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you can find biggest contour and analyze it with Contour Approximation here my sample code that you can adopt it to python

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>

using namespace cv;
using namespace std;

static bool analyzeImage( const Mat& image )
{

    Mat gray,gray0;

    vector<vector<Point> > contours;

    cvtColor(image,gray0,COLOR_BGR2GRAY);

    gray=gray0 > 10 ;

    // find contours and store them all as a list
    findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

    for( size_t i = 0; i < contours.size(); i++ )
    {

        approxPolyDP(Mat(contours[i]), contours[i], 5, true);

        if( fabs(contourArea(Mat(contours[i]))) > image.rows*image.cols/3 )
        {
            Scalar color;
            String Message;
            if( contours[i].size() >5) // here we test if the biggest contour have 4 or more corner
            {
                color = Scalar(255,127,0);
                Message = "Dents"  ;
            }

            else
            {
                color = Scalar(0,255,0);
                Message = "No Dents"  ;
            }

            drawContours( image,contours,i, color ,2 );
            putText(image, Message, Point(image.cols/5,image.rows/2),FONT_HERSHEY_PLAIN, 2.5, CV_RGB(255,255,255), 2.0);
            imshow("image",image);
            waitKey();
            return true;
        }


    }
    return false;
}

int main( int argc, char** argv )
{

    Mat image = imread(argv[1], 1);
    if( image.empty() )
    {
        cout <<  "Could not open or find the image" << endl ;
        return -1;
    }

    if( !analyzeImage(image) );
    {
        cout <<  "Could not find any result" << endl ;
        return -1;
    }

    return 0;
}

results