/* * 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 */