arm_compute v20.05
diff --git a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp
index bc88f71..b3fc9c7 100644
--- a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp
+++ b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,7 +26,6 @@
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Validate.h"
-#include "support/ToolchainSupport.h"
#include <cstddef>
#include <ios>
@@ -41,7 +40,7 @@
DetectionPostProcessLayerInfo info, const unsigned int kBatchSize, const unsigned int kNumCoordBox)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input_box_encoding, input_class_score, input_anchors);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_box_encoding, 1, DataType::F32, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_box_encoding, 1, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_box_encoding, input_anchors);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->num_dimensions() > 3, "The location input tensor shape should be [4, N, kBatchSize].");
if(input_box_encoding->num_dimensions() > 2)
@@ -91,6 +90,24 @@
return Status{};
}
+inline void DecodeBoxCorner(BBox &box_centersize, BBox &anchor, Iterator &decoded_it, DetectionPostProcessLayerInfo info)
+{
+ const float half_factor = 0.5f;
+
+ // BBox is equavalent to CenterSizeEncoding [y,x,h,w]
+ const float y_center = box_centersize[0] / info.scale_value_y() * anchor[2] + anchor[0];
+ const float x_center = box_centersize[1] / info.scale_value_x() * anchor[3] + anchor[1];
+ const float half_h = half_factor * static_cast<float>(std::exp(box_centersize[2] / info.scale_value_h())) * anchor[2];
+ const float half_w = half_factor * static_cast<float>(std::exp(box_centersize[3] / info.scale_value_w())) * anchor[3];
+
+ // Box Corner encoding boxes are saved as [xmin, ymin, xmax, ymax]
+ auto decoded_ptr = reinterpret_cast<float *>(decoded_it.ptr());
+ *(decoded_ptr) = x_center - half_w; // xmin
+ *(1 + decoded_ptr) = y_center - half_h; // ymin
+ *(2 + decoded_ptr) = x_center + half_w; // xmax
+ *(3 + decoded_ptr) = y_center + half_h; // ymax
+}
+
/** Decode a bbox according to a anchors and scale info.
*
* @param[in] input_box_encoding The input prior bounding boxes.
@@ -102,8 +119,8 @@
{
const QuantizationInfo &qi_box = input_box_encoding->info()->quantization_info();
const QuantizationInfo &qi_anchors = input_anchors->info()->quantization_info();
- BBox box_centersize;
- BBox anchor;
+ BBox box_centersize{ {} };
+ BBox anchor{ {} };
Window win;
win.use_tensor_dimensions(input_box_encoding->info()->tensor_shape());
@@ -113,11 +130,9 @@
Iterator anchor_it(input_anchors, win);
Iterator decoded_it(decoded_boxes, win);
- const float half_factor = 0.5f;
-
- execute_window_loop(win, [&](const Coordinates &)
+ if(input_box_encoding->info()->data_type() == DataType::QASYMM8)
{
- if(is_data_type_quantized(input_box_encoding->info()->data_type()))
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto box_ptr = reinterpret_cast<const qasymm8_t *>(box_it.ptr());
const auto anchor_ptr = reinterpret_cast<const qasymm8_t *>(anchor_it.ptr());
@@ -127,29 +142,38 @@
anchor = BBox({ dequantize_qasymm8(*anchor_ptr, qi_anchors), dequantize_qasymm8(*(anchor_ptr + 1), qi_anchors),
dequantize_qasymm8(*(2 + anchor_ptr), qi_anchors), dequantize_qasymm8(*(3 + anchor_ptr), qi_anchors)
});
- }
- else
+ DecodeBoxCorner(box_centersize, anchor, decoded_it, info);
+ },
+ box_it, anchor_it, decoded_it);
+ }
+ else if(input_box_encoding->info()->data_type() == DataType::QASYMM8_SIGNED)
+ {
+ execute_window_loop(win, [&](const Coordinates &)
+ {
+ const auto box_ptr = reinterpret_cast<const qasymm8_signed_t *>(box_it.ptr());
+ const auto anchor_ptr = reinterpret_cast<const qasymm8_signed_t *>(anchor_it.ptr());
+ box_centersize = BBox({ dequantize_qasymm8_signed(*box_ptr, qi_box), dequantize_qasymm8_signed(*(box_ptr + 1), qi_box),
+ dequantize_qasymm8_signed(*(2 + box_ptr), qi_box), dequantize_qasymm8_signed(*(3 + box_ptr), qi_box)
+ });
+ anchor = BBox({ dequantize_qasymm8_signed(*anchor_ptr, qi_anchors), dequantize_qasymm8_signed(*(anchor_ptr + 1), qi_anchors),
+ dequantize_qasymm8_signed(*(2 + anchor_ptr), qi_anchors), dequantize_qasymm8_signed(*(3 + anchor_ptr), qi_anchors)
+ });
+ DecodeBoxCorner(box_centersize, anchor, decoded_it, info);
+ },
+ box_it, anchor_it, decoded_it);
+ }
+ else
+ {
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto box_ptr = reinterpret_cast<const float *>(box_it.ptr());
const auto anchor_ptr = reinterpret_cast<const float *>(anchor_it.ptr());
box_centersize = BBox({ *box_ptr, *(box_ptr + 1), *(2 + box_ptr), *(3 + box_ptr) });
anchor = BBox({ *anchor_ptr, *(anchor_ptr + 1), *(2 + anchor_ptr), *(3 + anchor_ptr) });
- }
-
- // BBox is equavalent to CenterSizeEncoding [y,x,h,w]
- const float y_center = box_centersize[0] / info.scale_value_y() * anchor[2] + anchor[0];
- const float x_center = box_centersize[1] / info.scale_value_x() * anchor[3] + anchor[1];
- const float half_h = half_factor * static_cast<float>(std::exp(box_centersize[2] / info.scale_value_h())) * anchor[2];
- const float half_w = half_factor * static_cast<float>(std::exp(box_centersize[3] / info.scale_value_w())) * anchor[3];
-
- // Box Corner encoding boxes are saved as [xmin, ymin, xmax, ymax]
- auto decoded_ptr = reinterpret_cast<float *>(decoded_it.ptr());
- *(decoded_ptr) = x_center - half_w; // xmin
- *(1 + decoded_ptr) = y_center - half_h; // ymin
- *(2 + decoded_ptr) = x_center + half_w; // xmax
- *(3 + decoded_ptr) = y_center + half_h; // ymax
- },
- box_it, anchor_it, decoded_it);
+ DecodeBoxCorner(box_centersize, anchor, decoded_it, info);
+ },
+ box_it, anchor_it, decoded_it);
+ }
}
void SaveOutputs(const Tensor *decoded_boxes, const std::vector<int> &result_idx_boxes_after_nms, const std::vector<float> &result_scores_after_nms, const std::vector<int> &result_classes_after_nms,
@@ -264,12 +288,26 @@
// Decode scores if necessary
if(_dequantize_scores)
{
- for(unsigned int idx_c = 0; idx_c < _num_classes_with_background; ++idx_c)
+ if(_input_box_encoding->info()->data_type() == DataType::QASYMM8)
{
- for(unsigned int idx_b = 0; idx_b < _num_boxes; ++idx_b)
+ for(unsigned int idx_c = 0; idx_c < _num_classes_with_background; ++idx_c)
{
- *(reinterpret_cast<float *>(_decoded_scores.ptr_to_element(Coordinates(idx_c, idx_b)))) =
- dequantize_qasymm8(*(reinterpret_cast<qasymm8_t *>(_input_scores->ptr_to_element(Coordinates(idx_c, idx_b)))), _input_scores->info()->quantization_info());
+ for(unsigned int idx_b = 0; idx_b < _num_boxes; ++idx_b)
+ {
+ *(reinterpret_cast<float *>(_decoded_scores.ptr_to_element(Coordinates(idx_c, idx_b)))) =
+ dequantize_qasymm8(*(reinterpret_cast<qasymm8_t *>(_input_scores->ptr_to_element(Coordinates(idx_c, idx_b)))), _input_scores->info()->quantization_info());
+ }
+ }
+ }
+ else if(_input_box_encoding->info()->data_type() == DataType::QASYMM8_SIGNED)
+ {
+ for(unsigned int idx_c = 0; idx_c < _num_classes_with_background; ++idx_c)
+ {
+ for(unsigned int idx_b = 0; idx_b < _num_boxes; ++idx_b)
+ {
+ *(reinterpret_cast<float *>(_decoded_scores.ptr_to_element(Coordinates(idx_c, idx_b)))) =
+ dequantize_qasymm8_signed(*(reinterpret_cast<qasymm8_signed_t *>(_input_scores->ptr_to_element(Coordinates(idx_c, idx_b)))), _input_scores->info()->quantization_info());
+ }
}
}
}