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>

4 files changed, 566 insertions, 0 deletions

diff --git a/tests/validation/NEON/CropResize.cpp b/tests/validation/NEON/CropResize.cpp
new file mode 100644
index 0000000000..1feed3d9d2
--- /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 0000000000..d83c4113f5
--- /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 0000000000..8cfce97eec
--- /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 0000000000..517c24bd32
--- /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__ */