COMPMID-761: Add CL/NEON HOGMultiDetection benchmark tests
Change-Id: I5e38eccc2fb273e2fd196b0528f27058e7c7ba2e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/135667
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/tests/benchmark/fixtures/HOGMultiDetectionFixture.h b/tests/benchmark/fixtures/HOGMultiDetectionFixture.h
new file mode 100644
index 0000000..947646c
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+++ b/tests/benchmark/fixtures/HOGMultiDetectionFixture.h
@@ -0,0 +1,148 @@
+/*
+ * 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.
+ */
+#ifndef ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE
+#define ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/Globals.h"
+#include "tests/Utils.h"
+#include "tests/framework/Fixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace benchmark
+{
+template <typename TensorType,
+ typename HOGType,
+ typename MultiHOGType,
+ typename DetectionWindowArrayType,
+ typename DetectionWindowStrideType,
+ typename Function,
+ typename Accessor,
+ typename HOGAccessorType,
+ typename Size2DArrayAccessorType>
+class HOGMultiDetectionFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(std::string image, std::vector<HOGInfo> models, Format format, BorderMode border_mode, bool non_maxima_suppression)
+ {
+ // Only defined borders supported
+ ARM_COMPUTE_ERROR_ON(border_mode == BorderMode::UNDEFINED);
+
+ std::mt19937 generator(library->seed());
+ std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+ uint8_t constant_border_value = static_cast<uint8_t>(distribution_u8(generator));
+
+ // Load the image (cached by the library if loaded before)
+ const RawTensor &raw = library->get(image, format);
+
+ // Initialize descriptors vector
+ std::vector<std::vector<float>> descriptors(models.size());
+
+ // Resize detection window_strides for index access
+ detection_window_strides.resize(models.size());
+
+ // Initialiize MultiHOG and detection windows
+ initialize_batch(models, multi_hog, descriptors, detection_window_strides);
+
+ // Create tensors
+ src = create_tensor<TensorType>(raw.shape(), format);
+
+ // Use default values for threshold and min_distance
+ const float threshold = 0.f;
+ const float min_distance = 1.f;
+
+ hog_multi_detection_func.configure(&src,
+ &multi_hog,
+ &detection_windows,
+ &detection_window_strides,
+ border_mode,
+ constant_border_value,
+ threshold,
+ non_maxima_suppression,
+ min_distance);
+
+ // Reset detection windows
+ detection_windows.clear();
+
+ // Allocate tensor
+ src.allocator()->allocate();
+
+ library->fill(Accessor(src), raw);
+ }
+
+ void run()
+ {
+ hog_multi_detection_func.run();
+ }
+
+ void sync()
+ {
+ sync_if_necessary<TensorType>();
+ }
+
+private:
+ void initialize_batch(const std::vector<HOGInfo> &models, MultiHOGType &multi_hog,
+ std::vector<std::vector<float>> &descriptors, DetectionWindowStrideType &detection_window_strides)
+ {
+ for(unsigned i = 0; i < models.size(); ++i)
+ {
+ auto hog_model = reinterpret_cast<HOGType *>(multi_hog.model(i));
+ hog_model->init(models[i]);
+
+ // Initialise descriptor (linear SVM coefficients).
+ std::random_device::result_type seed = 0;
+ descriptors.at(i) = generate_random_real(models[i].descriptor_size(), -0.505f, 0.495f, seed);
+
+ // Copy HOG descriptor values to HOG memory
+ {
+ HOGAccessorType hog_accessor(*hog_model);
+ std::memcpy(hog_accessor.descriptor(), descriptors.at(i).data(), descriptors.at(i).size() * sizeof(float));
+ }
+
+ // Initialize detection window stride
+ Size2DArrayAccessorType accessor(detection_window_strides);
+ accessor.at(i) = models[i].block_stride();
+ }
+ }
+
+private:
+ static const unsigned int model_size = 4;
+ static const unsigned int max_num_detection_windows = 100000;
+
+ MultiHOGType multi_hog{ model_size };
+ DetectionWindowStrideType detection_window_strides{ model_size };
+ DetectionWindowArrayType detection_windows{ max_num_detection_windows };
+
+ TensorType src{};
+ Function hog_multi_detection_func{};
+};
+} // namespace benchmark
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE */