Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "Resize.hpp" |
| 7 | |
| 8 | #include "TensorBufferArrayView.hpp" |
| 9 | |
| 10 | #include <boost/numeric/conversion/cast.hpp> |
| 11 | |
| 12 | #include <cmath> |
| 13 | #include <algorithm> |
| 14 | |
| 15 | using namespace armnnUtils; |
| 16 | |
| 17 | namespace armnn |
| 18 | { |
| 19 | |
| 20 | namespace |
| 21 | { |
| 22 | |
| 23 | inline float Lerp(float a, float b, float w) |
| 24 | { |
| 25 | return w * b + (1.f - w) * a; |
| 26 | } |
| 27 | |
Teresa Charlin | da1fb9b | 2019-07-02 13:25:22 +0100 | [diff] [blame] | 28 | inline double EuclideanDistance(float Xa, float Ya, const unsigned int Xb, const unsigned int Yb) |
| 29 | { |
| 30 | return std::sqrt(pow(Xa - boost::numeric_cast<float>(Xb), 2) + pow(Ya - boost::numeric_cast<float>(Yb), 2)); |
| 31 | } |
| 32 | |
Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 33 | }// anonymous namespace |
| 34 | |
| 35 | void Resize(Decoder<float>& in, |
| 36 | const TensorInfo& inputInfo, |
| 37 | Encoder<float>& out, |
| 38 | const TensorInfo& outputInfo, |
| 39 | DataLayoutIndexed dataLayout, |
| 40 | armnn::ResizeMethod resizeMethod) |
| 41 | { |
| 42 | // We follow the definition of TensorFlow and AndroidNN: the top-left corner of a texel in the output |
| 43 | // image is projected into the input image to figure out the interpolants and weights. Note that this |
| 44 | // will yield different results than if projecting the centre of output texels. |
| 45 | |
| 46 | const unsigned int batchSize = inputInfo.GetShape()[0]; |
| 47 | const unsigned int channelCount = inputInfo.GetShape()[dataLayout.GetChannelsIndex()]; |
| 48 | |
| 49 | const unsigned int inputHeight = inputInfo.GetShape()[dataLayout.GetHeightIndex()]; |
| 50 | const unsigned int inputWidth = inputInfo.GetShape()[dataLayout.GetWidthIndex()]; |
| 51 | const unsigned int outputHeight = outputInfo.GetShape()[dataLayout.GetHeightIndex()]; |
| 52 | const unsigned int outputWidth = outputInfo.GetShape()[dataLayout.GetWidthIndex()]; |
| 53 | |
| 54 | // How much to scale pixel coordinates in the output image, to get the corresponding pixel coordinates |
| 55 | // in the input image. |
| 56 | const float scaleY = boost::numeric_cast<float>(inputHeight) / boost::numeric_cast<float>(outputHeight); |
| 57 | const float scaleX = boost::numeric_cast<float>(inputWidth) / boost::numeric_cast<float>(outputWidth); |
| 58 | |
| 59 | TensorShape inputShape = inputInfo.GetShape(); |
| 60 | TensorShape outputShape = outputInfo.GetShape(); |
| 61 | |
| 62 | for (unsigned int n = 0; n < batchSize; ++n) |
| 63 | { |
| 64 | for (unsigned int c = 0; c < channelCount; ++c) |
| 65 | { |
| 66 | for (unsigned int y = 0; y < outputHeight; ++y) |
| 67 | { |
| 68 | // Corresponding real-valued height coordinate in input image. |
| 69 | const float iy = boost::numeric_cast<float>(y) * scaleY; |
| 70 | |
| 71 | // Discrete height coordinate of top-left texel (in the 2x2 texel area used for interpolation). |
| 72 | const float fiy = floorf(iy); |
| 73 | const unsigned int y0 = boost::numeric_cast<unsigned int>(fiy); |
| 74 | |
| 75 | // Interpolation weight (range [0,1]). |
| 76 | const float yw = iy - fiy; |
| 77 | |
| 78 | for (unsigned int x = 0; x < outputWidth; ++x) |
| 79 | { |
| 80 | // Real-valued and discrete width coordinates in input image. |
| 81 | const float ix = boost::numeric_cast<float>(x) * scaleX; |
| 82 | const float fix = floorf(ix); |
| 83 | const unsigned int x0 = boost::numeric_cast<unsigned int>(fix); |
| 84 | |
| 85 | // Interpolation weight (range [0,1]). |
| 86 | const float xw = ix - fix; |
| 87 | |
| 88 | // Discrete width/height coordinates of texels below and to the right of (x0, y0). |
| 89 | const unsigned int x1 = std::min(x0 + 1, inputWidth - 1u); |
| 90 | const unsigned int y1 = std::min(y0 + 1, inputHeight - 1u); |
| 91 | |
| 92 | float interpolatedValue; |
| 93 | switch (resizeMethod) |
| 94 | { |
| 95 | case armnn::ResizeMethod::Bilinear: |
| 96 | { |
| 97 | in[dataLayout.GetIndex(inputShape, n, c, y0, x0)]; |
| 98 | float input1 = in.Get(); |
| 99 | in[dataLayout.GetIndex(inputShape, n, c, y0, x1)]; |
| 100 | float input2 = in.Get(); |
| 101 | in[dataLayout.GetIndex(inputShape, n, c, y1, x0)]; |
| 102 | float input3 = in.Get(); |
| 103 | in[dataLayout.GetIndex(inputShape, n, c, y1, x1)]; |
| 104 | float input4 = in.Get(); |
| 105 | |
| 106 | const float ly0 = Lerp(input1, input2, xw); // lerp along row y0. |
| 107 | const float ly1 = Lerp(input3, input4, xw); // lerp along row y1. |
| 108 | interpolatedValue = Lerp(ly0, ly1, yw); |
| 109 | break; |
| 110 | } |
| 111 | case armnn::ResizeMethod::NearestNeighbor: |
Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 112 | { |
Teresa Charlin | da1fb9b | 2019-07-02 13:25:22 +0100 | [diff] [blame] | 113 | // calculate euclidean distance to the 4 neighbours |
| 114 | auto distance00 = EuclideanDistance(fix, fiy, x0, y0); |
| 115 | auto distance01 = EuclideanDistance(fix, fiy, x0, y1); |
| 116 | auto distance10 = EuclideanDistance(fix, fiy, x1, y0); |
| 117 | auto distance11 = EuclideanDistance(fix, fiy, x1, y1); |
Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 118 | |
Teresa Charlin | da1fb9b | 2019-07-02 13:25:22 +0100 | [diff] [blame] | 119 | auto minimum = std::min( { distance00, distance01, distance10, distance11 } ); |
| 120 | |
| 121 | unsigned int xNearest = 0; |
| 122 | unsigned int yNearest = 0; |
| 123 | |
| 124 | if (minimum == distance00) |
| 125 | { |
| 126 | xNearest = x0; |
| 127 | yNearest = y0; |
| 128 | } |
| 129 | else if (minimum == distance01) |
| 130 | { |
| 131 | xNearest = x0; |
| 132 | yNearest = y1; |
| 133 | } |
| 134 | else if (minimum == distance10) |
| 135 | { |
| 136 | xNearest = x1; |
| 137 | yNearest = y0; |
| 138 | } |
| 139 | else if (minimum == distance11) |
| 140 | { |
| 141 | xNearest = x1; |
| 142 | yNearest = y1; |
| 143 | } |
| 144 | else |
| 145 | { |
| 146 | throw armnn::InvalidArgumentException("Resize Nearest Neighbor failure"); |
| 147 | } |
Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 148 | |
| 149 | in[dataLayout.GetIndex(inputShape, n, c, yNearest, xNearest)]; |
| 150 | interpolatedValue = in.Get(); |
| 151 | break; |
| 152 | } |
Teresa Charlin | da1fb9b | 2019-07-02 13:25:22 +0100 | [diff] [blame] | 153 | default: |
| 154 | throw armnn::InvalidArgumentException("Unknown resize method: " + |
| 155 | std::to_string(static_cast<int>(resizeMethod))); |
Teresa Charlin | 970f43b | 2019-07-01 13:51:07 +0100 | [diff] [blame] | 156 | } |
| 157 | out[dataLayout.GetIndex(outputShape, n, c, y, x)]; |
| 158 | out.Set(interpolatedValue); |
| 159 | } |
| 160 | } |
| 161 | } |
| 162 | } |
| 163 | } |
| 164 | |
| 165 | } //namespace armnn |