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Doxygen documentation: more fixes and cleanups

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This commit is contained in:
Maksim Shabunin
2014-11-21 11:28:14 +03:00
parent f9a83c28e5
commit 1523fdcc1c
41 changed files with 894 additions and 859 deletions
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62
modules/cuda/include/opencv2/cuda.hpp
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@@ -83,11 +83,11 @@ as possible.
@note
- An example applying the HOG descriptor for people detection can be found at
opencv\_source\_code/samples/cpp/peopledetect.cpp
opencv_source_code/samples/cpp/peopledetect.cpp
- A CUDA example applying the HOG descriptor for people detection can be found at
opencv\_source\_code/samples/gpu/hog.cpp
opencv_source_code/samples/gpu/hog.cpp
- (Python) An example applying the HOG descriptor for people detection can be found at
opencv\_source\_code/samples/python2/peopledetect.py
opencv_source_code/samples/python2/peopledetect.py
*/
struct CV_EXPORTS HOGDescriptor
{
@@ -97,14 +97,14 @@ struct CV_EXPORTS HOGDescriptor
/** @brief Creates the HOG descriptor and detector.
@param win\_size Detection window size. Align to block size and block stride.
@param block\_size Block size in pixels. Align to cell size. Only (16,16) is supported for now.
@param block\_stride Block stride. It must be a multiple of cell size.
@param cell\_size Cell size. Only (8, 8) is supported for now.
@param win_size Detection window size. Align to block size and block stride.
@param block_size Block size in pixels. Align to cell size. Only (16,16) is supported for now.
@param block_stride Block stride. It must be a multiple of cell size.
@param cell_size Cell size. Only (8, 8) is supported for now.
@param nbins Number of bins. Only 9 bins per cell are supported for now.
@param win\_sigma Gaussian smoothing window parameter.
@param threshold\_L2hys L2-Hys normalization method shrinkage.
@param gamma\_correction Flag to specify whether the gamma correction preprocessing is required or
@param win_sigma Gaussian smoothing window parameter.
@param threshold_L2hys L2-Hys normalization method shrinkage.
@param gamma_correction Flag to specify whether the gamma correction preprocessing is required or
not.
@param nlevels Maximum number of detection window increases.
*/
@@ -137,13 +137,13 @@ struct CV_EXPORTS HOGDescriptor
/** @brief Performs object detection without a multi-scale window.
@param img Source image. CV\_8UC1 and CV\_8UC4 types are supported for now.
@param found\_locations Left-top corner points of detected objects boundaries.
@param hit\_threshold Threshold for the distance between features and SVM classifying plane.
@param img Source image. CV_8UC1 and CV_8UC4 types are supported for now.
@param found_locations Left-top corner points of detected objects boundaries.
@param hit_threshold Threshold for the distance between features and SVM classifying plane.
Usually it is 0 and should be specfied in the detector coefficients (as the last free
coefficient). But if the free coefficient is omitted (which is allowed), you can specify it
manually here.
@param win\_stride Window stride. It must be a multiple of block stride.
@param win_stride Window stride. It must be a multiple of block stride.
@param padding Mock parameter to keep the CPU interface compatibility. It must be (0,0).
*/
void detect(const GpuMat& img, std::vector<Point>& found_locations,
@@ -153,13 +153,13 @@ struct CV_EXPORTS HOGDescriptor
/** @brief Performs object detection with a multi-scale window.
@param img Source image. See cuda::HOGDescriptor::detect for type limitations.
@param found\_locations Detected objects boundaries.
@param hit\_threshold Threshold for the distance between features and SVM classifying plane. See
@param found_locations Detected objects boundaries.
@param hit_threshold Threshold for the distance between features and SVM classifying plane. See
cuda::HOGDescriptor::detect for details.
@param win\_stride Window stride. It must be a multiple of block stride.
@param win_stride Window stride. It must be a multiple of block stride.
@param padding Mock parameter to keep the CPU interface compatibility. It must be (0,0).
@param scale0 Coefficient of the detection window increase.
@param group\_threshold Coefficient to regulate the similarity threshold. When detected, some
@param group_threshold Coefficient to regulate the similarity threshold. When detected, some
objects can be covered by many rectangles. 0 means not to perform grouping. See groupRectangles .
*/
void detectMultiScale(const GpuMat& img, std::vector<Rect>& found_locations,
@@ -177,11 +177,11 @@ struct CV_EXPORTS HOGDescriptor
/** @brief Returns block descriptors computed for the whole image.
@param img Source image. See cuda::HOGDescriptor::detect for type limitations.
@param win\_stride Window stride. It must be a multiple of block stride.
@param win_stride Window stride. It must be a multiple of block stride.
@param descriptors 2D array of descriptors.
@param descr\_format Descriptor storage format:
- **DESCR\_FORMAT\_ROW\_BY\_ROW** - Row-major order.
- **DESCR\_FORMAT\_COL\_BY\_COL** - Column-major order.
@param descr_format Descriptor storage format:
- **DESCR_FORMAT_ROW_BY_ROW** - Row-major order.
- **DESCR_FORMAT_COL_BY_COL** - Column-major order.
The function is mainly used to learn the classifier.
*/
@@ -236,9 +236,9 @@ protected:
@note
- A cascade classifier example can be found at
opencv\_source\_code/samples/gpu/cascadeclassifier.cpp
opencv_source_code/samples/gpu/cascadeclassifier.cpp
- A Nvidea API specific cascade classifier example can be found at
opencv\_source\_code/samples/gpu/cascadeclassifier\_nvidia\_api.cpp
opencv_source_code/samples/gpu/cascadeclassifier_nvidia_api.cpp
*/
class CV_EXPORTS CascadeClassifier_CUDA
{
@@ -271,7 +271,7 @@ public:
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.2, int minNeighbors = 4, Size minSize = Size());
/** @brief Detects objects of different sizes in the input image.
@param image Matrix of type CV\_8U containing an image where objects should be detected.
@param image Matrix of type CV_8U containing an image where objects should be detected.
@param objectsBuf Buffer to store detected objects (rectangles). If it is empty, it is allocated
with the default size. If not empty, the function searches not more than N objects, where
N = sizeof(objectsBufer's data)/sizeof(cv::Rect).
@@ -364,15 +364,15 @@ CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tve
@param object Single-row matrix of object points.
@param image Single-row matrix of image points.
@param camera\_mat 3x3 matrix of intrinsic camera parameters.
@param dist\_coef Distortion coefficients. See undistortPoints for details.
@param camera_mat 3x3 matrix of intrinsic camera parameters.
@param dist_coef Distortion coefficients. See undistortPoints for details.
@param rvec Output 3D rotation vector.
@param tvec Output 3D translation vector.
@param use\_extrinsic\_guess Flag to indicate that the function must use rvec and tvec as an
@param use_extrinsic_guess Flag to indicate that the function must use rvec and tvec as an
initial transformation guess. It is not supported for now.
@param num\_iters Maximum number of RANSAC iterations.
@param max\_dist Euclidean distance threshold to detect whether point is inlier or not.
@param min\_inlier\_count Flag to indicate that the function must stop if greater or equal number
@param num_iters Maximum number of RANSAC iterations.
@param max_dist Euclidean distance threshold to detect whether point is inlier or not.
@param min_inlier_count Flag to indicate that the function must stop if greater or equal number
of inliers is achieved. It is not supported for now.
@param inliers Output vector of inlier indices.
*/