Zi 字媒體
2017-07-25T20:27:27+00:00
fanfuhan OpenCV 教學082 ~ opencv-082-角點檢測(shi-tomas角點檢測/標記/定位/尋找)
資料來源: https://fanfuhan.github.io/
https://fanfuhan.github.io/2019/04/26/opencv-082/
GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV
Harris角點檢測是一種計算速度很慢的角點檢測算法，很難實時計算，所有最常用的是shi-tomas角點檢測算法，它的運行速度很快。
C++
#include
#include
using namespace std;
using namespace cv;
void process_frame(Mat &image);
RNG rng(12345);
/*
* 角点检测(shi-tomas角点检测)
*/
int main() {
VideoCapture capture("../images/color_object.mp4");
if (!capture.isOpened()) {
cout << "could not open video..." << endl;
return -1;
}
Mat frame;
while (true) {
bool ret = capture.read(frame);
imshow("input", frame);
if (!ret) break;
process_frame(frame);
imshow("result", frame);
char c = waitKey(5);
if (c == 27) {
break;
}
}
waitKey(0);
return 0;
}
void process_frame(Mat &image) {
// Detector parameters
int maxCorners = 100;
double quality_level = 0.01;
double minDistance = 0.04;
// detecting corners
Mat gray, dst;
cvtColor(image, gray, COLOR_BGR2GRAY);
vector corners;
goodFeaturesToTrack(gray, corners, maxCorners, quality_level,
minDistance, Mat(), 3, false);
// drawing corner
for (int i = 0; i < corners.size(); ++i) {
int b = rng.uniform(0, 255);
int g = rng.uniform(0, 255);
int r = rng.uniform(0, 255);
circle(image, corners[i], 5, Scalar(b, g, r), 3);
}
}
Python
import numpy as np
import cv2 as cv
def process(image, opt=1):
# Detecting corners
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
corners = cv.goodFeaturesToTrack(gray, 100, 0.05, 10)
print(len(corners))
for pt in corners:
print(pt)
b = np.random.random_integers(0, 256)
g = np.random.random_integers(0, 256)
r = np.random.random_integers(0, 256)
x = np.int32(pt[0][0])
y = np.int32(pt[0][1])
cv.circle(image, (x, y), 5, (int(b), int(g), int(r)), 2)
# output
return image
src = cv.imread("D:/images/ele_panel.png")
cv.imshow("input", src)
result = process(src)
cv.imshow('result', result)
cv.waitKey(0)
cv.destroyAllWindows()
"""
cap = cv.VideoCapture(0)
while True:
ret, frame = cap.read()
cv.imwrite("D:/input.png", frame)
cv.imshow('input', frame)
result = process(frame)
cv.imshow('result', result)
k = cv.waitKey(5)&0xff
if k == 27:
break
cap.release()
cv.destroyAllWindows()
"""
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