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authorIsabella Gottardi <isabella.gottardi@arm.com>2019-07-15 17:33:07 +0100
committerIsabella Gottardi <isabella.gottardi@arm.com>2019-07-29 13:01:03 +0000
commit883bad7ef34c3429b3338d5544a8cdf3b60cd1e8 (patch)
tree8e8a485c2581137c643003466ea1c467a579ba99 /src/runtime
parentbd9097db81f229c2d7bbafc2bcf392b7c1c49b58 (diff)
downloadComputeLibrary-883bad7ef34c3429b3338d5544a8cdf3b60cd1e8.tar.gz
COMPMID-1849: Add DetectorPostProcess operator
Part1 - Rework of CPPNonMaximumSuppression Change-Id: I2b34fbd12188db49b0ac050a12312494eeefd819 Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com> Reviewed-on: https://review.mlplatform.org/c/1585 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Diffstat (limited to 'src/runtime')
-rw-r--r--src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp95
-rw-r--r--src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp46
2 files changed, 49 insertions, 92 deletions
diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp
index 9a141cb73a..a1f4e6e89c 100644
--- a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp
+++ b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp
@@ -34,7 +34,7 @@ namespace arm_compute
{
namespace
{
-Status detection_layer_validate_arguments(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info)
+Status 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);
@@ -380,97 +380,8 @@ void ApplyNMSFast(const std::vector<NormalizedBBox> &bboxes,
}
}
}
-
-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()
@@ -488,7 +399,7 @@ 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(detection_layer_validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info));
_input_loc = input_loc;
_input_conf = input_conf;
@@ -526,7 +437,7 @@ 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(detection_layer_validate_arguments(input_loc, input_conf, input_priorbox, output, info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input_loc, input_conf, input_priorbox, output, info));
return Status{};
}
diff --git a/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp
new file mode 100644
index 0000000000..f13674a42f
--- /dev/null
+++ b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp
@@ -0,0 +1,46 @@
+/*
+ * Copyright (c) 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.
+ */
+#include "arm_compute/runtime/CPP/functions/CPPNonMaximumSuppression.h"
+
+#include "arm_compute/core/CPP/kernels/CPPNonMaximumSuppressionKernel.h"
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+void CPPNonMaximumSuppression::configure(
+ const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size,
+ const float score_threshold, const float nms_threshold)
+{
+ auto k = arm_compute::support::cpp14::make_unique<CPPNonMaximumSuppressionKernel>();
+ k->configure(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold);
+ _kernel = std::move(k);
+}
+
+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)
+{
+ return CPPNonMaximumSuppressionKernel::validate(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold);
+}
+} // namespace arm_compute