diff options
Diffstat (limited to 'src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp')
| -rw-r--r-- | src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp | 101 |
1 files changed, 95 insertions, 6 deletions
diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp index 61005ab5fd..34a7294513 100644 --- a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -34,7 +34,7 @@ namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) +Status detection_layer_validate_arguments(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input_loc, input_conf, input_priorbox, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_loc, 1, DataType::F32); @@ -366,14 +366,103 @@ void ApplyNMSFast(const std::vector<NormalizedBBox> &bboxes, indices.push_back(idx); } score_index_vec.erase(score_index_vec.begin()); - if(keep && eta < 1 && adaptive_threshold > 0.5) + if(keep && eta < 1.f && adaptive_threshold > 0.5f) { adaptive_threshold *= eta; } } } + +Status non_max_suppression_validate_arguments(const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, + const float score_threshold, const float nms_threshold) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(bboxes, scores, indices); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bboxes, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(bboxes->num_dimensions() > 2, "The bboxes tensor must be a 2-D float tensor of shape [4, num_boxes]."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(scores->num_dimensions() > 1, "The scores tensor must be a 1-D float tensor of shape [num_boxes]."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices->num_dimensions() > 1, "The indices must be 1-D integer tensor of shape [M], where max_output_size <= M"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(bboxes, scores); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(scores->num_dimensions() > 1, "Scores must be a 1D float tensor"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices->dimension(0) == 0, "Indices tensor must be bigger than 0"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(max_output_size == 0, "Max size cannot be 0"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(nms_threshold < 0.f || nms_threshold > 1.f, "Threshould must be in [0,1]"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(score_threshold < 0.f || score_threshold > 1.f, "Threshould must be in [0,1]"); + + return Status{}; +} } // namespace +CPPNonMaximumSuppression::CPPNonMaximumSuppression() + : _bboxes(nullptr), _scores(nullptr), _indices(nullptr), _max_output_size(0), _score_threshold(0.f), _nms_threshold(0.f) +{ +} + +void CPPNonMaximumSuppression::configure( + const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, + const float score_threshold, const float nms_threshold) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(bboxes, scores, indices); + ARM_COMPUTE_ERROR_THROW_ON(non_max_suppression_validate_arguments(bboxes->info(), scores->info(), indices->info(), max_output_size, score_threshold, nms_threshold)); + + // copy scores also to a vector + _bboxes = bboxes; + _scores = scores; + _indices = indices; + + _nms_threshold = nms_threshold; + _max_output_size = max_output_size; + _score_threshold = score_threshold; +} + +Status CPPNonMaximumSuppression::validate( + const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, + const float score_threshold, const float nms_threshold) +{ + ARM_COMPUTE_RETURN_ON_ERROR(non_max_suppression_validate_arguments(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold)); + return Status{}; +} + +void extract_bounding_boxes_from_tensor(const ITensor *bboxes, std::vector<NormalizedBBox> &bboxes_vector) +{ + Window input_win; + input_win.use_tensor_dimensions(bboxes->info()->tensor_shape()); + input_win.set_dimension_step(0U, 4U); + input_win.set_dimension_step(1U, 1U); + Iterator input(bboxes, input_win); + auto f = [&bboxes_vector, &input](const Coordinates &) + { + const auto input_ptr = reinterpret_cast<const float *>(input.ptr()); + bboxes_vector.push_back(NormalizedBBox({ *input_ptr, *(input_ptr + 1), *(2 + input_ptr), *(3 + input_ptr) })); + }; + execute_window_loop(input_win, f, input); +} + +void extract_scores_from_tensor(const ITensor *scores, std::vector<float> &scores_vector) +{ + Window window; + window.use_tensor_dimensions(scores->info()->tensor_shape()); + Iterator it(scores, window); + auto f = [&it, &scores_vector](const Coordinates &) + { + const auto input_ptr = reinterpret_cast<const float *>(it.ptr()); + scores_vector.push_back(*input_ptr); + }; + execute_window_loop(window, f, it); +} + +void CPPNonMaximumSuppression::run() +{ + std::vector<NormalizedBBox> bboxes_vector; + std::vector<float> scores_vector; + std::vector<int> indices_vector; + extract_bounding_boxes_from_tensor(_bboxes, bboxes_vector); + extract_scores_from_tensor(_scores, scores_vector); + ApplyNMSFast(bboxes_vector, scores_vector, _score_threshold, _nms_threshold, 1, -1 /* disable top_k */, indices_vector); + std::copy_n(indices_vector.begin(), std::min(indices_vector.size(), _indices->info()->dimension(0)), reinterpret_cast<int *>(_indices->ptr_to_element(Coordinates(0)))); +} + CPPDetectionOutputLayer::CPPDetectionOutputLayer() : _input_loc(nullptr), _input_conf(nullptr), _input_priorbox(nullptr), _output(nullptr), _info(), _num_priors(), _num(), _all_location_predictions(), _all_confidence_scores(), _all_prior_bboxes(), _all_prior_variances(), _all_decode_bboxes(), _all_indices() @@ -391,7 +480,7 @@ void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor auto_init_if_empty(*output->info(), input_loc->info()->clone()->set_tensor_shape(TensorShape(7U, max_size))); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info)); + ARM_COMPUTE_ERROR_THROW_ON(detection_layer_validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info)); _input_loc = input_loc; _input_conf = input_conf; @@ -429,7 +518,7 @@ void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor Status CPPDetectionOutputLayer::validate(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input_loc, input_conf, input_priorbox, output, info)); + ARM_COMPUTE_RETURN_ON_ERROR(detection_layer_validate_arguments(input_loc, input_conf, input_priorbox, output, info)); return Status{}; } @@ -582,4 +671,4 @@ void CPPDetectionOutputLayer::run() } } } -} // namespace arm_compute
\ No newline at end of file +} // namespace arm_compute |