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-rw-r--r--arm_compute/core/Helpers.inl4
-rw-r--r--src/core/NEON/kernels/NEWarpKernel.cpp63
-rw-r--r--tests/validation/CL/WarpPerspective.cpp208
-rw-r--r--tests/validation/Helpers.h25
-rw-r--r--tests/validation/NEON/WarpPerspective.cpp209
-rw-r--r--tests/validation/Reference.cpp16
-rw-r--r--tests/validation/Reference.h15
-rw-r--r--tests/validation/ReferenceCPP.cpp10
-rw-r--r--tests/validation/ReferenceCPP.h12
-rw-r--r--tests/validation/TensorOperations.h128
-rw-r--r--tests/validation/Validation.cpp34
-rw-r--r--tests/validation/Validation.h12
12 files changed, 725 insertions, 11 deletions
diff --git a/arm_compute/core/Helpers.inl b/arm_compute/core/Helpers.inl
index f885810078..d342a60987 100644
--- a/arm_compute/core/Helpers.inl
+++ b/arm_compute/core/Helpers.inl
@@ -53,8 +53,8 @@ inline uint8_t pixel_bilinear_c1u8(const uint8_t *first_pixel_ptr, size_t stride
{
ARM_COMPUTE_ERROR_ON(first_pixel_ptr == nullptr);
- const int32_t xi = x;
- const int32_t yi = y;
+ const int32_t xi = std::floor(x);
+ const int32_t yi = std::floor(y);
const float dx = x - xi;
const float dy = y - yi;
diff --git a/src/core/NEON/kernels/NEWarpKernel.cpp b/src/core/NEON/kernels/NEWarpKernel.cpp
index 8f8c852672..5ca1395b47 100644
--- a/src/core/NEON/kernels/NEWarpKernel.cpp
+++ b/src/core/NEON/kernels/NEWarpKernel.cpp
@@ -521,7 +521,6 @@ void NEWarpPerspectiveKernel<interpolation>::warp_constant(const Window &window)
const float yn = y0 / z0;
// Only use input values if xn and yn are within the valid region.
- // Otherwise write the constant border value.
if((min_y <= yn) && (yn < max_y) && (min_x <= xn) && (xn < max_x))
{
switch(interpolation)
@@ -538,7 +537,34 @@ void NEWarpPerspectiveKernel<interpolation>::warp_constant(const Window &window)
}
else
{
- *out.ptr() = _constant_border_value;
+ switch(interpolation)
+ {
+ case InterpolationPolicy::NEAREST_NEIGHBOR:
+ *out.ptr() = _constant_border_value;
+ break;
+ case InterpolationPolicy::BILINEAR:
+ {
+ const auto xi = clamp<int>(std::floor(xn), min_x - 1, max_x);
+ const auto yi = clamp<int>(std::floor(yn), min_y - 1, max_y);
+ const auto xi_1 = clamp<int>(std::floor(xn + 1), min_x - 1, max_x);
+ const auto yi_1 = clamp<int>(std::floor(yn + 1), min_y - 1, max_y);
+
+ const float dx = xn - std::floor(xn);
+ const float dy = yn - std::floor(yn);
+ const float dx1 = 1.0f - dx;
+ const float dy1 = 1.0f - dy;
+
+ const float a00 = *(in.ptr() + xi + yi * stride);
+ const float a01 = *(in.ptr() + xi_1 + yi * stride);
+ const float a10 = *(in.ptr() + xi + yi_1 * stride);
+ const float a11 = *(in.ptr() + xi_1 + yi_1 * stride);
+
+ *out.ptr() = a00 * (dx1 * dy1) + a01 * (dx * dy1) + a10 * (dx1 * dy) + a11 * (dx * dy);
+ }
+ break;
+ default:
+ ARM_COMPUTE_ERROR("Interpolation not supported");
+ }
}
x0 += M00;
@@ -619,7 +645,6 @@ void NEWarpPerspectiveKernel<interpolation>::warp_replicate(const Window &window
const float yn = y0 / z0;
// Only load from (x0, y0) if the point is within the valid region.
- // Otherwise load from the edge of the valid region.
if((min_y <= yn) && (yn < max_y) && (min_x <= xn) && (xn < max_x))
{
switch(interpolation)
@@ -637,10 +662,34 @@ void NEWarpPerspectiveKernel<interpolation>::warp_replicate(const Window &window
else
{
// Clamp coordinates
- const auto xi = clamp<int>(x0, min_x, max_x - 1);
- const auto yi = clamp<int>(y0, min_y, max_y - 1);
-
- *out.ptr() = *(in.ptr() + xi + yi * stride);
+ const auto xi = clamp<int>(std::floor(xn), min_x, max_x - 1);
+ const auto yi = clamp<int>(std::floor(yn), min_y, max_y - 1);
+ switch(interpolation)
+ {
+ case InterpolationPolicy::NEAREST_NEIGHBOR:
+ *out.ptr() = *(in.ptr() + xi + yi * stride);
+ break;
+ case InterpolationPolicy::BILINEAR:
+ {
+ const auto xi_1 = clamp<int>(std::floor(xn + 1), min_x, max_x - 1);
+ const auto yi_1 = clamp<int>(std::floor(yn + 1), min_y, max_y - 1);
+
+ const float dx = xn - std::floor(xn);
+ const float dy = yn - std::floor(yn);
+ const float dx1 = 1.0f - dx;
+ const float dy1 = 1.0f - dy;
+
+ const float a00 = *(in.ptr() + xi + yi * stride);
+ const float a01 = *(in.ptr() + xi_1 + yi * stride);
+ const float a10 = *(in.ptr() + xi + yi_1 * stride);
+ const float a11 = *(in.ptr() + xi_1 + yi_1 * stride);
+
+ *out.ptr() = a00 * (dx1 * dy1) + a01 * (dx * dy1) + a10 * (dx1 * dy) + a11 * (dx * dy);
+ }
+ break;
+ default:
+ ARM_COMPUTE_ERROR("Interpolation not supported");
+ }
}
x0 += M00;
diff --git a/tests/validation/CL/WarpPerspective.cpp b/tests/validation/CL/WarpPerspective.cpp
new file mode 100644
index 0000000000..260b22be03
--- /dev/null
+++ b/tests/validation/CL/WarpPerspective.cpp
@@ -0,0 +1,208 @@
+/*
+ * Copyright (c) 2017 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 "AssetsLibrary.h"
+#include "CL/CLAccessor.h"
+#include "Globals.h"
+#include "PaddingCalculator.h"
+#include "TypePrinter.h"
+#include "Utils.h"
+#include "validation/Datasets.h"
+#include "validation/Helpers.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+#include "validation/ValidationUserConfiguration.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/functions/CLWarpPerspective.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+
+#include "boost_wrapper.h"
+
+#include <random>
+#include <string>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+/** Compute Warp Perspective function.
+ *
+ * @param[in] input Shape of the input and output tensors.
+ * @param[in] matrix The perspective matrix. Must be 3x3 of type float.
+ * @param[in] policy The interpolation type.
+ * @param[in] border_mode Strategy to use for borders.
+ * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT.
+ *
+ * @return Computed output tensor.
+ */
+CLTensor compute_warp_perspective(const TensorShape &shape, const float *matrix, InterpolationPolicy policy,
+ BorderMode border_mode, uint8_t constant_border_value)
+{
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8);
+
+ // Create and configure function
+ CLWarpPerspective warp_perspective;
+ warp_perspective.configure(&src, &dst, matrix, policy, border_mode, constant_border_value);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ BOOST_TEST(!src.info()->is_resizable());
+ BOOST_TEST(!dst.info()->is_resizable());
+
+ // Fill tensors
+ library->fill_tensor_uniform(CLAccessor(src), 0);
+
+ // Compute function
+ warp_perspective.run();
+
+ return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(CL)
+BOOST_AUTO_TEST_SUITE(WarpPerspective)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration, (SmallShapes() + LargeShapes())
+ * boost::unit_test::data::make({ InterpolationPolicy::BILINEAR, InterpolationPolicy::NEAREST_NEIGHBOR }) * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8);
+
+ BOOST_TEST(src.info()->is_resizable());
+ BOOST_TEST(dst.info()->is_resizable());
+
+ // Create and configure function
+ CLWarpPerspective warp_perspective;
+ warp_perspective.configure(&src, &dst, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate valid region
+ const ValidRegion valid_region = shape_to_valid_region(shape);
+
+ validate(src.info()->valid_region(), valid_region);
+ validate(dst.info()->valid_region(), valid_region);
+
+ // Validate padding
+ PaddingCalculator calculator(shape.x(), 4);
+ calculator.set_border_mode(border_mode);
+
+ const PaddingSize read_padding(1);
+ const PaddingSize write_padding = calculator.required_padding(PaddingCalculator::Option::EXCLUDE_BORDER);
+
+ validate(src.info()->padding(), read_padding);
+ validate(dst.info()->padding(), write_padding);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall, SmallShapes()
+ * boost::unit_test::data::make({ InterpolationPolicy::BILINEAR, InterpolationPolicy::NEAREST_NEIGHBOR })
+ * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ // Create the valid mask Tensor
+ RawTensor valid_mask(shape, DataType::U8);
+
+ // Create the matrix
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Compute function
+ CLTensor dst = compute_warp_perspective(shape, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_warp_perspective(shape, valid_mask, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate output
+ validate(CLAccessor(dst), ref_dst, valid_mask, 1, 0.2f);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge, LargeShapes()
+ * boost::unit_test::data::make({ InterpolationPolicy::NEAREST_NEIGHBOR, InterpolationPolicy::BILINEAR }) * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ // Create the valid mask Tensor
+ RawTensor valid_mask(shape, DataType::U8);
+
+ // Create the matrix
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Compute function
+ CLTensor dst = compute_warp_perspective(shape, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_warp_perspective(shape, valid_mask, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate output
+ validate(CLAccessor(dst), ref_dst, valid_mask, 1, 0.2f);
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif /* DOXYGEN_SKIP_THIS */
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h
index 8d70de6958..09ffda8957 100644
--- a/tests/validation/Helpers.h
+++ b/tests/validation/Helpers.h
@@ -225,6 +225,31 @@ inline TensorShape calculate_depth_concatenate_shape(std::vector<TensorShape> in
return out_shape;
}
+/** Fill matrix random.
+ *
+ * @param[in,out] matrix Matrix
+ * @param[in] cols Columns (width) of matrix
+ * @param[in] rows Rows (height) of matrix
+ */
+template <std::size_t SIZE>
+inline void fill_warp_matrix(std::array<float, SIZE> &matrix, int cols, int rows)
+{
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_real_distribution<float> dist(-1, 1);
+
+ for(int v = 0, r = 0; r < rows; ++r)
+ {
+ for(int c = 0; c < cols; ++c, ++v)
+ {
+ matrix[v] = dist(gen);
+ }
+ }
+ if(SIZE == 9)
+ {
+ matrix[(cols * rows) - 1] = 1;
+ }
+}
+
/** Create a vector of random ROIs.
*
* @param[in] shape The shape of the input tensor.
diff --git a/tests/validation/NEON/WarpPerspective.cpp b/tests/validation/NEON/WarpPerspective.cpp
new file mode 100644
index 0000000000..2c102ea37e
--- /dev/null
+++ b/tests/validation/NEON/WarpPerspective.cpp
@@ -0,0 +1,209 @@
+/*
+ * Copyright (c) 2017 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 "AssetsLibrary.h"
+#include "Globals.h"
+#include "NEON/Accessor.h"
+#include "PaddingCalculator.h"
+#include "TypePrinter.h"
+#include "Utils.h"
+#include "validation/Datasets.h"
+#include "validation/Helpers.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+#include "validation/ValidationUserConfiguration.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEWarpPerspective.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+
+#include "boost_wrapper.h"
+
+#include <random>
+#include <string>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+/** Compute Warp Perspective function.
+ *
+ * @param[in] input Shape of the input and output tensors.
+ * @param[in] matrix The perspective matrix. Must be 3x3 of type float.
+ * @param[in] policy The interpolation type.
+ * @param[in] border_mode Strategy to use for borders.
+ * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT.
+ *
+ * @return Computed output tensor.
+ */
+Tensor compute_warp_perspective(const TensorShape &shape, const float *matrix, InterpolationPolicy policy,
+ BorderMode border_mode, uint8_t constant_border_value)
+{
+ // Create tensors
+ Tensor src = create_tensor<Tensor>(shape, DataType::U8);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U8);
+
+ // Create and configure function
+ NEWarpPerspective warp_perspective;
+ warp_perspective.configure(&src, &dst, matrix, policy, border_mode, constant_border_value);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ BOOST_TEST(!src.info()->is_resizable());
+ BOOST_TEST(!dst.info()->is_resizable());
+
+ // Fill tensors
+ library->fill_tensor_uniform(Accessor(src), 0);
+
+ // Compute function
+ warp_perspective.run();
+
+ return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(NEON)
+BOOST_AUTO_TEST_SUITE(WarpPerspective)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration, (SmallShapes() + LargeShapes())
+ * boost::unit_test::data::make({ InterpolationPolicy::BILINEAR, InterpolationPolicy::NEAREST_NEIGHBOR }) * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ // Create the matrix
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Create tensors
+ Tensor src = create_tensor<Tensor>(shape, DataType::U8);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U8);
+
+ BOOST_TEST(src.info()->is_resizable());
+ BOOST_TEST(dst.info()->is_resizable());
+
+ // Create and configure function
+ NEWarpPerspective warp_perspective;
+ warp_perspective.configure(&src, &dst, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate valid region
+ const ValidRegion valid_region = shape_to_valid_region(shape);
+
+ validate(src.info()->valid_region(), valid_region);
+ validate(dst.info()->valid_region(), valid_region);
+
+ // Validate padding
+ PaddingCalculator calculator(shape.x(), 1);
+ calculator.set_border_mode(border_mode);
+ calculator.set_border_size(1);
+
+ const PaddingSize read_padding(1);
+ const PaddingSize write_padding = calculator.required_padding();
+
+ validate(src.info()->padding(), read_padding);
+ validate(dst.info()->padding(), write_padding);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall, SmallShapes()
+ * boost::unit_test::data::make({ InterpolationPolicy::BILINEAR, InterpolationPolicy::NEAREST_NEIGHBOR })
+ * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ // Create the valid mask Tensor
+ RawTensor valid_mask(shape, DataType::U8);
+
+ // Create the matrix
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Compute function
+ Tensor dst = compute_warp_perspective(shape, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_warp_perspective(shape, valid_mask, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate output
+ validate(Accessor(dst), ref_dst, valid_mask, 1, 0.2f);
+}
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge, LargeShapes()
+ * boost::unit_test::data::make({ InterpolationPolicy::NEAREST_NEIGHBOR, InterpolationPolicy::BILINEAR }) * BorderModes(),
+ shape, policy, border_mode)
+{
+ uint8_t constant_border_value = 0;
+
+ // Generate a random constant value if border_mode is constant
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ std::mt19937 gen(user_config.seed.get());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ constant_border_value = distribution_u8(gen);
+ }
+
+ // Create the valid mask Tensor
+ RawTensor valid_mask(shape, DataType::U8);
+
+ // Create the matrix
+ std::array<float, 9> matrix;
+ fill_warp_matrix<9>(matrix, 3, 3);
+
+ // Compute function
+ Tensor dst = compute_warp_perspective(shape, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_warp_perspective(shape, valid_mask, matrix.data(), policy, border_mode, constant_border_value);
+
+ // Validate output
+ validate(Accessor(dst), ref_dst, valid_mask, 1, 0.2f);
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif /* DOXYGEN_SKIP_THIS */
diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp
index 621158a80e..0fca661dc4 100644
--- a/tests/validation/Reference.cpp
+++ b/tests/validation/Reference.cpp
@@ -390,6 +390,22 @@ RawTensor Reference::compute_reference_threshold(const TensorShape &shape, uint8
return ref_dst;
}
+RawTensor Reference::compute_reference_warp_perspective(const TensorShape &shape, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode,
+ uint8_t constant_border_value)
+{
+ // Create reference
+ RawTensor ref_src(shape, DataType::U8);
+ RawTensor ref_dst(shape, DataType::U8);
+
+ // Fill reference
+ library->fill_tensor_uniform(ref_src, 0);
+
+ // Compute reference
+ ReferenceCPP::warp_perspective(ref_src, ref_dst, valid_mask, matrix, policy, border_mode, constant_border_value);
+
+ return ref_dst;
+}
+
RawTensor Reference::compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position)
{
// Create reference
diff --git a/tests/validation/Reference.h b/tests/validation/Reference.h
index e00a5b95d5..13e43d3d30 100644
--- a/tests/validation/Reference.h
+++ b/tests/validation/Reference.h
@@ -266,6 +266,21 @@ public:
* @return Computed raw tensor.
*/
static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
+
+ /** Compute reference Warp Perspective.
+ *
+ * @param[in] shape Shape of the input and output tensors.
+ * @param[out] valid_mask Valid mask tensor.
+ * @param[in] matrix The perspective matrix. Must be 3x3 of type float.
+ * @param[in] policy The interpolation type.
+ * @param[in] border_mode Strategy to use for borders.
+ * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT.
+ *
+ * @return Computed raw tensor.
+ */
+ static RawTensor compute_reference_warp_perspective(const TensorShape &shape, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode,
+ uint8_t constant_border_value);
+
/** Compute reference batch normalization layer.
*
* @param[in] shape0 Shape of the input and output tensors.
diff --git a/tests/validation/ReferenceCPP.cpp b/tests/validation/ReferenceCPP.cpp
index 69100ad9bb..069cc1d871 100644
--- a/tests/validation/ReferenceCPP.cpp
+++ b/tests/validation/ReferenceCPP.cpp
@@ -252,6 +252,16 @@ void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t thres
tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper);
}
+// Warp perspective
+void ReferenceCPP::warp_perspective(const RawTensor &src, RawTensor &dst, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value)
+{
+ ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
+ const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
+ Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
+ Tensor<uint8_t> vmask(valid_mask.shape(), valid_mask.data_type(), valid_mask.fixed_point_position(), reinterpret_cast<uint8_t *>(valid_mask.data()));
+ tensor_operations::warp_perspective(s, d, vmask, matrix, policy, border_mode, constant_border_value);
+}
+
// Batch Normalization Layer
void ReferenceCPP::batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon,
int fixed_point_position)
diff --git a/tests/validation/ReferenceCPP.h b/tests/validation/ReferenceCPP.h
index 2118ea942e..2d35fa9590 100644
--- a/tests/validation/ReferenceCPP.h
+++ b/tests/validation/ReferenceCPP.h
@@ -228,6 +228,18 @@ public:
* @param[in] upper Upper threshold. Only used when the thresholding type is RANGE.
*/
static void threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
+ /** Warp perspective of@p src to @p dst
+ *
+ * @param[in] src First tensor.
+ * @param[out] dst Result tensor.
+ * @param[out] valid_mask Valid mask tensor.
+ * @param[in] matrix The perspective matrix. Must be 3x3 of type float.
+ * @param[in] policy The interpolation type.
+ * @param[in] border_mode Strategy to use for borders.
+ * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT.
+ */
+ static void warp_perspective(const RawTensor &src, RawTensor &dst, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value);
+
/** Batch Normalization of @p src based on the information from @p norm_info.
*
* @param[in] src Input tensor.
diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h
index 317d22934e..3220d80a04 100644
--- a/tests/validation/TensorOperations.h
+++ b/tests/validation/TensorOperations.h
@@ -388,7 +388,7 @@ void accumulate_squared(const Tensor<T1> &in, Tensor<T2> &out, uint32_t shift)
}
}
-// Accumulate weighted
+// Accumulate weighted total_size = init_auto_padding(tensor_shape, num_channels, type);
template <typename T>
void accumulate_weighted(const Tensor<T> &in, Tensor<T> &out, float alpha)
{
@@ -748,6 +748,132 @@ void threshold(const Tensor<T> &in, Tensor<T> &out, uint8_t threshold, uint8_t f
}
}
+template <typename T>
+T bilinear_policy(const Tensor<T> &in, Coordinates id, float xn, float yn, BorderMode border_mode, uint8_t constant_border_value)
+{
+ int idx = std::floor(xn);
+ int idy = std::floor(yn);
+
+ const float dx = xn - idx;
+ const float dy = yn - idy;
+ const float dx_1 = 1.0f - dx;
+ const float dy_1 = 1.0f - dy;
+
+ id.set(0, idx);
+ id.set(1, idy);
+ const T tl = tensor_elem_at(in, id, border_mode, constant_border_value);
+ id.set(0, idx + 1);
+ id.set(1, idy);
+ const T tr = tensor_elem_at(in, id, border_mode, constant_border_value);
+ id.set(0, idx);
+ id.set(1, idy + 1);
+ const T bl = tensor_elem_at(in, id, border_mode, constant_border_value);
+ id.set(0, idx + 1);
+ id.set(1, idy + 1);
+ const T br = tensor_elem_at(in, id, border_mode, constant_border_value);
+
+ return tl * (dx_1 * dy_1) + tr * (dx * dy_1) + bl * (dx_1 * dy) + br * (dx * dy);
+}
+
+bool valid_bilinear_policy(float xn, float yn, int width, int height, BorderMode border_mode)
+{
+ if(border_mode != BorderMode::UNDEFINED)
+ {
+ return true;
+ }
+ if((0 <= yn + 1) && (yn + 1 < height) && (0 <= xn + 1) && (xn + 1 < width))
+ {
+ return true;
+ }
+ return false;
+}
+
+// Warp Perspective
+template <typename T>
+void warp_perspective(const Tensor<T> &in, Tensor<T> &out, Tensor<T> &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value)
+{
+ // x0 = M00 * x + M01 * y + M02
+ // y0 = M10 * x + M11 * y + M12
+ // z0 = M20 * x + M21 * y + M22
+ // xn = x0 / z0
+ // yn = y0 / z0
+ const float M00 = matrix[0];
+ const float M10 = matrix[1];
+ const float M20 = matrix[2];
+ const float M01 = matrix[0 + 1 * 3];
+ const float M11 = matrix[1 + 1 * 3];
+ const float M21 = matrix[2 + 1 * 3];
+ const float M02 = matrix[0 + 2 * 3];
+ const float M12 = matrix[1 + 2 * 3];
+ const float M22 = matrix[2 + 2 * 3];
+
+ const int width = in.shape().x();
+ const int height = in.shape().y();
+
+ for(int element_idx = 0; element_idx < in.num_elements(); ++element_idx)
+ {
+ valid_mask[element_idx] = 1;
+ Coordinates id = index2coord(in.shape(), element_idx);
+ int idx = id.x();
+ int idy = id.y();
+ const float z0 = M20 * idx + M21 * idy + M22;
+
+ float x0 = (M00 * idx + M01 * idy + M02);
+ float y0 = (M10 * idx + M11 * idy + M12);
+
+ float xn = x0 / z0;
+ float yn = y0 / z0;
+ id.set(0, static_cast<int>(std::floor(xn)));
+ id.set(1, static_cast<int>(std::floor(yn)));
+ if((0 <= yn) && (yn < height) && (0 <= xn) && (xn < width))
+ {
+ switch(policy)
+ {
+ case InterpolationPolicy::NEAREST_NEIGHBOR:
+ out[element_idx] = tensor_elem_at(in, id, border_mode, constant_border_value);
+ break;
+ case InterpolationPolicy::BILINEAR:
+ (valid_bilinear_policy(xn, yn, width, height, border_mode)) ? out[element_idx] = bilinear_policy(in, id, xn, yn, border_mode, constant_border_value) : valid_mask[element_idx] = 0;
+ break;
+ case InterpolationPolicy::AREA:
+ default:
+ ARM_COMPUTE_ERROR("Interpolation not supported");
+ }
+ }
+ else
+ {
+ if(border_mode == BorderMode::UNDEFINED)
+ {
+ valid_mask[element_idx] = 0;
+ }
+ else
+ {
+ switch(policy)
+ {
+ case InterpolationPolicy::NEAREST_NEIGHBOR:
+ if(border_mode == BorderMode::CONSTANT)
+ {
+ out[element_idx] = constant_border_value;
+ }
+ else if(border_mode == BorderMode::REPLICATE)
+ {
+ id.set(0, std::max(0, std::min(static_cast<int>(xn), width - 1)));
+ id.set(1, std::max(0, std::min(static_cast<int>(yn), height - 1)));
+ out[element_idx] = in[coord2index(in.shape(), id)];
+ }
+ break;
+ case InterpolationPolicy::BILINEAR:
+ out[element_idx] = bilinear_policy(in, id, xn, yn, border_mode, constant_border_value);
+ break;
+ case InterpolationPolicy::AREA:
+ default:
+ ARM_COMPUTE_ERROR("Interpolation not supported");
+ }
+ }
+ }
+ }
+}
+
// Batch Normalization Layer for fixed point type
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
void batch_normalization_layer(const Tensor<T> &in, Tensor<T> &out, const Tensor<T> &mean, const Tensor<T> &var, const Tensor<T> &beta, const Tensor<T> &gamma, float epsilon, int fixed_point_position)
diff --git a/tests/validation/Validation.cpp b/tests/validation/Validation.cpp
index eac4105b21..868bbaac5e 100644
--- a/tests/validation/Validation.cpp
+++ b/tests/validation/Validation.cpp
@@ -193,7 +193,6 @@ void check_single_element(const Coordinates &id, const IAccessor &tensor, const
BOOST_TEST_INFO("reference = " << std::setprecision(5) << ref);
BOOST_TEST_INFO("target = " << std::setprecision(5) << target);
BOOST_TEST_WARN(equal);
-
++num_mismatches;
}
++num_elements;
@@ -264,6 +263,39 @@ void validate(const IAccessor &tensor, const RawTensor &reference, const ValidRe
<< "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
}
+void validate(const IAccessor &tensor, const RawTensor &reference, const RawTensor &valid_mask, float tolerance_value, float tolerance_number, uint64_t wrap_range)
+{
+ int64_t num_mismatches = 0;
+ int64_t num_elements = 0;
+
+ BOOST_TEST(tensor.element_size() == reference.element_size());
+ BOOST_TEST(tensor.format() == reference.format());
+ BOOST_TEST(tensor.data_type() == reference.data_type());
+ BOOST_TEST(tensor.num_channels() == reference.num_channels());
+ BOOST_TEST(compare_dimensions(tensor.shape(), reference.shape()));
+
+ const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
+ const int min_channels = std::min(tensor.num_channels(), reference.num_channels());
+ const size_t channel_size = element_size_from_data_type(reference.data_type());
+
+ // Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
+ for(int element_idx = 0; element_idx < min_elements; ++element_idx)
+ {
+ const Coordinates id = index2coord(reference.shape(), element_idx);
+ if(valid_mask[element_idx] == 1)
+ {
+ check_single_element(id, tensor, reference, tolerance_value, wrap_range, min_channels, channel_size, num_mismatches, num_elements);
+ }
+ }
+
+ const int64_t absolute_tolerance_number = tolerance_number * num_elements;
+ const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f;
+
+ BOOST_TEST(num_mismatches <= absolute_tolerance_number,
+ num_mismatches << " values (" << std::setprecision(2) << percent_mismatches
+ << "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
+}
+
void validate(const IAccessor &tensor, const void *reference_value)
{
BOOST_TEST_REQUIRE((reference_value != nullptr));
diff --git a/tests/validation/Validation.h b/tests/validation/Validation.h
index 66bb2be2ca..43a90f378e 100644
--- a/tests/validation/Validation.h
+++ b/tests/validation/Validation.h
@@ -103,6 +103,18 @@ void validate(const IAccessor &tensor, const RawTensor &reference, float toleran
*/
void validate(const IAccessor &tensor, const RawTensor &reference, const ValidRegion &valid_region, float tolerance_value = 0.f, float tolerance_number = 0.f, uint64_t wrap_range = 0);
+/** Validate tensors with valid mask.
+ *
+ * - Dimensionality has to be the same.
+ * - All values have to match.
+ *
+ * @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
+ * zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
+ * reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
+ * other test cases.
+ */
+void validate(const IAccessor &tensor, const RawTensor &reference, const RawTensor &valid_mask, float tolerance_value = 0.f, float tolerance_number = 0.f, uint64_t wrap_range = 0);
+
/** Validate tensors against constant value.
*
* - All values have to match.
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-18 13:35:53 +0000