COMPMID-1843: Implement NECrop
Change-Id: I27e8b1a00c2315c72106e8e596f84ad48fb770e3
Signed-off-by: George Wort <george.wort@arm.com>
Reviewed-on: https://review.mlplatform.org/c/648
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
diff --git a/tests/validation/NEON/CropResize.cpp b/tests/validation/NEON/CropResize.cpp
new file mode 100644
index 0000000..1feed3d
--- /dev/null
+++ b/tests/validation/NEON/CropResize.cpp
@@ -0,0 +1,184 @@
+/*
+ * 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/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NECropResize.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+
+#include "tests/NEON/Accessor.h"
+#include "tests/datasets/CropResizeDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/CropResizeFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+TEST_SUITE(NEON)
+TEST_SUITE(CropResize)
+
+RelativeTolerance<float> tolerance_fp32(0.001f);
+
+template <typename T>
+using NECropResizeFixture = CropResizeFixture<Tensor, Accessor, NECropResize, T>;
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32),
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::U8), // Invalid input data type.
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32), // Invalid box_ind shape.
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32), // Invalid output shape.
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32), // Invalid output data type.
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32), // Invalid output shape.
+ TensorInfo(TensorShape(15U, 30U, 40U, 10U), 1, DataType::S32), // Invalid boxes shape.
+ }),
+ framework::dataset::make("BoxesInfo",{ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(4, 20), 1, DataType::F32),
+ TensorInfo(TensorShape(3, 20), 1, DataType::F32),
+ })),
+ framework::dataset::make("BoxIndInfo",{ TensorInfo(TensorShape(20), 1, DataType::S32),
+ TensorInfo(TensorShape(20), 1, DataType::S32),
+ TensorInfo(TensorShape(10), 1, DataType::S32),
+ TensorInfo(TensorShape(20), 1, DataType::S32),
+ TensorInfo(TensorShape(20), 1, DataType::S32),
+ TensorInfo(TensorShape(20), 1, DataType::S32),
+ TensorInfo(TensorShape(20), 1, DataType::S32),
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(15U, 5, 5, 20U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 5, 5, 20U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 5, 5, 20U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 5, 5, 10U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 5, 5, 20U), 1, DataType::S32),
+ TensorInfo(TensorShape(5U, 5, 5, 20U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 5, 5, 20U), 1, DataType::F32),
+ })),
+ framework::dataset::make("Expected", { true, false, false, false, false, false, false})),
+ input, boxes, box_ind, output, expected)
+{
+ ARM_COMPUTE_EXPECT(bool(NECropResize::validate(&input.clone()->set_data_layout(DataLayout::NHWC).set_is_resizable(false),
+ &boxes.clone()->set_is_resizable(false),
+ &box_ind.clone()->set_is_resizable(false),
+ &output.clone()->set_data_layout(DataLayout::NHWC).set_is_resizable(false),
+ Coordinates2D{ 5, 5 }, InterpolationPolicy::BILINEAR, 100)) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_SUITE(Float)
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+TEST_SUITE(F16)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::F16))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // F16
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+TEST_SUITE(F32)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::F32))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // F32
+TEST_SUITE_END() // Float
+
+TEST_SUITE(U16)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<uint16_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::U16))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // U16
+
+TEST_SUITE(S16)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<int16_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::S16))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // S16
+
+TEST_SUITE(U32)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<uint32_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::U32))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // U32
+
+TEST_SUITE(S32)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NECropResizeFixture<int32_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallCropResizeDataset(),
+ combine(framework::dataset::make("IsOutOfBounds", { true, false }),
+ framework::dataset::make("DataType", DataType::S32))))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+TEST_SUITE_END() // S32
+
+TEST_SUITE_END() // CropResize
+TEST_SUITE_END() // NEON
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/CropResizeFixture.h b/tests/validation/fixtures/CropResizeFixture.h
new file mode 100644
index 0000000..d83c411
--- /dev/null
+++ b/tests/validation/fixtures/CropResizeFixture.h
@@ -0,0 +1,139 @@
+/*
+ * 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.
+ */
+#ifndef ARM_COMPUTE_TEST_SLICE_OPERATIONS_FIXTURE
+#define ARM_COMPUTE_TEST_SLICE_OPERATIONS_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/RawLutAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/CropResize.h"
+#include "tests/validation/reference/Permute.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class CropResizeFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape src_shape, TensorShape boxes_shape, Coordinates2D crop_size, InterpolationPolicy method,
+ float extrapolation_value, bool is_outside_bounds, DataType data_type)
+ {
+ _target = compute_target(src_shape, boxes_shape, crop_size, method, extrapolation_value, is_outside_bounds, data_type);
+ _reference = compute_reference(src_shape, boxes_shape, crop_size, method, extrapolation_value, is_outside_bounds, data_type);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor, int i)
+ {
+ library->fill_tensor_uniform(tensor, i);
+ }
+
+ template <typename U, typename V>
+ void fill(U &&tensor, int i, V min, V max)
+ {
+ library->fill_tensor_uniform(tensor, i, min, max);
+ }
+
+ TensorType compute_target(const TensorShape &src_shape, const TensorShape &boxes_shape, const Coordinates2D &crop_size, InterpolationPolicy method,
+ float extrapolation_value, bool is_outside_bounds, DataType data_type)
+ {
+ TensorShape dst_shape(src_shape[0], crop_size.x, crop_size.y, boxes_shape[1]);
+
+ // Create tensors
+ TensorType src = create_tensor<TensorType>(src_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC);
+ TensorType boxes = create_tensor<TensorType>(boxes_shape, DataType::F32);
+ TensorType boxes_ind = create_tensor<TensorType>(TensorShape(boxes_shape[1]), DataType::S32);
+ TensorType dst = create_tensor<TensorType>(dst_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC);
+
+ // Create and configure function
+ FunctionType crop;
+ crop.configure(&src, &boxes, &boxes_ind, &dst, crop_size, method, extrapolation_value);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(boxes.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(boxes_ind.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ boxes.allocator()->allocate();
+ boxes_ind.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!boxes.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!boxes_ind.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Fill tensors
+ fill(AccessorType(src), 0);
+ fill(AccessorType(boxes), 1, is_outside_bounds ? 0.0f - out_of_bounds_reach : 0.0f, is_outside_bounds ? 1.0f + out_of_bounds_reach : 1.0f);
+ fill(AccessorType(boxes_ind), 2, 0, static_cast<int32_t>(src_shape[3] - 1));
+
+ // Compute function
+ crop.run();
+ return dst;
+ }
+
+ SimpleTensor<float> compute_reference(const TensorShape &src_shape, const TensorShape &boxes_shape, const Coordinates2D &crop_size, InterpolationPolicy method,
+ float extrapolation_value, bool is_outside_bounds, DataType data_type)
+ {
+ // Create reference
+ SimpleTensor<T> src{ src_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC };
+ SimpleTensor<float> boxes{ boxes_shape, DataType::F32 };
+ SimpleTensor<int32_t> boxes_ind{ TensorShape(boxes_shape[1]), DataType::S32 };
+
+ // Fill reference
+ fill(src, 0);
+ fill(boxes, 1, is_outside_bounds ? 0.0f - out_of_bounds_reach : 0.0f, is_outside_bounds ? 1.0f + out_of_bounds_reach : 1.0f);
+ fill(boxes_ind, 2, 0, static_cast<int32_t>(src.shape()[3] - 1));
+
+ SimpleTensor<float> output = reference::crop_and_resize(src, boxes, boxes_ind, crop_size, method, extrapolation_value);
+
+ SimpleTensor<float> permuted = reference::permute(output, PermutationVector(1, 2U, 0U));
+ return permuted;
+ }
+
+ constexpr static float out_of_bounds_reach = 2.0f;
+
+ TensorType _target{};
+ SimpleTensor<float> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_SLICE_OPERATIONS_FIXTURE */
diff --git a/tests/validation/reference/CropResize.cpp b/tests/validation/reference/CropResize.cpp
new file mode 100644
index 0000000..8cfce97
--- /dev/null
+++ b/tests/validation/reference/CropResize.cpp
@@ -0,0 +1,199 @@
+/*
+ * 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 "CropResize.h"
+#include "Utils.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+namespace
+{
+SimpleTensor<float> scale_image(const SimpleTensor<float> &in, const TensorShape &out_shape, InterpolationPolicy policy, float extrapolation_value)
+{
+ ARM_COMPUTE_ERROR_ON(in.data_layout() != DataLayout::NHWC);
+
+ SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC };
+ // Compute the ratio between source width/height and destination width/height
+ const auto wr = static_cast<float>(in.shape()[1]) / static_cast<float>(out_shape[1]);
+ const auto hr = static_cast<float>(in.shape()[2]) / static_cast<float>(out_shape[2]);
+
+ const auto width = static_cast<int>(in.shape().y());
+ const auto height = static_cast<int>(in.shape().z());
+
+ Window win;
+ win.use_tensor_dimensions(out_shape);
+ execute_window_loop(win, [&](const Coordinates & out_id)
+ {
+ Coordinates in_id(out_id);
+ int idw = in_id.y();
+ int idh = in_id.z();
+
+ switch(policy)
+ {
+ case InterpolationPolicy::NEAREST_NEIGHBOR:
+ {
+ //Calculate the source coords without -0.5f is equivalent to round the x_scr/y_src coords
+ float x_src = (idw + 0.5f) * wr;
+ float y_src = (idh + 0.5f) * hr;
+ in_id.set(1, x_src);
+ in_id.set(2, y_src);
+
+ // If coordinates in range of tensor's width or height
+ if(is_valid_pixel_index(x_src, y_src, width, height, 0))
+ {
+ *reinterpret_cast<float *>(out(out_id)) = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value);
+ }
+ else
+ {
+ *reinterpret_cast<float *>(out(out_id)) = extrapolation_value;
+ }
+ break;
+ }
+ case InterpolationPolicy::BILINEAR:
+ {
+ float x_src = idw * wr;
+ float y_src = idh * hr;
+ in_id.set(1, std::floor(x_src));
+ in_id.set(2, std::floor(y_src));
+ if(is_valid_pixel_index(x_src, y_src, width, height, 0))
+ {
+ const int id_w = in_id[1];
+ const int id_h = in_id[2];
+
+ const float dx = x_src - id_w;
+ const float dy = y_src - id_h;
+ const float dx_1 = 1.0f - dx;
+ const float dy_1 = 1.0f - dy;
+
+ in_id.set(1, id_w);
+ in_id.set(2, id_h);
+ const float tl = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value);
+ in_id.set(1, id_w + 1);
+ in_id.set(2, id_h);
+ const float tr = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value);
+ in_id.set(1, id_w);
+ in_id.set(2, id_h + 1);
+ const float bl = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value);
+ in_id.set(1, id_w + 1);
+ in_id.set(2, id_h + 1);
+ const float br = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value);
+
+ *reinterpret_cast<float *>(out(out_id)) = tl * (dx_1 * dy_1) + tr * (dx * dy_1) + bl * (dx_1 * dy) + br * (dx * dy);
+ }
+ else
+ {
+ *reinterpret_cast<float *>(out(out_id)) = extrapolation_value;
+ }
+ break;
+ }
+ default:
+ ARM_COMPUTE_ERROR("Unsupported interpolation mode");
+ }
+ });
+
+ return out;
+}
+
+template <typename T>
+SimpleTensor<float> crop_image(const SimpleTensor<T> &src, Coordinates start, Coordinates end, int32_t batch_index, float extrapolation_value)
+{
+ TensorShape out_shape(src.shape()[0], abs(end[0] - start[0]) + 1, abs(end[1] - start[1]) + 1);
+
+ SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC };
+
+ Window win;
+ win.use_tensor_dimensions(out_shape);
+ execute_window_loop(win, [&](const Coordinates & id)
+ {
+ bool out_of_bounds = false;
+ Coordinates offset(id[0], 0, 0, batch_index);
+ for(uint32_t i = 1; i < 3; ++i)
+ {
+ offset.set(i, end[i - 1] < start[i - 1] ? start[i - 1] - id[i] : start[i - 1] + id[i]);
+ if(offset[i] < 0 || static_cast<uint32_t>(offset[i]) > src.shape()[i] - 1)
+ {
+ out_of_bounds = true;
+ break;
+ }
+ }
+ if(!out_of_bounds)
+ {
+ *reinterpret_cast<float *>(out(id)) = static_cast<float>(*reinterpret_cast<const T *>(src(offset)));
+ }
+ else
+ {
+ *reinterpret_cast<float *>(out(id)) = extrapolation_value;
+ }
+ });
+ return out;
+}
+
+} // namespace
+
+template <typename T>
+SimpleTensor<float> crop_and_resize(const SimpleTensor<T> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value)
+{
+ ARM_COMPUTE_ERROR_ON(src.shape().num_dimensions() > 4);
+ ARM_COMPUTE_ERROR_ON(src.data_layout() != DataLayout::NHWC);
+
+ const TensorShape out_shape(src.shape()[0], crop_size.x, crop_size.y, boxes.shape()[1]);
+ SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC };
+
+ const TensorShape scaled_image_shape(src.shape()[0], crop_size.x, crop_size.y);
+
+ for(uint32_t i = 0; i < boxes.shape()[1]; ++i)
+ {
+ Coordinates start = Coordinates(std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(1, i)))) * (src.shape()[1] - 1) + 0.5f),
+ std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(0, i)))) * (src.shape()[2] - 1) + 0.5f));
+ Coordinates end = Coordinates(std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(3, i)))) * (src.shape()[1] - 1) + 0.5f),
+ std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(2, i)))) * (src.shape()[2] - 1) + 0.5f));
+ SimpleTensor<float> cropped = crop_image(src, start, end, box_ind[i], extrapolation_value);
+ SimpleTensor<float> scaled = scale_image(cropped, scaled_image_shape, method, extrapolation_value);
+ std::copy_n(reinterpret_cast<float *>(scaled.data()), scaled.num_elements(), reinterpret_cast<float *>(out(Coordinates(0, 0, 0, i))));
+ }
+ return out;
+}
+
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<float> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<uint16_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<uint32_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<int16_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<int32_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+template SimpleTensor<float> crop_and_resize(const SimpleTensor<half> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/reference/CropResize.h b/tests/validation/reference/CropResize.h
new file mode 100644
index 0000000..517c24b
--- /dev/null
+++ b/tests/validation/reference/CropResize.h
@@ -0,0 +1,44 @@
+/*
+ * 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.
+ */
+#ifndef __ARM_COMPUTE_TEST_CROP_RESIZE_H__
+#define __ARM_COMPUTE_TEST_CROP_RESIZE_H__
+
+#include "tests/SimpleTensor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<float> crop_and_resize(const SimpleTensor<T> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind,
+ Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_CROP_RESIZE_H__ */