COMPMID-1766: Implemented CPP Non Max Suppression
Change-Id: I2d2b684d464f7b3bb1f91cfd29952f612d65f11f
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/708
Reviewed-by: VidhyaSudhan Loganathan <vidhyasudhan.loganathan@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp
index 61005ab..34a7294 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
{
-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 @@
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 @@
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 @@
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 @@
}
}
}
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute