arm_compute v19.05
diff --git a/examples/neon_convolution.cpp b/examples/neon_convolution.cpp
index 1a7e865..56b4ddc 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 @@
/** Gaussian 3x3 matrix
*/
-const int16_t gaussian3x3[] =
+const std::array<int16_t, 9> gaussian3x3 =
{
1, 2, 1,
2, 4, 2,
@@ -41,7 +41,7 @@
/** 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 @@
// 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();