv::drawContours(blob,contours,-1,cv::Scalar(1),CV_FILLED,8);

        cv::cvtColor(frame,gray,CV_RGB2GRAY);
        cv::equalizeHist(gray, gray);

        int cmin = 50; 
        int cmax = 1000;
        std::vector<cv::Rect> rects;
        std::vector<std::vector<cv::Point>>::iterator itc=contours.begin();

        while (itc!=contours.end()) {   

                if (itc->size() > cmin && itc->size() < cmax){ 

                        human.detectMultiScale(gray, rects);
                        for (unsigned int i=0;i<rects.size();i++) {
                            cv::rectangle(frame, cv::Point(rects[i].x, rects[i].y),
                            cv::Point(rects[i].x+rects[i].width, rects[i].y+rects[i].height),
                            cv::Scalar(0, 255, 0));
                         }

                        ++itc;
                    }else{++itc;}
        }

        cv::imshow("Frame",frame);
        cv::imshow("Background Model",bgmodel);
        cv::imshow("Blob",blob);
        if(cv::waitKey(30) >= 0) break;
    }
    return 0;
}

On my code, I minimize the area using findcontours and make the area bigger than the object using morphologyEX (Close) and then I'm using HOGDescriptors.detectMultiScale to detect human in the contours area. But I've got the error message when I run the program. This is my error message:

"OpenCV Error: Assertion failed (dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0)) in unknown function, file C:\OpenCV\modules\imgproc\src\imgwarp.cpp, line 1726"

I've tried to detectMultiScale directly without findcontours but the same error message happened to me! So how to resolve this problems?

I'll appreciate any help here. Thanks! :)

==============

edited: resolved!

I've changed...

cv::HOGDescriptor body;

to...

cv::CascadeClassifier body;

it works like a charm! it can detect the pedestrian! :)

but there's another problem, this program run slowly! SO LAGGY! :))