我遇到了一个问题： cv::FlannBasedMatcher 更准确地说是使用 knnMatch 方法。我的程序将 IplImage* 作为输入并检测人脸，然后剪切人脸并将创建的人脸与存储在我的计算机上的图像进行比较。如果我得到超过 10 个好的匹配，它会在标准输出上写入 Matched。
加载的图像不是灰度的。那很重要吗？
我的问题是它的工作原理是随机的，时间从 1 分钟到 3 分钟不等。
错误消息总是出现在 knnMatch 方法上。它们在这里（请注意，每次只有一个）：
OpenCV Error: Assertion failed ((globalDescIdx>=0) && (globalDescIdx < size())) in getLocalIdx, file /opt/local/var/macports/build/_opt_mports_dports_graphics_opencv/opencv/work/opencv- 2.4.9/modules/features2d/src/matchers.cpp, line 163
libc++abi.dylib: terminating with uncaught exception of type cv::Exception: /opt/local/var/macports/build/_opt_mports_dports_graphics_opencv/opencv/work/opencv-2.4.9/modules/features2d/src/matchers.cpp:163: error: (-215) (globalDescIdx>=0) && (globalDescIdx < size()) in function getLocalIdx
我不明白为什么会抛出这个异常......
这是我的代码：
int DroneCV::matchFaces()
{
std::vector<cv::KeyPoint> keypointsO;
std::vector<cv::KeyPoint> keypointsS;
cv::Mat descriptors_object, descriptors_scene;
cv::Mat foundFaces(this->_faceCut);
cv::FlannBasedMatcher matcher;
std::vector<std::vector<cv::DMatch>> matches;
std::vector<cv::DMatch> good_matches;
cv::SurfDescriptorExtractor extractor;
cv::SurfFeatureDetector surf(this->_minHessian);
surf.detect(foundFaces,keypointsS);
surf.detect(this->_faceToRecognize,keypointsO);
if (!this->_faceToRecognize.data || !foundFaces.data)
{
this->log("Fail to init data in DronceCV::matchFaces");
return (0);
}
extractor.compute(foundFaces, keypointsS, descriptors_scene);
extractor.compute(this->_faceToRecognize, keypointsO, descriptors_object);
if(descriptors_scene.empty())//descriptors_scene.type()!=CV_32F)
{
this->log("Descriptor got wrong type");
descriptors_scene.convertTo(descriptors_scene, CV_32F);
return 0;
}
if(descriptors_object.type()!=CV_32F || descriptors_scene.type()!=CV_32F)
{
this->log("TYPE OBJECT " + std::to_string(descriptors_object.type()));
this->log("TYPE SCENE " + std::to_string(descriptors_scene.type()));
return (0);
}
//Both image must be in grayscale ???
try {
matcher.knnMatch( descriptors_object, descriptors_scene, matches, 5 ); // find the 2 nearest neighbors
} catch (cv::Exception e) {
this->log(e.err);
}
good_matches.reserve(matches.size());
for (size_t i = 0; i < matches.size(); ++i)
{
if (matches[i].size() < 2)
continue;
const cv::DMatch &m1 = matches[i][0];
const cv::DMatch &m2 = matches[i][1];
if(m1.distance <= this->_nndrRatio * m2.distance)
good_matches.push_back(m1);
}
this->log("Number of good matches" + std::to_string(good_matches.size()));
foundFaces.release();
if (good_matches.size() > 8)
return (1);
else
return (0);
}
void DroneCV::analyzeFrame(IplImage *img)
{
if (!img)
{
this->log("Frame empty");
return;
}
if (this->detectFaces(img) == 1)
{
if (this->matchFaces() == 1)
{
this->log("Matched");
cvReleaseImage(&this->_faceCut);
}
}
}
在此先感谢您的帮助