You can achieve it simply by using minAreaRect. Which I also used the same method in this answer of me. I coded in C++ because my environment based on C++. Converting to Python is not a big issue. Here is my code and results:
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
#include <string>
using namespace cv;
using namespace std;
int main()
{
Mat src; Mat src_gray;
RNG rng(12345);
int counter = 0;
/// Load source image and convert it to gray
src = imread( "/ur/image/directory/Python-Interview.jpg", 1 );
Mat original = src.clone();
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
imshow("dd",src_gray);
Mat threshold_output;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
/// Detect edges using Threshold
threshold( src_gray, threshold_output, 138, 100, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Find the rotated rectangles for each contour
vector<RotatedRect> minRect( contours.size() );
for( int i = 0; i < contours.size(); i++ )
minRect[i] = minAreaRect( Mat(contours[i]) );
/// Draw contours + rotated rects
Mat drawing = Mat::zeros( threshold_output.size(), CV_8UC3 );
Mat result_zero = Mat::zeros( threshold_output.size(), CV_8UC3 );
for( int i = 0; i< contours.size(); i++ )
{
Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
// detect contours
drawContours( drawing, contours, i, color, 1, 8, vector<Vec4i>(), 0, Point() );
// detect rectangle for each contour
Point2f rect_points[4]; minRect[i].points( rect_points );
double length_1 = cv::norm(cv::Mat(rect_points[0]),cv::Mat(rect_points[1]));
double length_2 = cv::norm(cv::Mat(rect_points[1]),cv::Mat(rect_points[2]));
int temp1 = (int)length_1;
int temp2 = (int)length_2;
//25 and 35 are the pixel lengths of those small rectangles. By using this if scope I am filtering them
if(temp1>25 && temp1<35 && temp2>25 && temp2<35 )
{
int min_x = rect_points[0].x;
int min_y = rect_points[0].y;
for( int j = 0; j < 4; j++ )
{
if(rect_points[j].x<min_x)
min_x = rect_points[j].x;
if(rect_points[j].y<min_y)
min_y = rect_points[j].y;
line( result_zero, rect_points[j], rect_points[(j+1)%4], color, 1, 8 );
}
Rect my_roi(min_x,min_y,temp1,temp2);
Mat copy = original(my_roi);
imwrite("/ur/target/copy/image/directory/image" + to_string(counter) + ".jpg",copy);
counter++;
}
}
imshow( "Result", result_zero );
waitKey(0);
return(0);
}
Result:
At the end, your directory will seem like this:
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