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Diffstat (limited to 'tests/validation/TensorOperations.h')
| -rw-r--r-- | tests/validation/TensorOperations.h | 61 |
1 files changed, 61 insertions, 0 deletions
diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h index 0430d59d33..843c52fec4 100644 --- a/tests/validation/TensorOperations.h +++ b/tests/validation/TensorOperations.h @@ -711,6 +711,67 @@ void gemm(const Tensor<T> &in1, const Tensor<T> &in2, const Tensor<T> &in3, Tens } } +// Non linear filter +template <typename T> +void non_linear_filter(const Tensor<T> &in, Tensor<T> &out, NonLinearFilterFunction function, unsigned int mask_size, + MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value) +{ + ARM_COMPUTE_ERROR_ON(MatrixPattern::OTHER == pattern && nullptr == mask); + + using intermediate_type = typename common_promoted_signed_type<T>::intermediate_type; + + const int sq_mask_size = mask_size * mask_size; + const int half_mask_size = mask_size / 2; + std::vector<intermediate_type> vals(sq_mask_size); + intermediate_type current_value = 0; + + ValidRegion valid_region = shape_to_valid_region(in.shape()); + if(border_mode == BorderMode::UNDEFINED) + { + valid_region = shape_to_valid_region_undefined_border(in.shape(), BorderSize(half_mask_size)); + } + + for(int element_idx = 0, count = 0, index = 0; element_idx < in.num_elements(); ++element_idx, count = 0, index = 0) + { + Coordinates id = index2coord(in.shape(), element_idx); + if(is_in_valid_region(valid_region, id)) + { + int idx = id.x(); + int idy = id.y(); + for(int y = idy - half_mask_size; y <= idy + half_mask_size; ++y) + { + for(int x = idx - half_mask_size; x <= idx + half_mask_size; ++x, ++index) + { + id.set(0, x); + id.set(1, y); + current_value = tensor_elem_at(in, id, border_mode, constant_border_value); + + if(mask[index] == 255) + { + vals[count] = static_cast<intermediate_type>(current_value); + ++count; + } + } + } + std::sort(vals.begin(), vals.begin() + count); + switch(function) + { + case NonLinearFilterFunction::MIN: + out[element_idx] = saturate_cast<T>(vals[0]); + break; + case NonLinearFilterFunction::MAX: + out[element_idx] = saturate_cast<T>(vals[count - 1]); + break; + case NonLinearFilterFunction::MEDIAN: + out[element_idx] = saturate_cast<T>(vals[count / 2]); + break; + default: + ARM_COMPUTE_ERROR("Unsupported NonLinearFilter function."); + } + } + } +} + // Pixel-wise multiplication template <typename T1, typename T2, typename T3> void pixel_wise_multiplication(const Tensor<T1> &in1, const Tensor<T2> &in2, Tensor<T3> &out, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy) |