Purpose: 2nd review cycle - see ?? . wrong syntax format
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Elena Fedotova
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@ -9,7 +9,7 @@ gpu::HOGDescriptor
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------------------
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.. ocv:class:: gpu::HOGDescriptor
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This class provides a histogram of Oriented Gradients [Navneet Dalal and Bill Triggs. Histogram of oriented gradients for human detection. 2005.] descriptor and detector.
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Class providing a histogram of Oriented Gradients [Navneet Dalal and Bill Triggs. *Histogram of oriented gradients for human detection*. 2005.] descriptor and detector.
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::
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struct CV_EXPORTS HOGDescriptor
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@ -72,27 +72,27 @@ gpu::HOGDescriptor::HOGDescriptor
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Size cell_size=Size(8, 8), int nbins=9,
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double win_sigma=DEFAULT_WIN_SIGMA,
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double threshold_L2hys=0.2, bool gamma_correction=true,
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int nlevels=DEFAULT_NLEVELS)
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int nlevels=DEFAULT_NLEVELS)??check the output??
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Creates the ``HOG`` descriptor and detector.
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Creates the ``HOG`` descriptor and detector.
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:param win_size: Detection window size. Align to block size and block stride.
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:param win_size: Detection window size. Align to block size and block stride.
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:param block_size: Block size in pixels. Align to cell size. Only (16,16) is supported for now.
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:param block_size: Block size in pixels. Align to cell size. Only (16,16) is supported for now.
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:param block_stride: Block stride. It must be a multiple of cell size.
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:param block_stride: Block stride. It must be a multiple of cell size.
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:param cell_size: Cell size. Only (8, 8) is supported for now.
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:param cell_size: Cell size. Only (8, 8) is supported for now.
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:param nbins: Number of bins. Only 9 bins per cell are supported for now.
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:param nbins: Number of bins. Only 9 bins per cell are supported for now.
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:param win_sigma: Gaussian smoothing window parameter.
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:param win_sigma: Gaussian smoothing window parameter.
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:param threshold_L2Hys: L2-Hys normalization method shrinkage.
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:param threshold_L2Hys: L2-Hys normalization method shrinkage.
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:param gamma_correction: Flag to specify whether the gamma correction preprocessing is required or not.
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:param gamma_correction: Flag to specify whether the gamma correction preprocessing is required or not.
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:param nlevels: Maximum number of detection window increases.
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:param nlevels: Maximum number of detection window increases.
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.. index:: gpu::HOGDescriptor::getDescriptorSize
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@ -148,19 +148,19 @@ gpu::HOGDescriptor::detect
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------------------------------
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.. ocv:function:: void gpu::HOGDescriptor::detect(const GpuMat\& img,
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vector<Point>\& found_locations, double hit_threshold=0,
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Size win_stride=Size(), Size padding=Size())
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Size win_stride=Size(), Size padding=Size())??see output??
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Performs object detection without a multi-scale window.
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:param img: Source image. ``CV_8UC1`` and ``CV_8UC4`` types are supported for now.
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:param img: Source image. ``CV_8UC1`` and ``CV_8UC4`` types are supported for now.
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:param found_locations: Left-top corner points of detected objects boundaries.
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:param found_locations: Left-top corner points of detected objects boundaries.
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: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.
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: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.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
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:param padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
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.. index:: gpu::HOGDescriptor::detectMultiScale
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@ -169,23 +169,23 @@ gpu::HOGDescriptor::detectMultiScale
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.. ocv:function:: void gpu::HOGDescriptor::detectMultiScale(const GpuMat\& img,
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vector<Rect>\& found_locations, double hit_threshold=0,
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Size win_stride=Size(), Size padding=Size(),
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double scale0=1.05, int group_threshold=2)
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double scale0=1.05, int group_threshold=2)??the same??
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Performs object detection with a multi-scale window.
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:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
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:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
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:param found_locations: Detected objects boundaries.
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:param found_locations: Detected objects boundaries.
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:param hit_threshold: Threshold for the distance between features and SVM classifying plane. See :ocv:func:`gpu::HOGDescriptor::detect` for details.
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:param hit_threshold: Threshold for the distance between features and SVM classifying plane. See :ocv:func:`gpu::HOGDescriptor::detect` for details.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
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:param padding: Mock parameter to keep the CPU interface compatibility. It must be (0,0).
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:param scale0: Coefficient of the detection window increase.
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:param scale0: Coefficient of the detection window increase.
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: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` .
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: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` .
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.. index:: gpu::HOGDescriptor::getDescriptors
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@ -193,21 +193,21 @@ gpu::HOGDescriptor::getDescriptors
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--------------------------------------
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.. ocv:function:: void gpu::HOGDescriptor::getDescriptors(const GpuMat\& img,
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Size win_stride, GpuMat\& descriptors,
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int descr_format=DESCR_FORMAT_COL_BY_COL)
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int descr_format=DESCR_FORMAT_COL_BY_COL)?? the same??
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Returns block descriptors computed for the whole image. The function is mainly used to learn the classifier.
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Returns block descriptors computed for the whole image. The function is mainly used to learn the classifier.
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:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
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:param img: Source image. See :ocv:func:`gpu::HOGDescriptor::detect` for type limitations.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param win_stride: Window stride. It must be a multiple of block stride.
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:param descriptors: 2D array of descriptors.
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:param descriptors: 2D array of descriptors.
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:param descr_format: Descriptor storage format:
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:param descr_format: Descriptor storage format:
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* **DESCR_FORMAT_ROW_BY_ROW** Row-major order.
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* **DESCR_FORMAT_ROW_BY_ROW** - Row-major order.
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* **DESCR_FORMAT_COL_BY_COL** Column-major order.
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* **DESCR_FORMAT_COL_BY_COL** - Column-major order.
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.. index:: gpu::CascadeClassifier_GPU
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@ -216,7 +216,7 @@ gpu::CascadeClassifier_GPU
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--------------------------
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.. ocv:class:: gpu::CascadeClassifier_GPU
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This cascade classifier class is used for object detection.
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Cascade classifier class used for object detection.
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::
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class CV_EXPORTS CascadeClassifier_GPU
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@ -324,5 +324,5 @@ gpu::CascadeClassifier_GPU::detectMultiScale
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imshow("Faces", image_cpu);
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See Also: :ocv:func:`CascadeClassifier::detectMultiScale`
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.. seealso:: :ocv:func:`CascadeClassifier::detectMultiScale`
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