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/*
* Copyright (c) 2016-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ARM_COMPUTE_NEHOGDESCRIPTORKERNEL_H
#define ARM_COMPUTE_NEHOGDESCRIPTORKERNEL_H
#include "arm_compute/core/IHOG.h"
#include "arm_compute/core/NEON/INEKernel.h"
#include "arm_compute/core/Size2D.h"
namespace arm_compute
{
class ITensor;
/** NEON kernel to perform HOG Orientation Binning */
class NEHOGOrientationBinningKernel : public INEKernel
{
public:
const char *name() const override
{
return "NEHOGOrientationBinningKernel";
}
/** Default constructor */
NEHOGOrientationBinningKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEHOGOrientationBinningKernel(const NEHOGOrientationBinningKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEHOGOrientationBinningKernel &operator=(const NEHOGOrientationBinningKernel &) = delete;
/** Allow instances of this class to be moved */
NEHOGOrientationBinningKernel(NEHOGOrientationBinningKernel &&) = default;
/** Allow instances of this class to be moved */
NEHOGOrientationBinningKernel &operator=(NEHOGOrientationBinningKernel &&) = default;
/** Default destructor */
~NEHOGOrientationBinningKernel() = default;
/** Initialise the kernel's inputs, output and HOG's metadata
*
* @param[in] input_magnitude Input tensor which stores the magnitude of the gradient for each pixel. Data type supported: S16.
* @param[in] input_phase Input tensor which stores the phase of the gradient for each pixel. Data type supported: U8
* @param[out] output Output tensor which stores the local HOG for each cell. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per cell
* @param[in] hog_info HOG's metadata
*/
void configure(const ITensor *input_magnitude, const ITensor *input_phase, ITensor *output, const HOGInfo *hog_info);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Common signature for all the specialised block normalization functions
*
* @param[in] mag_row_ptr Pointer to the first row of the cell in the magnitude tensor
* @param[in] phase_row_ptr Pointer to the first row of the cell in the phase tensor
* @param[out] output_ptr Pointer to the output cell of hog space tensor
* @param[in] mag_stride Stride of the magnitude tensor
* @param[in] phase_stride Stride of the phase tensor
* @param[in] cell_width Width of the cell
* @param[in] cell_height Height of the cell
* @param[in] num_bins Number of bins for each cell
* @param[in] phase_scale Scale factor to apply to the phase in order to calculate the histogram index
*/
using OrientBinFunc = void(const int16_t *__restrict mag_row_ptr, const uint8_t *__restrict phase_row_ptr, float *__restrict output_ptr, size_t mag_stride, size_t phase_stride, size_t cell_width,
size_t cell_height, size_t num_bins, float phase_scale);
/** Orientation binning function to use for the particular cell width passed to configure() */
OrientBinFunc *_func;
const ITensor *_input_magnitude;
const ITensor *_input_phase;
ITensor *_output;
size_t _cell_width;
size_t _cell_height;
size_t _num_bins;
float _phase_scale;
};
/** NEON kernel to perform HOG block normalization */
class NEHOGBlockNormalizationKernel : public INEKernel
{
public:
const char *name() const override
{
return "NEHOGBlockNormalizationKernel";
}
/** Default constructor */
NEHOGBlockNormalizationKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEHOGBlockNormalizationKernel(const NEHOGBlockNormalizationKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEHOGBlockNormalizationKernel &operator=(const NEHOGBlockNormalizationKernel &) = delete;
/** Allow instances of this class to be moved */
NEHOGBlockNormalizationKernel(NEHOGBlockNormalizationKernel &&) = default;
/** Allow instances of this class to be moved */
NEHOGBlockNormalizationKernel &operator=(NEHOGBlockNormalizationKernel &&) = default;
/** Default destructor */
~NEHOGBlockNormalizationKernel() = default;
/** Initialise the kernel's input, output and HOG's metadata
*
* @param[in] input Input tensor which stores the local HOG for each cell. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per cell
* @param[out] output Output tensor which stores the normalised blocks. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per block
* @param[in] hog_info HOG's metadata
*/
void configure(const ITensor *input, ITensor *output, const HOGInfo *hog_info);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Common signature for all the specialised block normalization functions
*
* @param[in] input_row_ptr Pointer to the first row of the block in the input hog space tensor
* @param[out] output_ptr Pointer to the output block of the hog normalized space
* @param[in] input_stride Stride of the input hog space tensor
* @param[in] num_cells_per_block_height Number of cells per block along the Y direction
* @param[in] num_bins_block_x Number of bins per block along the X direction
* @param[in] num_bins_block Number of total bins per block
* @param[in] l2_hyst_threshold Threshold to use for l2 hysteresis normalization
*/
using BlockNormFunc = void(const float *input_row_ptr, float *output_ptr, size_t input_stride, size_t num_cells_per_block_height, size_t num_bins_block_x, size_t num_bins_block,
float l2_hyst_threshold);
/** Block normalization function to use for the particular normalization type passed to configure() */
BlockNormFunc *_func;
const ITensor *_input;
ITensor *_output;
Size2D _num_cells_per_block;
Size2D _num_cells_per_block_stride;
size_t _num_bins;
float _l2_hyst_threshold;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEHOGDESCRIPTORKERNEL_H */
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