diff options
Diffstat (limited to 'examples/neon_convolution.cpp')
| -rw-r--r-- | examples/neon_convolution.cpp | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/examples/neon_convolution.cpp b/examples/neon_convolution.cpp index 1a7e865908..56b4ddc0be 100644 --- a/examples/neon_convolution.cpp +++ b/examples/neon_convolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2018 ARM Limited. + * Copyright (c) 2016-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -32,7 +32,7 @@ using namespace utils; /** Gaussian 3x3 matrix */ -const int16_t gaussian3x3[] = +const std::array<int16_t, 9> gaussian3x3 = { 1, 2, 1, 2, 4, 2, @@ -41,7 +41,7 @@ const int16_t gaussian3x3[] = /** Gaussian 5x5 matrix */ -const int16_t gaussian5x5[] = +const std::array<int16_t, 25> gaussian5x5 = { 1, 4, 6, 4, 1, 4, 16, 24, 16, 4, @@ -79,8 +79,8 @@ public: // Apply a Gaussian 3x3 filter to the source image followed by a Gaussian 5x5: // The function will automatically update the padding information inside input and output to match its requirements - conv3x3.configure(&src, &tmp, gaussian3x3, 0 /* Let arm_compute calculate the scale */, BorderMode::UNDEFINED); - conv5x5.configure(&tmp, &dst, gaussian5x5, 0 /* Let arm_compute calculate the scale */, BorderMode::UNDEFINED); + conv3x3.configure(&src, &tmp, gaussian3x3.data(), 0 /* Let arm_compute calculate the scale */, BorderMode::UNDEFINED); + conv5x5.configure(&tmp, &dst, gaussian5x5.data(), 0 /* Let arm_compute calculate the scale */, BorderMode::UNDEFINED); // Now that the padding requirements are known we can allocate the images: src.allocator()->allocate(); |