| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | #include "balchunayte_z_sobel/omp/include/ops_omp.hpp" | ||
| 2 | |||
| 3 | #include <cstddef> | ||
| 4 | #include <cstdlib> | ||
| 5 | #include <vector> | ||
| 6 | |||
| 7 | #include "balchunayte_z_sobel/common/include/common.hpp" | ||
| 8 | |||
| 9 | namespace balchunayte_z_sobel { | ||
| 10 | |||
| 11 | namespace { | ||
| 12 | |||
| 13 | int ConvertPixelToGray(const Pixel &pixel_value) { | ||
| 14 | return (77 * static_cast<int>(pixel_value.r) + 150 * static_cast<int>(pixel_value.g) + | ||
| 15 | 29 * static_cast<int>(pixel_value.b)) >> | ||
| 16 | 8; | ||
| 17 | } | ||
| 18 | |||
| 19 | } // namespace | ||
| 20 | |||
| 21 |
1/2✓ Branch 1 taken 12 times.
✗ Branch 2 not taken.
|
12 | BalchunayteZSobelOpOMP::BalchunayteZSobelOpOMP(const InType &input_image) { |
| 22 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 23 | GetInput() = input_image; | ||
| 24 | GetOutput().clear(); | ||
| 25 | 12 | } | |
| 26 | |||
| 27 | 12 | bool BalchunayteZSobelOpOMP::ValidationImpl() { | |
| 28 | const auto &input_image = GetInput(); | ||
| 29 | |||
| 30 |
2/4✓ Branch 0 taken 12 times.
✗ Branch 1 not taken.
✓ Branch 2 taken 12 times.
✗ Branch 3 not taken.
|
12 | if (input_image.width <= 0 || input_image.height <= 0) { |
| 31 | return false; | ||
| 32 | } | ||
| 33 | |||
| 34 |
1/2✓ Branch 0 taken 12 times.
✗ Branch 1 not taken.
|
12 | const auto expected_size = static_cast<size_t>(input_image.width) * static_cast<size_t>(input_image.height); |
| 35 | |||
| 36 |
1/2✓ Branch 0 taken 12 times.
✗ Branch 1 not taken.
|
12 | if (input_image.data.size() != expected_size) { |
| 37 | return false; | ||
| 38 | } | ||
| 39 | |||
| 40 | 12 | return GetOutput().empty(); | |
| 41 | } | ||
| 42 | |||
| 43 | 12 | bool BalchunayteZSobelOpOMP::PreProcessingImpl() { | |
| 44 | const auto &input_image = GetInput(); | ||
| 45 | 12 | GetOutput().assign(static_cast<size_t>(input_image.width) * static_cast<size_t>(input_image.height), 0); | |
| 46 | 12 | return true; | |
| 47 | } | ||
| 48 | |||
| 49 |
1/2✓ Branch 0 taken 12 times.
✗ Branch 1 not taken.
|
12 | bool BalchunayteZSobelOpOMP::RunImpl() { |
| 50 | const auto &input_image = GetInput(); | ||
| 51 | auto &output_data = GetOutput(); | ||
| 52 | |||
| 53 | 12 | const int image_width = input_image.width; | |
| 54 | 12 | const int image_height = input_image.height; | |
| 55 | 12 | const auto image_width_size = static_cast<size_t>(image_width); | |
| 56 | |||
| 57 |
1/2✓ Branch 0 taken 12 times.
✗ Branch 1 not taken.
|
12 | if (image_width < 3 || image_height < 3) { |
| 58 | return true; | ||
| 59 | } | ||
| 60 | |||
| 61 | 12 | #pragma omp parallel for default(none) shared(input_image, output_data, image_width, image_height, image_width_size) \ | |
| 62 | schedule(static) | ||
| 63 | for (int row_index = 1; row_index < image_height - 1; ++row_index) { | ||
| 64 | for (int col_index = 1; col_index < image_width - 1; ++col_index) { | ||
| 65 | const size_t index_top_left = | ||
| 66 | (static_cast<size_t>(row_index - 1) * image_width_size) + static_cast<size_t>(col_index - 1); | ||
| 67 | const size_t index_top_middle = | ||
| 68 | (static_cast<size_t>(row_index - 1) * image_width_size) + static_cast<size_t>(col_index); | ||
| 69 | const size_t index_top_right = | ||
| 70 | (static_cast<size_t>(row_index - 1) * image_width_size) + static_cast<size_t>(col_index + 1); | ||
| 71 | |||
| 72 | const size_t index_middle_left = | ||
| 73 | (static_cast<size_t>(row_index) * image_width_size) + static_cast<size_t>(col_index - 1); | ||
| 74 | const size_t index_middle_right = | ||
| 75 | (static_cast<size_t>(row_index) * image_width_size) + static_cast<size_t>(col_index + 1); | ||
| 76 | |||
| 77 | const size_t index_bottom_left = | ||
| 78 | (static_cast<size_t>(row_index + 1) * image_width_size) + static_cast<size_t>(col_index - 1); | ||
| 79 | const size_t index_bottom_middle = | ||
| 80 | (static_cast<size_t>(row_index + 1) * image_width_size) + static_cast<size_t>(col_index); | ||
| 81 | const size_t index_bottom_right = | ||
| 82 | (static_cast<size_t>(row_index + 1) * image_width_size) + static_cast<size_t>(col_index + 1); | ||
| 83 | |||
| 84 | const int gray_top_left = ConvertPixelToGray(input_image.data[index_top_left]); | ||
| 85 | const int gray_top_middle = ConvertPixelToGray(input_image.data[index_top_middle]); | ||
| 86 | const int gray_top_right = ConvertPixelToGray(input_image.data[index_top_right]); | ||
| 87 | |||
| 88 | const int gray_middle_left = ConvertPixelToGray(input_image.data[index_middle_left]); | ||
| 89 | const int gray_middle_right = ConvertPixelToGray(input_image.data[index_middle_right]); | ||
| 90 | |||
| 91 | const int gray_bottom_left = ConvertPixelToGray(input_image.data[index_bottom_left]); | ||
| 92 | const int gray_bottom_middle = ConvertPixelToGray(input_image.data[index_bottom_middle]); | ||
| 93 | const int gray_bottom_right = ConvertPixelToGray(input_image.data[index_bottom_right]); | ||
| 94 | |||
| 95 | const int gradient_x = (-gray_top_left + gray_top_right) + (-2 * gray_middle_left + 2 * gray_middle_right) + | ||
| 96 | (-gray_bottom_left + gray_bottom_right); | ||
| 97 | |||
| 98 | const int gradient_y = (gray_top_left + (2 * gray_top_middle) + gray_top_right) + | ||
| 99 | (-gray_bottom_left - (2 * gray_bottom_middle) - gray_bottom_right); | ||
| 100 | |||
| 101 | const int magnitude = std::abs(gradient_x) + std::abs(gradient_y); | ||
| 102 | |||
| 103 | const size_t output_index = (static_cast<size_t>(row_index) * image_width_size) + static_cast<size_t>(col_index); | ||
| 104 | output_data[output_index] = magnitude; | ||
| 105 | } | ||
| 106 | } | ||
| 107 | |||
| 108 | 12 | return true; | |
| 109 | } | ||
| 110 | |||
| 111 | 12 | bool BalchunayteZSobelOpOMP::PostProcessingImpl() { | |
| 112 | 12 | return true; | |
| 113 | } | ||
| 114 | |||
| 115 | } // namespace balchunayte_z_sobel | ||
| 116 |