本文整理汇总了Java中org.opencv.utils.Converters.vector_vector_KeyPoint_to_Mat方法的典型用法代码示例。如果您正苦于以下问题：Java Converters.vector_vector_KeyPoint_to_Mat方法的具体用法？Java Converters.vector_vector_KeyPoint_to_Mat怎么用？Java Converters.vector_vector_KeyPoint_to_Mat使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.opencv.utils.Converters的用法示例。
在下文中一共展示了Converters.vector_vector_KeyPoint_to_Mat方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: compute
import org.opencv.utils.Converters; //导入方法依赖的package包/类
public void compute(List<Mat> images, List<MatOfKeyPoint> keypoints, List<Mat> descriptors)
{
Mat images_mat = Converters.vector_Mat_to_Mat(images);
List<Mat> keypoints_tmplm = new ArrayList<Mat>((keypoints != null) ? keypoints.size() : 0);
Mat keypoints_mat = Converters.vector_vector_KeyPoint_to_Mat(keypoints, keypoints_tmplm);
Mat descriptors_mat = new Mat();
compute_1(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj, descriptors_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
keypoints_mat.release();
Converters.Mat_to_vector_Mat(descriptors_mat, descriptors);
descriptors_mat.release();
return;
}
示例2: add
import org.opencv.utils.Converters; //导入方法依赖的package包/类
/**
* <p>Adds images and their keypoints to the training collection stored in the
* class instance.</p>
*
* @param images Image collection.
* @param keypoints Point collection. It is assumed that <code>keypoints[i]</code>
* are keypoints detected in the image <code>images[i]</code>.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_generic_descriptor_matchers.html#genericdescriptormatcher-add">org.opencv.features2d.GenericDescriptorMatcher.add</a>
*/
public void add(List<Mat> images, List<MatOfKeyPoint> keypoints)
{
Mat images_mat = Converters.vector_Mat_to_Mat(images);
List<Mat> keypoints_tmplm = new ArrayList<Mat>((keypoints != null) ? keypoints.size() : 0);
Mat keypoints_mat = Converters.vector_vector_KeyPoint_to_Mat(keypoints, keypoints_tmplm);
add_0(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj);
return;
}
示例3: compute
import org.opencv.utils.Converters; //导入方法依赖的package包/类
/**
* <p>Computes the descriptors for a set of keypoints detected in an image (first
* variant) or image set (second variant).</p>
*
* @param images Image set.
* @param keypoints Input collection of keypoints. Keypoints for which a
* descriptor cannot be computed are removed and the remaining ones may be
* reordered. Sometimes new keypoints can be added, for example:
* <code>SIFT</code> duplicates a keypoint with several dominant orientations
* (for each orientation).
* @param descriptors Computed descriptors. In the second variant of the method
* <code>descriptors[i]</code> are descriptors computed for a <code>keypoints[i]</code>.
* Row <code>j</code> is the <code>keypoints</code> (or <code>keypoints[i]</code>)
* is the descriptor for keypoint <code>j</code>-th keypoint.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_extractors.html#descriptorextractor-compute">org.opencv.features2d.DescriptorExtractor.compute</a>
*/
public void compute(List<Mat> images, List<MatOfKeyPoint> keypoints, List<Mat> descriptors)
{
Mat images_mat = Converters.vector_Mat_to_Mat(images);
List<Mat> keypoints_tmplm = new ArrayList<Mat>((keypoints != null) ? keypoints.size() : 0);
Mat keypoints_mat = Converters.vector_vector_KeyPoint_to_Mat(keypoints, keypoints_tmplm);
Mat descriptors_mat = new Mat();
compute_1(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj, descriptors_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
Converters.Mat_to_vector_Mat(descriptors_mat, descriptors);
return;
}