我有這個引腳頭的影像，我需要使用 OpenCV 檢測頭中是否有彎曲的引腳。
更新，解決了
多虧了尼克，我做了一些效果很好的東西，不是完美的，但還可以！
我使用該findContours功能來查找所有輪廓。然后我遍歷所有專案并找到minAreaRect, 并繪制一個給定大小的框。當一個盒子的寬度大于設定的閾值時，引腳太彎曲（超出規格）。
for (const auto &entry: fs::directory_iterator(SAMPLES)) {
try {
// Load src image
src = imread(entry.path(), IMREAD_COLOR);
// Blur
medianBlur(src, blurred, 3);
// Set threshold
threshold(blurred, blurred, 100, 255, cv::THRESH_BINARY);
// Edge detection
Canny(blurred, detected_edges, thres1, thres2, 3);
// imshow("blurred", blurred);
vector<vector<Point> > contours;
// Find all the contours in the image
findContours(detected_edges, contours, RETR_TREE, CHAIN_APPROX_SIMPLE);
vector<RotatedRect> minRect(contours.size());
vector<vector<Point> > contours_poly(contours.size());
vector<Rect> boundRect(contours.size());
int bendPins = 0;
for (size_t i = 0; i < contours.size(); i ) {
// bind all shapes to the vectors
minRect[i] = minAreaRect(contours[i]);
approxPolyDP(contours[i], contours_poly[i], 3, true);
boundRect[i] = boundingRect(contours_poly[i]);
// Draw the min area rect need to fill the contour
Rect rect(boundRect[i].tl(), boundRect[i].br());
rectangle(src, rect, Scalar(0, 0, 255), 2);
// When a pin it to bend
if (rect.width > threshold_bend) {
Point centerRect = (boundRect[i].br() boundRect[i].tl()) * 0.5;
circle(src, centerRect, 20, Scalar(255, 0, 255), 2);
bendPins ;
}
// Draw a rect around the pin, bent or not
Point2f rect_points[4];
minRect[i].points(rect_points);
for (int j = 0; j < 4; j ) {
line(src, rect_points[j], rect_points[(j 1) % 4], Scalar(0, 255, 255), 1);
}
}
char buffer[100];
snprintf(buffer, 100, "Found bend pin(s) : %d", bendPins);
putText(src, buffer, Point(10, 25), FONT_HERSHEY_SIMPLEX, 0.75, Scalar(255, 255, 255), 2);
imshow(entry.path().filename(), src);
waitKey();
} catch (const std::exception &e) {
cout << e.what() << endl;
}
}
結果：
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- 檢查每一行并根據厚度閾值獲取木棍。
此步驟的結果影像：
- 獲取每根棍子的中點 y 軸值并保存在一個陣列中。
- 計算每個陣列的標準偏差并選擇較高的。
這是代碼：
#include <string>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn_superres.hpp>
#include <numeric>
#include <boost/accumulators/accumulators.hpp>
#include <boost/accumulators/statistics/stats.hpp>
#include <boost/accumulators/statistics/mean.hpp>
#include <boost/accumulators/statistics/moment.hpp>
using namespace boost::accumulators;
using namespace std;
using namespace boost;
double stddev(std::vector<int> const & func)
{
double mean = std::accumulate(func.begin(), func.end(), 0.0) / func.size();
double sq_sum = std::inner_product(func.begin(), func.end(), func.begin(), 0.0,
[](double const & x, double const & y) { return x y; },
[mean](double const & x, double const & y) { return (x - mean)*(y - mean); });
return std::sqrt(sq_sum / func.size());
}
int main(){
cv::Mat img = cv::imread("/home/yns/Downloads/aaa.jpg",cv::IMREAD_GRAYSCALE);
cv::namedWindow("input",0);
cv::namedWindow("output",0);
cv::namedWindow("output2",0);
cv::imshow("input",img);
cv::Mat out;
cv::medianBlur(img,img,3);
cv::threshold(img,out,80,255,cv::THRESH_BINARY);
cv::Mat out2;
cv::cvtColor(out,out2,cv::COLOR_GRAY2BGR);
cv::imshow("output",out);
int start = 0;
int cnt = 0;
int refX = 0;
int thresholdThickness = 5;
int orderNum = 1;
std::vector<int> yAxis_1;
std::vector<int> yAxis_2;
std::vector<int> yAxis_3;
std::vector<int> yAxis_4;
std::vector<int> yAxis_5;
std::vector<int> yAxis_6;
std::vector<int> yAxis_7;
std::vector<int> yAxis_8;
std::vector<int> yAxis_9;
std::vector<int> yAxis_10;
std::vector<int> yAxis_11;
std::vector<int> yAxis_12;
int annen = 0;
for(int i=0; i<out.rows; i )
{
orderNum = 1;
annen = 0;
for(int j=0; j<out.cols; j )
{
if(out.at<uchar>(cv::Point(j,i))==255 && start != 1)
{
start = 1;
refX = j;
cnt = 0;
}
else if (out.at<uchar>(cv::Point(j,i))==255)
{
cnt ;
}
else if (out.at<uchar>(cv::Point(j,i))==0 && start == 1 && cnt>thresholdThickness) {
cv::circle(out2,cv::Point((j refX)/2,i),1,cv::Scalar(0,0,255),cv::FILLED);
start = 0;
annen ;
if(orderNum == 1)
yAxis_1.push_back(j);
if(orderNum == 2)
yAxis_2.push_back(j);
if(orderNum == 3)
yAxis_3.push_back(j);
if(orderNum == 4)
yAxis_4.push_back(j);
if(orderNum == 5)
yAxis_5.push_back(j);
if(orderNum == 6)
yAxis_6.push_back(j);
if(orderNum == 7)
yAxis_7.push_back(j);
if(orderNum == 8)
yAxis_8.push_back(j);
if(orderNum == 9)
yAxis_9.push_back(j);
if(orderNum == 10)
yAxis_10.push_back(j);
if(orderNum == 11)
yAxis_11.push_back(j);
if(orderNum == 12)
yAxis_12.push_back(j);
orderNum ;
}
else if (out.at<uchar>(cv::Point(j,i))==0 && start == 1)
{
start = 0;
}
}
}
std::cout<<stddev(yAxis_1)<<std::endl;
std::cout<<stddev(yAxis_2)<<std::endl;
std::cout<<stddev(yAxis_3)<<std::endl;
std::cout<<stddev(yAxis_4)<<std::endl;
std::cout<<stddev(yAxis_5)<<std::endl;
std::cout<<stddev(yAxis_6)<<std::endl;
std::cout<<stddev(yAxis_7)<<std::endl;
std::cout<<stddev(yAxis_8)<<std::endl;
std::cout<<stddev(yAxis_9)<<std::endl;
std::cout<<stddev(yAxis_10)<<std::endl;
std::cout<<stddev(yAxis_11)<<std::endl;
std::cout<<stddev(yAxis_12)<<std::endl;
float average = accumulate( yAxis_6.begin(), yAxis_6.end(), 0.0)/yAxis_6.size();
float average2 = accumulate( yAxis_7.begin(), yAxis_7.end(), 0.0)/yAxis_7.size();
cv::circle(out2,cv::Point(average,out2.rows/2),25,cv::Scalar(0,255,255),5);
cv::circle(out2,cv::Point(average2,out2.rows/2),25,cv::Scalar(0,255,255),5);
cv::imshow("output2",out2);
cv::waitKey(0);
return 0;
}
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標籤：C opencv