finalization of pointbase functionality, removed old scripts, removed camera scripts, they will be added into their own folder
Pavol Debnar
2 years ago
parent
3025a56f36
commit
3995ba6298
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After Width: | Height: | Size: 1.2 MiB |
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import cv2
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import numpy as np
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import os
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def variance_of_laplacian(image):
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return cv2.Laplacian(image, cv2.CV_64F).var()
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os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"]="rtsp_transport;tcp"
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gstreamerstr = "tcpclientsrc host=192.168.0.144 port=5000 ! jpegdec ! videoconvert ! appsink"
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#if not capture.isOpened() : print("CANNOT OPEN STREAM")
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capture = cv2.VideoCapture("vid.mp4")
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keypressNo = 1
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while(True):
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#capture = cv2.VideoCapture(gstreamerstr,cv2.CAP_GSTREAMER)
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ret, frame = capture.read()
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if not ret:
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print('fail')
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break
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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variance = variance_of_laplacian(frame)
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cv2.putText(frame, "{}: {:.2f}".format("Variance:", variance), (10, 30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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cv2.imshow('frame',frame)
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#cv2.waitKey(0)
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if cv2.waitKey(70) == ord('v'):
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frames=[]
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maxVarIdx = 0
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maxVar = 0
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for i in range(5):
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ret, frame = capture.read()
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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frames.append(frame)
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var = variance_of_laplacian(frame)
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if var > maxVar:
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maxVar = var
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maxVarIdx = i
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cv2.waitKey(20)
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#test to see if the image with the highest variance gets picked
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#cv2.putText(frame, "{}: {:.2f}".format("Variance:", var), (10, 30),
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#cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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#writeString="imgtest"+str(keypressNo)+str(i)+".jpg"
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#cv2.imwrite(writeString, frames[i])
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writeString="img"+str(keypressNo)+".jpg"
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cv2.imwrite(writeString, frames[maxVarIdx])
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keypressNo=keypressNo+1
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capture.release()
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cv2.destroyAllWindows()
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@ -1,38 +0,0 @@
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import cv2
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import numpy as np
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import os
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from imutils import paths
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import argparse
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def variance_of_laplacian(image):
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return cv2.Laplacian(image, cv2.CV_64F).var()
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def minVarInFolder(path):
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minVar = 90000
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minPath=""
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files = os.listdir(path)
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for p in files:
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if ".png" in p and ".mask" not in p:
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print(path+p)
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img = cv2.imread(path+p)
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cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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var = variance_of_laplacian(img)
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if var < minVar:
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minPath = path+p
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minVar = var
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return minPath,minVar
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ap = argparse.ArgumentParser()
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ap.add_argument("-i", "--images", required=True,
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help="path to image")
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args = vars(ap.parse_args())
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path = args["images"]
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#img = cv2.imread(path)
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#cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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#var = variance_of_laplacian(img)
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print(minVarInFolder(path))
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File diff suppressed because it is too large
Load Diff
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gst-launch-1.0 -v v4l2src device=/dev/video0 num-buffers=-1 ! video/x-raw,width=640,height=480, framerate=30/1 ! videoconvert ! jpegenc ! tcpserversink host=192.168.0.144 port=5000
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@ -1,71 +0,0 @@
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#include "opencv2/highgui.hpp"
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#include "opencv2/core.hpp"
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#include "opencv2/imgproc.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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// static void help()
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// {
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// cout << "\nThis program demonstrates kmeans clustering.\n"
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// "It generates an image with random points, then assigns a random number of cluster\n"
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// "centers and uses kmeans to move those cluster centers to their representitive location\n"
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// "Call\n"
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// "./kmeans\n" << endl;
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// }
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int main( int /*argc*/, char** /*argv*/ )
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{
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const int MAX_CLUSTERS = 5;
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Scalar colorTab[] =
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{
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Scalar(0, 0, 255),
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Scalar(0,255,0),
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Scalar(255,100,100),
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Scalar(255,0,255),
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Scalar(0,255,255)
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};
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Mat img(500, 500, CV_8UC3);
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RNG rng(12345);
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for(;;)
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{
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int k, clusterCount = rng.uniform(2, MAX_CLUSTERS+1);
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int i, sampleCount = rng.uniform(1, 1001);
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Mat points(sampleCount, 1, CV_32FC2), labels;
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clusterCount = MIN(clusterCount, sampleCount);
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std::vector<Point2f> centers;
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/* generate random sample from multigaussian distribution */
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for( k = 0; k < clusterCount; k++ )
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{
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Point center;
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center.x = rng.uniform(0, img.cols);
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center.y = rng.uniform(0, img.rows);
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Mat pointChunk = points.rowRange(k*sampleCount/clusterCount,
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k == clusterCount - 1 ? sampleCount :
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(k+1)*sampleCount/clusterCount);
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rng.fill(pointChunk, RNG::NORMAL, Scalar(center.x, center.y), Scalar(img.cols*0.05, img.rows*0.05));
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}
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randShuffle(points, 1, &rng);
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double compactness = kmeans(points, clusterCount, labels,
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TermCriteria( TermCriteria::EPS+TermCriteria::COUNT, 10, 1.0),
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3, KMEANS_PP_CENTERS, centers);
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img = Scalar::all(0);
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for( i = 0; i < sampleCount; i++ )
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{
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int clusterIdx = labels.at<int>(i);
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Point ipt = points.at<Point2f>(i);
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circle( img, ipt, 2, colorTab[clusterIdx], FILLED, LINE_AA );
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}
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for (i = 0; i < (int)centers.size(); ++i)
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{
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Point2f c = centers[i];
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circle( img, c, 40, colorTab[i], 1, LINE_AA );
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}
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cout << "Compactness: " << compactness << endl;
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cout << "Labels rows" << labels.rows;
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cout << "Labels cols" << labels.cols;
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imshow("clusters", img);
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char key = (char)waitKey();
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if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
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break;
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}
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return 0;
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}
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// CPP program to Stitch
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// input images (panorama) using OpenCV
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#include <iostream>
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#include <fstream>
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// Include header files from OpenCV directory
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// required to stitch images.
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/stitching.hpp"
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using namespace std;
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using namespace cv;
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// Define mode for stitching as panorama
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// (One out of many functions of Stitcher)
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Stitcher::Mode mode = Stitcher::SCANS;
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// Array for pictures
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vector<Mat> imgs;
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int main(int argc, char* argv[])
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{
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// Get all the images that need to be
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// stitched as arguments from command line
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for (int i = 1; i < argc; ++i)
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{
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// Read the ith argument or image
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// and push into the image array
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Mat img = imread(argv[i]);
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if (img.empty())
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{
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// Exit if image is not present
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cout << "Can't read image '" << argv[i] << "'\n";
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return -1;
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}
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imgs.push_back(img);
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}
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// Define object to store the stitched image
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Mat pano;
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// Create a Stitcher class object with mode panoroma
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Ptr<Stitcher> stitcher = Stitcher::create(mode);
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// Command to stitch all the images present in the image array
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Stitcher::Status status = stitcher->stitch(imgs, pano);
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if (status != Stitcher::OK)
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{
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// Check if images could not be stitched
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// status is OK if images are stitched successfully
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cout << "Can't stitch images\n";
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return -1;
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}
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// Store a new image stitched from the given
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//set of images as "result.jpg"
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imwrite("result.jpg", pano);
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// Show the result
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imshow("Result", pano);
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waitKey(0);
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return 0;
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}
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