我正在使用 OpenCV 3.2
我正在尝试使用 FLANN 以比蛮力更快的方式匹配特征描述符。
// Ratio to the second neighbor to consider a good match.
#define RATIO 0.75
void matchFeatures(const cv::Mat &query, const cv::Mat &target,
std::vector<cv::DMatch> &goodMatches) {
std::vector<std::vector<cv::DMatch>> matches;
cv::Ptr<cv::FlannBasedMatcher> matcher = cv::FlannBasedMatcher::create();
// Find 2 best matches for each descriptor to make later the second neighbor test.
matcher->knnMatch(query, target, matches, 2);
// Second neighbor ratio test.
for (unsigned int i = 0; i < matches.size(); ++i) {
if (matches[i][0].distance < matches[i][1].distance * RATIO)
goodMatches.push_back(matches[i][0]);
}
}
此代码使用 SURF 和 SIFT 描述符，但不适用于 ORB。
OpenCV Error: Unsupported format or combination of formats (type=0) in buildIndex
正如这里所说，FLANN 需要描述符为 CV_32F 类型，因此我们需要对其进行转换。
if (query.type() != CV_32F) query.convertTo(query, CV_32F);
if (target.type() != CV_32F) target.convertTo(target, CV_32F);
但是，这个假定的修复返回给我另一个convertTo函数错误。
OpenCV Error: Assertion failed (!fixedType() || ((Mat*)obj)->type() == mtype) in create
这个断言在opencv/modules/core/src/matrix.cpp文件中，第 2277 行。
发生了什么？
复制问题的代码。
#include <opencv2/opencv.hpp>
int main(int argc, char **argv) {
// Read both images.
cv::Mat image1 = cv::imread(argv[1], cv::IMREAD_GRAYSCALE);
if (image1.empty()) {
std::cerr << "Couldn't read image in " << argv[1] << std::endl;
return 1;
}
cv::Mat image2 = cv::imread(argv[2], cv::IMREAD_GRAYSCALE);
if (image2.empty()) {
std::cerr << "Couldn't read image in " << argv[2] << std::endl;
return 1;
}
// Detect the keyPoints and compute its descriptors using ORB Detector.
std::vector<cv::KeyPoint> keyPoints1, keyPoints2;
cv::Mat descriptors1, descriptors2;
cv::Ptr<cv::ORB> detector = cv::ORB::create();
detector->detectAndCompute(image1, cv::Mat(), keyPoints1, descriptors1);
detector->detectAndCompute(image2, cv::Mat(), keyPoints2, descriptors2);
// Match features.
std::vector<cv::DMatch> matches;
matchFeatures(descriptors1, descriptors2, matches);
// Draw matches.
cv::Mat image_matches;
cv::drawMatches(image1, keyPoints1, image2, keyPoints2, matches, image_matches);
cv::imshow("Matches", image_matches);
}