diff options
Diffstat (limited to 'tests/validation/Helpers.h')
-rw-r--r-- | tests/validation/Helpers.h | 49 |
1 files changed, 0 insertions, 49 deletions
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index 604840b33e..30ec14e716 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -111,15 +111,6 @@ std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::Activation return bounds; } -/** Fill mask with the corresponding given pattern. - * - * @param[in,out] mask Mask to be filled according to pattern - * @param[in] cols Columns (width) of mask - * @param[in] rows Rows (height) of mask - * @param[in] pattern Pattern to fill the mask according to - */ -void fill_mask_from_pattern(uint8_t *mask, int cols, int rows, MatrixPattern pattern); - /** Calculate output tensor shape give a vector of input tensor to concatenate * * @param[in] input_shapes Shapes of the tensors to concatenate across depth. @@ -137,46 +128,6 @@ TensorShape calculate_depth_concatenate_shape(const std::vector<TensorShape> &in */ TensorShape calculate_concatenate_shape(const std::vector<TensorShape> &input_shapes, size_t axis); -/** Parameters of Harris Corners algorithm. */ -struct HarrisCornersParameters -{ - float threshold{ 0.f }; /**< Threshold */ - float sensitivity{ 0.f }; /**< Sensitivity */ - float min_dist{ 0.f }; /**< Minimum distance */ - uint8_t constant_border_value{ 0 }; /**< Border value */ -}; - -/** Generate parameters for Harris Corners algorithm. */ -HarrisCornersParameters harris_corners_parameters(); - -/** Parameters of Canny edge algorithm. */ -struct CannyEdgeParameters -{ - int32_t upper_thresh{ 255 }; - int32_t lower_thresh{ 0 }; - uint8_t constant_border_value{ 0 }; -}; - -/** Generate parameters for Canny edge algorithm. */ -CannyEdgeParameters canny_edge_parameters(); - -/** Helper function to fill the Lut random by a ILutAccessor. - * - * @param[in,out] table Accessor at the Lut. - * - */ -template <typename T> -void fill_lookuptable(T &&table) -{ - std::mt19937 generator(library->seed()); - std::uniform_int_distribution<typename T::value_type> distribution(std::numeric_limits<typename T::value_type>::min(), std::numeric_limits<typename T::value_type>::max()); - - for(int i = std::numeric_limits<typename T::value_type>::min(); i <= std::numeric_limits<typename T::value_type>::max(); i++) - { - table[i] = distribution(generator); - } -} - /** Convert an asymmetric quantized simple tensor into float using tensor quantization information. * * @param[in] src Quantized tensor. |