George Wort | 05398a9 | 2019-01-25 15:38:33 +0000 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2019 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "CropResize.h" |
| 25 | #include "Utils.h" |
| 26 | |
| 27 | namespace arm_compute |
| 28 | { |
| 29 | namespace test |
| 30 | { |
| 31 | namespace validation |
| 32 | { |
| 33 | namespace reference |
| 34 | { |
| 35 | namespace |
| 36 | { |
| 37 | SimpleTensor<float> scale_image(const SimpleTensor<float> &in, const TensorShape &out_shape, InterpolationPolicy policy, float extrapolation_value) |
| 38 | { |
| 39 | ARM_COMPUTE_ERROR_ON(in.data_layout() != DataLayout::NHWC); |
| 40 | |
| 41 | SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC }; |
| 42 | // Compute the ratio between source width/height and destination width/height |
| 43 | const auto wr = static_cast<float>(in.shape()[1]) / static_cast<float>(out_shape[1]); |
| 44 | const auto hr = static_cast<float>(in.shape()[2]) / static_cast<float>(out_shape[2]); |
| 45 | |
| 46 | const auto width = static_cast<int>(in.shape().y()); |
| 47 | const auto height = static_cast<int>(in.shape().z()); |
| 48 | |
| 49 | Window win; |
| 50 | win.use_tensor_dimensions(out_shape); |
| 51 | execute_window_loop(win, [&](const Coordinates & out_id) |
| 52 | { |
| 53 | Coordinates in_id(out_id); |
| 54 | int idw = in_id.y(); |
| 55 | int idh = in_id.z(); |
| 56 | |
| 57 | switch(policy) |
| 58 | { |
| 59 | case InterpolationPolicy::NEAREST_NEIGHBOR: |
| 60 | { |
| 61 | //Calculate the source coords without -0.5f is equivalent to round the x_scr/y_src coords |
| 62 | float x_src = (idw + 0.5f) * wr; |
| 63 | float y_src = (idh + 0.5f) * hr; |
| 64 | in_id.set(1, x_src); |
| 65 | in_id.set(2, y_src); |
| 66 | |
| 67 | // If coordinates in range of tensor's width or height |
| 68 | if(is_valid_pixel_index(x_src, y_src, width, height, 0)) |
| 69 | { |
| 70 | *reinterpret_cast<float *>(out(out_id)) = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value); |
| 71 | } |
| 72 | else |
| 73 | { |
| 74 | *reinterpret_cast<float *>(out(out_id)) = extrapolation_value; |
| 75 | } |
| 76 | break; |
| 77 | } |
| 78 | case InterpolationPolicy::BILINEAR: |
| 79 | { |
| 80 | float x_src = idw * wr; |
| 81 | float y_src = idh * hr; |
| 82 | in_id.set(1, std::floor(x_src)); |
| 83 | in_id.set(2, std::floor(y_src)); |
| 84 | if(is_valid_pixel_index(x_src, y_src, width, height, 0)) |
| 85 | { |
| 86 | const int id_w = in_id[1]; |
| 87 | const int id_h = in_id[2]; |
| 88 | |
| 89 | const float dx = x_src - id_w; |
| 90 | const float dy = y_src - id_h; |
| 91 | const float dx_1 = 1.0f - dx; |
| 92 | const float dy_1 = 1.0f - dy; |
| 93 | |
| 94 | in_id.set(1, id_w); |
| 95 | in_id.set(2, id_h); |
| 96 | const float tl = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value); |
| 97 | in_id.set(1, id_w + 1); |
| 98 | in_id.set(2, id_h); |
| 99 | const float tr = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value); |
| 100 | in_id.set(1, id_w); |
| 101 | in_id.set(2, id_h + 1); |
| 102 | const float bl = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value); |
| 103 | in_id.set(1, id_w + 1); |
| 104 | in_id.set(2, id_h + 1); |
| 105 | const float br = tensor_elem_at(in, in_id, BorderMode::CONSTANT, extrapolation_value); |
| 106 | |
| 107 | *reinterpret_cast<float *>(out(out_id)) = tl * (dx_1 * dy_1) + tr * (dx * dy_1) + bl * (dx_1 * dy) + br * (dx * dy); |
| 108 | } |
| 109 | else |
| 110 | { |
| 111 | *reinterpret_cast<float *>(out(out_id)) = extrapolation_value; |
| 112 | } |
| 113 | break; |
| 114 | } |
| 115 | default: |
| 116 | ARM_COMPUTE_ERROR("Unsupported interpolation mode"); |
| 117 | } |
| 118 | }); |
| 119 | |
| 120 | return out; |
| 121 | } |
| 122 | |
| 123 | template <typename T> |
| 124 | SimpleTensor<float> crop_image(const SimpleTensor<T> &src, Coordinates start, Coordinates end, int32_t batch_index, float extrapolation_value) |
| 125 | { |
| 126 | TensorShape out_shape(src.shape()[0], abs(end[0] - start[0]) + 1, abs(end[1] - start[1]) + 1); |
| 127 | |
| 128 | SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC }; |
| 129 | |
| 130 | Window win; |
| 131 | win.use_tensor_dimensions(out_shape); |
| 132 | execute_window_loop(win, [&](const Coordinates & id) |
| 133 | { |
| 134 | bool out_of_bounds = false; |
| 135 | Coordinates offset(id[0], 0, 0, batch_index); |
| 136 | for(uint32_t i = 1; i < 3; ++i) |
| 137 | { |
| 138 | offset.set(i, end[i - 1] < start[i - 1] ? start[i - 1] - id[i] : start[i - 1] + id[i]); |
| 139 | if(offset[i] < 0 || static_cast<uint32_t>(offset[i]) > src.shape()[i] - 1) |
| 140 | { |
| 141 | out_of_bounds = true; |
| 142 | break; |
| 143 | } |
| 144 | } |
| 145 | if(!out_of_bounds) |
| 146 | { |
| 147 | *reinterpret_cast<float *>(out(id)) = static_cast<float>(*reinterpret_cast<const T *>(src(offset))); |
| 148 | } |
| 149 | else |
| 150 | { |
| 151 | *reinterpret_cast<float *>(out(id)) = extrapolation_value; |
| 152 | } |
| 153 | }); |
| 154 | return out; |
| 155 | } |
| 156 | |
| 157 | } // namespace |
| 158 | |
| 159 | template <typename T> |
| 160 | SimpleTensor<float> crop_and_resize(const SimpleTensor<T> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 161 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value) |
| 162 | { |
| 163 | ARM_COMPUTE_ERROR_ON(src.shape().num_dimensions() > 4); |
| 164 | ARM_COMPUTE_ERROR_ON(src.data_layout() != DataLayout::NHWC); |
| 165 | |
| 166 | const TensorShape out_shape(src.shape()[0], crop_size.x, crop_size.y, boxes.shape()[1]); |
| 167 | SimpleTensor<float> out{ out_shape, DataType::F32, 1, QuantizationInfo(), DataLayout::NHWC }; |
| 168 | |
| 169 | const TensorShape scaled_image_shape(src.shape()[0], crop_size.x, crop_size.y); |
| 170 | |
| 171 | for(uint32_t i = 0; i < boxes.shape()[1]; ++i) |
| 172 | { |
| 173 | Coordinates start = Coordinates(std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(1, i)))) * (src.shape()[1] - 1) + 0.5f), |
| 174 | std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(0, i)))) * (src.shape()[2] - 1) + 0.5f)); |
| 175 | Coordinates end = Coordinates(std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(3, i)))) * (src.shape()[1] - 1) + 0.5f), |
| 176 | std::floor((*reinterpret_cast<const float *>(boxes(Coordinates(2, i)))) * (src.shape()[2] - 1) + 0.5f)); |
| 177 | SimpleTensor<float> cropped = crop_image(src, start, end, box_ind[i], extrapolation_value); |
| 178 | SimpleTensor<float> scaled = scale_image(cropped, scaled_image_shape, method, extrapolation_value); |
| 179 | std::copy_n(reinterpret_cast<float *>(scaled.data()), scaled.num_elements(), reinterpret_cast<float *>(out(Coordinates(0, 0, 0, i)))); |
| 180 | } |
| 181 | return out; |
| 182 | } |
| 183 | |
| 184 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<float> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 185 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 186 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<uint16_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 187 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 188 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<uint32_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 189 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 190 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<int16_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 191 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 192 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<int32_t> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 193 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 194 | template SimpleTensor<float> crop_and_resize(const SimpleTensor<half> &src, const SimpleTensor<float> &boxes, SimpleTensor<int32_t> box_ind, |
| 195 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value); |
| 196 | } // namespace reference |
| 197 | } // namespace validation |
| 198 | } // namespace test |
| 199 | } // namespace arm_compute |