COMPMID-1327: Add support for BBoxTransform operator in CL

Change-Id: I91865506166951b3bf7f06a0b2d4cde925cfefb6
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/153447
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

1 files changed, 101 insertions, 0 deletions

diff --git a/tests/validation/reference/BoundingBoxTransform.cpp b/tests/validation/reference/BoundingBoxTransform.cpp
new file mode 100644
index 0000000000..6ac512e749
--- /dev/null
+++ b/tests/validation/reference/BoundingBoxTransform.cpp
@@ -0,0 +1,101 @@
+/*
+ * Copyright (c) 2018 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 "BoundingBoxTransform.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/utils/misc/Utility.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> bounding_box_transform(const SimpleTensor<T> &boxes, const SimpleTensor<T> &deltas, const BoundingBoxTransformInfo &info)
+{
+    const DataType  boxes_data_type = deltas.data_type();
+    SimpleTensor<T> pred_boxes(deltas.shape(), boxes_data_type);
+
+    const size_t num_classes    = deltas.shape()[0] / 4;
+    const size_t num_boxes      = deltas.shape()[1];
+    const T     *deltas_ptr     = deltas.data();
+    T           *pred_boxes_ptr = pred_boxes.data();
+
+    const int img_h = floor(info.img_height() / info.scale() + 0.5f);
+    const int img_w = floor(info.img_width() / info.scale() + 0.5f);
+
+    const T scale = (info.apply_scale() ? T(info.scale()) : T(1));
+
+    const size_t box_fields   = 4;
+    const size_t class_fields = 4;
+
+    for(size_t i = 0; i < num_boxes; ++i)
+    {
+        // Extract ROI information
+        const size_t start_box = box_fields * i;
+        const T      width     = boxes[start_box + 2] - boxes[start_box] + T(1.0);
+        const T      height    = boxes[start_box + 3] - boxes[start_box + 1] + T(1.0);
+        const T      ctr_x     = boxes[start_box] + T(0.5) * width;
+        const T      ctr_y     = boxes[start_box + 1] + T(0.5) * height;
+
+        for(size_t j = 0; j < num_classes; ++j)
+        {
+            // Extract deltas
+            const size_t start_delta = i * num_classes * class_fields + class_fields * j;
+            const T      dx          = deltas_ptr[start_delta] / T(info.weights()[0]);
+            const T      dy          = deltas_ptr[start_delta + 1] / T(info.weights()[1]);
+            T            dw          = deltas_ptr[start_delta + 2] / T(info.weights()[2]);
+            T            dh          = deltas_ptr[start_delta + 3] / T(info.weights()[3]);
+
+            // Clip dw and dh
+            dw = std::min(dw, T(info.bbox_xform_clip()));
+            dh = std::min(dh, T(info.bbox_xform_clip()));
+
+            // Determine the predictions
+            const T pred_ctr_x = dx * width + ctr_x;
+            const T pred_ctr_y = dy * height + ctr_y;
+            const T pred_w     = T(std::exp(dw)) * width;
+            const T pred_h     = T(std::exp(dh)) * height;
+
+            // Store the prediction into the output tensor
+            pred_boxes_ptr[start_delta]     = scale * utility::clamp<T>(pred_ctr_x - T(0.5) * pred_w, T(0), T(img_w));
+            pred_boxes_ptr[start_delta + 1] = scale * utility::clamp<T>(pred_ctr_y - T(0.5) * pred_h, T(0), T(img_h));
+            pred_boxes_ptr[start_delta + 2] = scale * utility::clamp<T>(pred_ctr_x + T(0.5) * pred_w, T(0), T(img_w));
+            pred_boxes_ptr[start_delta + 3] = scale * utility::clamp<T>(pred_ctr_y + T(0.5) * pred_h, T(0), T(img_h));
+        }
+    }
+    return pred_boxes;
+}
+
+template SimpleTensor<float> bounding_box_transform(const SimpleTensor<float> &boxes, const SimpleTensor<float> &deltas, const BoundingBoxTransformInfo &info);
+template SimpleTensor<half> bounding_box_transform(const SimpleTensor<half> &boxes, const SimpleTensor<half> &deltas, const BoundingBoxTransformInfo &info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute