1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
|
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ResizeBilinear.hpp"
#include "TensorBufferArrayView.hpp"
#include <boost/numeric/conversion/cast.hpp>
#include <cmath>
#include <algorithm>
using namespace armnnUtils;
namespace armnn
{
namespace
{
inline float Lerp(float a, float b, float w)
{
return w * b + (1.f - w) * a;
}
}
void ResizeBilinear(const float* in,
const TensorInfo& inputInfo,
float* out,
const TensorInfo& outputInfo,
DataLayoutIndexed dataLayout)
{
// We follow the definition of TensorFlow and AndroidNN: the top-left corner of a texel in the output
// image is projected into the input image to figure out the interpolants and weights. Note that this
// will yield different results than if projecting the centre of output texels.
const unsigned int batchSize = inputInfo.GetShape()[0];
const unsigned int channelCount = inputInfo.GetShape()[dataLayout.GetChannelsIndex()];
const unsigned int inputHeight = inputInfo.GetShape()[dataLayout.GetHeightIndex()];
const unsigned int inputWidth = inputInfo.GetShape()[dataLayout.GetWidthIndex()];
const unsigned int outputHeight = outputInfo.GetShape()[dataLayout.GetHeightIndex()];
const unsigned int outputWidth = outputInfo.GetShape()[dataLayout.GetWidthIndex()];
// How much to scale pixel coordinates in the output image, to get the corresponding pixel coordinates
// in the input image.
const float scaleY = boost::numeric_cast<float>(inputHeight) / boost::numeric_cast<float>(outputHeight);
const float scaleX = boost::numeric_cast<float>(inputWidth) / boost::numeric_cast<float>(outputWidth);
TensorBufferArrayView<const float> input(inputInfo.GetShape(), in, dataLayout);
TensorBufferArrayView<float> output(outputInfo.GetShape(), out, dataLayout);
for (unsigned int n = 0; n < batchSize; ++n)
{
for (unsigned int c = 0; c < channelCount; ++c)
{
for (unsigned int y = 0; y < outputHeight; ++y)
{
// Corresponding real-valued height coordinate in input image.
const float iy = boost::numeric_cast<float>(y) * scaleY;
// Discrete height coordinate of top-left texel (in the 2x2 texel area used for interpolation).
const float fiy = floorf(iy);
const unsigned int y0 = boost::numeric_cast<unsigned int>(fiy);
// Interpolation weight (range [0,1]).
const float yw = iy - fiy;
for (unsigned int x = 0; x < outputWidth; ++x)
{
// Real-valued and discrete width coordinates in input image.
const float ix = boost::numeric_cast<float>(x) * scaleX;
const float fix = floorf(ix);
const unsigned int x0 = boost::numeric_cast<unsigned int>(fix);
// Interpolation weight (range [0,1]).
const float xw = ix - fix;
// Discrete width/height coordinates of texels below and to the right of (x0, y0).
const unsigned int x1 = std::min(x0 + 1, inputWidth - 1u);
const unsigned int y1 = std::min(y0 + 1, inputHeight - 1u);
// Interpolation
const float ly0 = Lerp(input.Get(n, c, y0, x0), input.Get(n, c, y0, x1), xw); // lerp along row y0.
const float ly1 = Lerp(input.Get(n, c, y1, x0), input.Get(n, c, y1, x1), xw); // lerp along row y1.
const float l = Lerp(ly0, ly1, yw);
output.Get(n, c, y, x) = l;
}
}
}
}
}
} //namespace armnn
|
