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Purpose: 2nd review cycle - see ?? . wrong syntax format

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Elena Fedotova 14 years ago
parent 5006ba773f
commit 4ec0287dd3
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  1. 72
      modules/gpu/doc/object_detection.rst

72
modules/gpu/doc/object_detection.rst
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@ -9,7 +9,7 @@ gpu::HOGDescriptor
------------------
.. ocv:class:: gpu::HOGDescriptor
This class provides a histogram of Oriented Gradients [Navneet Dalal and Bill Triggs. Histogram of oriented gradients for human detection. 2005.] descriptor and detector.
Class providing a histogram of Oriented Gradients [Navneet Dalal and Bill Triggs. *Histogram of oriented gradients for human detection*. 2005.] descriptor and detector.
::
struct CV_EXPORTS HOGDescriptor
@ -72,27 +72,27 @@ gpu::HOGDescriptor::HOGDescriptor
Size cell_size=Size(8, 8), int nbins=9,
double win_sigma=DEFAULT_WIN_SIGMA,
double threshold_L2hys=0.2, bool gamma_correction=true,
int nlevels=DEFAULT_NLEVELS)
int nlevels=DEFAULT_NLEVELS)??check the output??
Creates the ``HOG`` descriptor and detector.
Creates the ``HOG`` descriptor and detector.
:param win_size: Detection window size. Align to block size and block stride.
: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_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 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 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 nbins: Number of bins. Only 9 bins per cell are supported for now.
:param win_sigma: Gaussian smoothing window parameter.
:param win_sigma: Gaussian smoothing window parameter.
:param threshold_L2Hys: L2-Hys normalization method shrinkage.
:param threshold_L2Hys: L2-Hys normalization method shrinkage.
:param gamma_correction: Flag to specify whether the gamma correction preprocessing is required or not.
:param gamma_correction: Flag to specify whether the gamma correction preprocessing is required or not.
:param nlevels: Maximum number of detection window increases.
:param nlevels: Maximum number of detection window increases.
.. index:: gpu::HOGDescriptor::getDescriptorSize
@ -148,19 +148,19 @@ gpu::HOGDescriptor::detect
------------------------------
.. ocv:function:: void gpu::HOGDescriptor::detect(const GpuMat\& img,
vector<Point>\& found_locations, double hit_threshold=0,
Size win_stride=Size(), Size padding=Size())
Size win_stride=Size(), Size padding=Size())??see output??
Performs object detection without a multi-scale window.
:param img: Source image. ``CV_8UC1`` and ``CV_8UC4`` types are supported for now.
: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 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 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).
:param padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
.. index:: gpu::HOGDescriptor::detectMultiScale
@ -169,23 +169,23 @@ gpu::HOGDescriptor::detectMultiScale
.. ocv:function:: void gpu::HOGDescriptor::detectMultiScale(const GpuMat\& img,
vector<Rect>\& found_locations, double hit_threshold=0,
Size win_stride=Size(), Size padding=Size(),
double scale0=1.05, int group_threshold=2)
double scale0=1.05, int group_threshold=2)??the same??
Performs object detection with a multi-scale window.
:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
:param found_locations: Detected objects boundaries.
:param found_locations: Detected objects boundaries.
:param hit_threshold: Threshold for the distance between features and SVM classifying plane. See :ocv:func:`gpu::HOGDescriptor::detect` for details.
:param hit_threshold: Threshold for the distance between features and SVM classifying plane. See :ocv:func:`gpu::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 padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
:param scale0: Coefficient of the detection window increase.
:param scale0: Coefficient of the detection window increase.
: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 :ocv:func:`groupRectangles` .
: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 :ocv:func:`groupRectangles` .
.. index:: gpu::HOGDescriptor::getDescriptors
@ -193,21 +193,21 @@ gpu::HOGDescriptor::getDescriptors
--------------------------------------
.. ocv:function:: void gpu::HOGDescriptor::getDescriptors(const GpuMat\& img,
Size win_stride, GpuMat\& descriptors,
int descr_format=DESCR_FORMAT_COL_BY_COL)
int descr_format=DESCR_FORMAT_COL_BY_COL)?? the same??
Returns block descriptors computed for the whole image. The function is mainly used to learn the classifier.
Returns block descriptors computed for the whole image. The function is mainly used to learn the classifier.
:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
:param img: Source image. See :ocv:func:`gpu::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 descriptors: 2D array of descriptors.
:param descr_format: Descriptor storage format:
:param descr_format: Descriptor storage format:
* **DESCR_FORMAT_ROW_BY_ROW** Row-major order.
* **DESCR_FORMAT_ROW_BY_ROW** - Row-major order.
* **DESCR_FORMAT_COL_BY_COL** Column-major order.
* **DESCR_FORMAT_COL_BY_COL** - Column-major order.
.. index:: gpu::CascadeClassifier_GPU
@ -216,7 +216,7 @@ gpu::CascadeClassifier_GPU
--------------------------
.. ocv:class:: gpu::CascadeClassifier_GPU
This cascade classifier class is used for object detection.
Cascade classifier class used for object detection.
::
class CV_EXPORTS CascadeClassifier_GPU
@ -324,5 +324,5 @@ gpu::CascadeClassifier_GPU::detectMultiScale
imshow("Faces", image_cpu);
See Also: :ocv:func:`CascadeClassifier::detectMultiScale`
.. seealso:: :ocv:func:`CascadeClassifier::detectMultiScale`

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