public override FeatureMatchResult Match(Mat sourceMat, Mat searchMat, FeatureMatchArgument argument)
{
//创建SIFT
using var sift = SIFT.Create();
//创建特征点描述对象，为下边的特征点匹配做准备
using var sourceDescriptors = new Mat();
using var searchDescriptors = new Mat();
//提取特征点，并进行特征点描述
sift.DetectAndCompute(sourceMat, null, out var sourceKeyPoints, sourceDescriptors);
sift.DetectAndCompute(searchMat, null, out var searchKeyPoints, searchDescriptors);
//创建Brute-force descriptor matcher
using var bfMatcher = new BFMatcher();
//对原图特征点描述加入训练
bfMatcher.Add(new List <Mat>()
{
sourceDescriptors
});
bfMatcher.Train();
//获得匹配特征点，并提取最优配对
var matches = bfMatcher.KnnMatch(sourceDescriptors, searchDescriptors, (int)argument.MatchPoints);
argument.OutputDebugMessage($"[FeatureMatch] [SIFT] The number of matching points is ({matches.Length}).");
//即使使用SIFT算法，但此时没有经过点筛选的匹配效果同样糟糕，所进一步获取优秀匹配点
var goodMatches = SelectGoodMatches(matches, argument, sourceKeyPoints, searchKeyPoints);
//获取匹配结果
var matchResult = GetMatchResult(goodMatches, sourceKeyPoints, searchKeyPoints);
argument.OutputDebugMessage($"[FeatureMatch] [SIFT] The result of the match is ({matchResult.Success}) ({matchResult.MatchItems.Count}).");
if (matchResult.Success)
{
var bestMatch = matchResult.MatchItems[0];
argument.OutputDebugMessage($"[FeatureMatch] [SIFT] The center point of the best match is ({bestMatch.Point}), and the rect is {bestMatch.Rectangle}.");
}
argument.PreviewDebugFeatureMatchResult(matchResult, sourceMat, searchMat, sourceKeyPoints, searchKeyPoints, goodMatches);
return(matchResult);
}
