/* * Copyright (c) 2019-2020 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_CLGENERATEPROPOSALSLAYER_H #define ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H #include "arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h" #include "arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h" #include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h" #include "arm_compute/core/CL/kernels/CLPadLayerKernel.h" #include "arm_compute/core/CL/kernels/CLPermuteKernel.h" #include "arm_compute/core/CL/kernels/CLQuantizationLayerKernel.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/functions/CLReshapeLayer.h" #include "arm_compute/runtime/CPP/CPPScheduler.h" #include "arm_compute/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/MemoryGroup.h" namespace arm_compute { class ICLTensor; /** Basic function to generate proposals for a RPN (Region Proposal Network) * * This function calls the following OpenCL kernels: * -# @ref CLComputeAllAnchors * -# @ref CLPermute x 2 * -# @ref CLReshapeLayer x 2 * -# @ref CLBoundingBoxTransform * -# @ref CLPadLayerKernel * -# @ref CLDequantizationLayerKernel x 2 * -# @ref CLQuantizationLayerKernel * And the following CPP functions: * -# @ref CPPBoxWithNonMaximaSuppressionLimit */ class CLGenerateProposalsLayer : public IFunction { public: /** Default constructor * * @param[in] memory_manager (Optional) Memory manager. */ CLGenerateProposalsLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLGenerateProposalsLayer(const CLGenerateProposalsLayer &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLGenerateProposalsLayer &operator=(const CLGenerateProposalsLayer &) = delete; /** Set the input and output tensors. * * @param[in] scores Scores from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. * Data types supported: QASYMM8/F16/F32 * @param[in] deltas Bounding box deltas from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores * @param[in] anchors Anchors tensor of size (4, A). Data types supported: QSYMM16 with scale of 0.125 if @p scores is QASYMM8, otherwise same as @p scores * @param[out] proposals Box proposals output tensor of size (5, W*H*A). * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p scores is QASYMM8, otherwise same as @p scores * @param[out] scores_out Box scores output tensor of size (W*H*A). Data types supported: Same as @p scores * @param[out] num_valid_proposals Scalar output tensor which says which of the first proposals are valid. Data types supported: U32 * @param[in] info Contains GenerateProposals operation information described in @ref GenerateProposalsInfo * * @note Only single image prediction is supported. Height and Width (and scale) of the image will be contained in the @ref GenerateProposalsInfo struct. * @note Proposals contains all the proposals. Of those, only the first num_valid_proposals are valid. */ void configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, const GenerateProposalsInfo &info); /** Set the input and output tensors. * * @param[in] compile_context The compile context to be used. * @param[in] scores Scores from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. * Data types supported: QASYMM8/F16/F32 * @param[in] deltas Bounding box deltas from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores * @param[in] anchors Anchors tensor of size (4, A). Data types supported: QSYMM16 with scale of 0.125 if @p scores is QASYMM8, otherwise same as @p scores * @param[out] proposals Box proposals output tensor of size (5, W*H*A). * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p scores is QASYMM8, otherwise same as @p scores * @param[out] scores_out Box scores output tensor of size (W*H*A). Data types supported: Same as @p scores * @param[out] num_valid_proposals Scalar output tensor which says which of the first proposals are valid. Data types supported: U32 * @param[in] info Contains GenerateProposals operation information described in @ref GenerateProposalsInfo * * @note Only single image prediction is supported. Height and Width (and scale) of the image will be contained in the @ref GenerateProposalsInfo struct. * @note Proposals contains all the proposals. Of those, only the first num_valid_proposals are valid. */ void configure(const CLCompileContext &compile_context, const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, const GenerateProposalsInfo &info); /** Static function to check if given info will lead to a valid configuration of @ref CLGenerateProposalsLayer * * @param[in] scores Scores info from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. * Data types supported: QASYMM8/F16/F32 * @param[in] deltas Bounding box deltas info from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores * @param[in] anchors Anchors tensor of size (4, A). Data types supported: QSYMM16 with scale of 0.125 if @p scores is QASYMM8, otherwise same as @p scores * @param[in] proposals Box proposals info output tensor of size (5, W*H*A). * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p scores is QASYMM8, otherwise same as @p scores * @param[in] scores_out Box scores output tensor info of size (W*H*A). Data types supported: Same as @p scores * @param[in] num_valid_proposals Scalar output tensor info which says which of the first proposals are valid. Data types supported: U32 * @param[in] info Contains GenerateProposals operation information described in @ref GenerateProposalsInfo * * @return a Status */ static Status validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out, const ITensorInfo *num_valid_proposals, const GenerateProposalsInfo &info); // Inherited methods overridden: void run() override; private: // Memory group manager MemoryGroup _memory_group; // OpenCL kernels CLPermuteKernel _permute_deltas_kernel; CLReshapeLayer _flatten_deltas; CLPermuteKernel _permute_scores_kernel; CLReshapeLayer _flatten_scores; CLComputeAllAnchorsKernel _compute_anchors_kernel; CLBoundingBoxTransformKernel _bounding_box_kernel; CLPadLayerKernel _pad_kernel; CLDequantizationLayerKernel _dequantize_anchors; CLDequantizationLayerKernel _dequantize_deltas; CLQuantizationLayerKernel _quantize_all_proposals; // CPP functions CPPBoxWithNonMaximaSuppressionLimit _cpp_nms; bool _is_nhwc; bool _is_qasymm8; // Temporary tensors CLTensor _deltas_permuted; CLTensor _deltas_flattened; CLTensor _deltas_flattened_f32; CLTensor _scores_permuted; CLTensor _scores_flattened; CLTensor _all_anchors; CLTensor _all_anchors_f32; CLTensor _all_proposals; CLTensor _all_proposals_quantized; CLTensor _keeps_nms_unused; CLTensor _classes_nms_unused; CLTensor _proposals_4_roi_values; // Temporary tensor pointers CLTensor *_all_proposals_to_use; // Output tensor pointers ICLTensor *_num_valid_proposals; ICLTensor *_scores_out; /** Internal function to run the CPP BoxWithNMS kernel */ void run_cpp_nms_kernel(); }; } // namespace arm_compute #endif /* ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H */