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<div class="title">box_with_nms_limit_op.cc</div> </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#include "box_with_nms_limit_op.h"</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#include "caffe2/utils/eigen_utils.h"</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="preprocessor">#include "generate_proposals_op_util_nms.h"</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> </div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#ifdef CAFFE2_USE_MKL</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "caffe2/mkl/operators/operator_fallback_mkl.h"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#endif // CAFFE2_USE_MKL</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="keyword">namespace </span><a class="code" href="namespacecaffe2.html">caffe2</a> {</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="keyword">namespace </span>{</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">template</span> <<span class="keyword">class</span> Derived, <span class="keyword">class</span> Func></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> vector<int> filter_with_indices(</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  <span class="keyword">const</span> Eigen::ArrayBase<Derived>& array,</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">const</span> vector<int>& indices,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">const</span> Func& func) {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  vector<int> ret;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& cur : indices) {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keywordflow">if</span> (func(array[cur])) {</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  ret.push_back(cur);</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  }</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  }</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> }</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keywordtype">bool</span> BoxWithNMSLimitOp<CPUContext>::RunOnDevice() {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& tscores = Input(0);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& tboxes = Input(1);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">auto</span>* out_scores = Output(0);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">auto</span>* out_boxes = Output(1);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">auto</span>* out_classes = Output(2);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="comment">// tscores: (num_boxes, num_classes), 0 for background</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">if</span> (tscores.ndim() == 4) {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  CAFFE_ENFORCE_EQ(tscores.dim(2), 1, tscores.dim(2));</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  CAFFE_ENFORCE_EQ(tscores.dim(3), 1, tscores.dim(3));</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  CAFFE_ENFORCE_EQ(tscores.ndim(), 2, tscores.ndim());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  CAFFE_ENFORCE(tscores.template IsType<float>(), tscores.meta().name());</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// tboxes: (num_boxes, num_classes * 4)</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">if</span> (tboxes.ndim() == 4) {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  CAFFE_ENFORCE_EQ(tboxes.dim(2), 1, tboxes.dim(2));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  CAFFE_ENFORCE_EQ(tboxes.dim(3), 1, tboxes.dim(3));</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  CAFFE_ENFORCE_EQ(tboxes.ndim(), 2, tboxes.ndim());</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  }</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  CAFFE_ENFORCE(tboxes.template IsType<float>(), tboxes.meta().name());</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordtype">int</span> N = tscores.dim(0);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordtype">int</span> num_classes = tscores.dim(1);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  CAFFE_ENFORCE_EQ(N, tboxes.dim(0));</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  CAFFE_ENFORCE_EQ(num_classes * 4, tboxes.dim(1));</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordtype">int</span> batch_size = 1;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  vector<float> batch_splits_default(1, tscores.dim(0));</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* batch_splits_data = batch_splits_default.data();</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">if</span> (InputSize() > 2) {</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// tscores and tboxes have items from multiple images in a batch. Get the</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// corresponding batch splits from input.</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& tbatch_splits = Input(2);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  CAFFE_ENFORCE_EQ(tbatch_splits.ndim(), 1);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  batch_size = tbatch_splits.dim(0);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  batch_splits_data = tbatch_splits.data<<span class="keywordtype">float</span>>();</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  Eigen::Map<const EArrXf> batch_splits(batch_splits_data, batch_size);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  CAFFE_ENFORCE_EQ(batch_splits.sum(), N);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  out_scores->Resize(0);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  out_boxes->Resize(0, 4);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  out_classes->Resize(0);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  TensorCPU* out_keeps = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  TensorCPU* out_keeps_size = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">if</span> (OutputSize() > 4) {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  out_keeps = Output(4);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  out_keeps_size = Output(5);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  out_keeps->Resize(0);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  out_keeps_size->Resize(batch_size, num_classes);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  vector<int> total_keep_per_batch(batch_size);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordtype">int</span> offset = 0;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> b = 0; b < batch_splits.size(); ++b) {</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordtype">int</span> num_boxes = batch_splits(b);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  Eigen::Map<const ERArrXXf> scores(</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  tscores.data<<span class="keywordtype">float</span>>() + offset * tscores.dim(1),</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  num_boxes,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  tscores.dim(1));</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  Eigen::Map<const ERArrXXf> boxes(</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  tboxes.data<<span class="keywordtype">float</span>>() + offset * tboxes.dim(1),</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  num_boxes,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  tboxes.dim(1));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// To store updated scores if SoftNMS is used</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  ERArrXXf soft_nms_scores(num_boxes, tscores.dim(1));</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  vector<vector<int>> keeps(num_classes);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// Perform nms to each class</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="comment">// skip j = 0, because it's the background class</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordtype">int</span> total_keep_count = 0;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 1; j < num_classes; j++) {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">auto</span> cur_scores = scores.col(j);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">auto</span> inds = utils::GetArrayIndices(cur_scores > score_thres_);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">auto</span> cur_boxes = boxes.block(0, j * 4, boxes.rows(), 4);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">if</span> (soft_nms_enabled_) {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">auto</span> cur_soft_nms_scores = soft_nms_scores.col(j);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  keeps[j] = utils::soft_nms_cpu(</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  &cur_soft_nms_scores,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  cur_boxes,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  cur_scores,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  inds,</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  soft_nms_sigma_,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  nms_thres_,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  soft_nms_min_score_thres_,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  soft_nms_method_);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::sort(</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  inds.data(),</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  inds.data() + inds.size(),</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  [&cur_scores](<span class="keywordtype">int</span> lhs, <span class="keywordtype">int</span> rhs) {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">return</span> cur_scores(lhs) > cur_scores(rhs);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  });</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  keeps[j] = utils::nms_cpu(cur_boxes, cur_scores, inds, nms_thres_);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  total_keep_count += keeps[j].size();</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  }</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">if</span> (soft_nms_enabled_) {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// Re-map scores to the updated SoftNMS scores</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">new</span> (&scores) Eigen::Map<const ERArrXXf>(</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  soft_nms_scores.data(),</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  soft_nms_scores.rows(),</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  soft_nms_scores.cols());</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  }</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Limit to max_per_image detections *over all classes*</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">if</span> (detections_per_im_ > 0 && total_keep_count > detections_per_im_) {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">// merge all scores together and sort</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">auto</span> get_all_scores_sorted = [&scores, &keeps, total_keep_count]() {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  EArrXf ret(total_keep_count);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordtype">int</span> ret_idx = 0;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i < keeps.size(); i++) {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keyword">auto</span>& cur_keep = keeps[i];</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">auto</span> cur_scores = scores.col(i);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">auto</span> cur_ret = ret.segment(ret_idx, cur_keep.size());</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  utils::GetSubArray(cur_scores, utils::AsEArrXt(keeps[i]), &cur_ret);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  ret_idx += cur_keep.size();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  }</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  std::sort(ret.data(), ret.data() + ret.size());</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  };</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">// Compute image thres based on all classes</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">auto</span> all_scores_sorted = get_all_scores_sorted();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  DCHECK_GT(all_scores_sorted.size(), detections_per_im_);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">auto</span> image_thresh =</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  all_scores_sorted[all_scores_sorted.size() - detections_per_im_];</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  total_keep_count = 0;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// filter results with image_thresh</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 1; j < num_classes; j++) {</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">auto</span>& cur_keep = keeps[j];</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">auto</span> cur_scores = scores.col(j);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  keeps[j] = filter_with_indices(</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  cur_scores, cur_keep, [&image_thresh](<span class="keywordtype">float</span> sc) {</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">return</span> sc >= image_thresh;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  });</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  total_keep_count += keeps[j].size();</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  }</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  total_keep_per_batch[b] = total_keep_count;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// Write results</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordtype">int</span> cur_start_idx = out_scores->dim(0);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  out_scores->Extend(total_keep_count, 50, &context_);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  out_boxes->Extend(total_keep_count, 50, &context_);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  out_classes->Extend(total_keep_count, 50, &context_);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordtype">int</span> cur_out_idx = 0;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 1; j < num_classes; j++) {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">auto</span> cur_scores = scores.col(j);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keyword">auto</span> cur_boxes = boxes.block(0, j * 4, boxes.rows(), 4);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keyword">auto</span>& cur_keep = keeps[j];</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  Eigen::Map<EArrXf> cur_out_scores(</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  out_scores->mutable_data<<span class="keywordtype">float</span>>() + cur_start_idx + cur_out_idx,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  cur_keep.size());</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  Eigen::Map<ERArrXXf> cur_out_boxes(</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  out_boxes->mutable_data<<span class="keywordtype">float</span>>() + (cur_start_idx + cur_out_idx) * 4,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  cur_keep.size(),</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  4);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  Eigen::Map<EArrXf> cur_out_classes(</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  out_classes->mutable_data<<span class="keywordtype">float</span>>() + cur_start_idx + cur_out_idx,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  cur_keep.size());</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  utils::GetSubArray(</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  cur_scores, utils::AsEArrXt(cur_keep), &cur_out_scores);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  utils::GetSubArrayRows(</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  cur_boxes, utils::AsEArrXt(cur_keep), &cur_out_boxes);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < cur_keep.size(); k++) {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  cur_out_classes[k] = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(j);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  cur_out_idx += cur_keep.size();</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">if</span> (out_keeps) {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  out_keeps->Extend(total_keep_count, 50, &context_);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  Eigen::Map<EArrXi> out_keeps_arr(</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  out_keeps->mutable_data<<span class="keywordtype">int</span>>() + cur_start_idx, total_keep_count);</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  Eigen::Map<EArrXi> cur_out_keeps_size(</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  out_keeps_size->mutable_data<<span class="keywordtype">int</span>>() + b * num_classes, num_classes);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  cur_out_idx = 0;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < num_classes; j++) {</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  out_keeps_arr.segment(cur_out_idx, keeps[j].size()) =</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  utils::AsEArrXt(keeps[j]);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  cur_out_keeps_size[j] = keeps[j].size();</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  cur_out_idx += keeps[j].size();</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  }</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  offset += num_boxes;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordflow">if</span> (OutputSize() > 3) {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keyword">auto</span>* batch_splits_out = Output(3);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  batch_splits_out->Resize(batch_size);</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  Eigen::Map<EArrXf> batch_splits_out_map(</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  batch_splits_out->mutable_data<<span class="keywordtype">float</span>>(), batch_size);</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  batch_splits_out_map =</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  Eigen::Map<const EArrXi>(total_keep_per_batch.data(), batch_size)</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  .cast<float>();</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  }</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> }</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="keyword">namespace </span>{</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> REGISTER_CPU_OPERATOR(BoxWithNMSLimit, BoxWithNMSLimitOp<CPUContext>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="preprocessor">#ifdef CAFFE2_HAS_MKL_DNN</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> REGISTER_MKL_OPERATOR(</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  BoxWithNMSLimit,</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  mkl::MKLFallbackOp<BoxWithNMSLimitOp<CPUContext>>);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="preprocessor">#endif // CAFFE2_HAS_MKL_DNN</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> OPERATOR_SCHEMA(BoxWithNMSLimit)</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  .NumInputs(2, 3)</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  .NumOutputs(3, 6)</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  .SetDoc(R<span class="stringliteral">"DOC(</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="stringliteral">Apply NMS to each class (except background) and limit the number of</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="stringliteral">returned boxes.</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="stringliteral">)DOC")</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="stringliteral"> .Arg(</span><span class="stringliteral">"score_thresh"</span>, <span class="stringliteral">"(float) TEST.SCORE_THRESH"</span>)</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  .Arg(<span class="stringliteral">"nms"</span>, <span class="stringliteral">"(float) TEST.NMS"</span>)</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  .Arg(<span class="stringliteral">"detections_per_im"</span>, <span class="stringliteral">"(int) TEST.DEECTIONS_PER_IM"</span>)</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  .Arg(<span class="stringliteral">"soft_nms_enabled"</span>, <span class="stringliteral">"(bool) TEST.SOFT_NMS.ENABLED"</span>)</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  .Arg(<span class="stringliteral">"soft_nms_method"</span>, <span class="stringliteral">"(string) TEST.SOFT_NMS.METHOD"</span>)</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  .Arg(<span class="stringliteral">"soft_nms_sigma"</span>, <span class="stringliteral">"(float) TEST.SOFT_NMS.SIGMA"</span>)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  .Arg(</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="stringliteral">"soft_nms_min_score_thres"</span>,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="stringliteral">"(float) Lower bound on updated scores to discard boxes"</span>)</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  .Input(0, <span class="stringliteral">"scores"</span>, <span class="stringliteral">"Scores, size (count, num_classes)"</span>)</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  .Input(</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  1,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="stringliteral">"boxes"</span>,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="stringliteral">"Bounding box for each class, size (count, num_classes * 4)"</span>)</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  .Input(</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  2,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="stringliteral">"batch_splits"</span>,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="stringliteral">"Tensor of shape (batch_size) with each element denoting the number "</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="stringliteral">"of RoIs/boxes belonging to the corresponding image in batch. "</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="stringliteral">"Sum should add up to total count of scores/boxes."</span>)</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  .Output(0, <span class="stringliteral">"scores"</span>, <span class="stringliteral">"Filtered scores, size (n)"</span>)</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  .Output(1, <span class="stringliteral">"boxes"</span>, <span class="stringliteral">"Filtered boxes, size (n, 4)"</span>)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  .Output(2, <span class="stringliteral">"classes"</span>, <span class="stringliteral">"Class id for each filtered score/box, size (n)"</span>)</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  .Output(</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  3,</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="stringliteral">"batch_splits"</span>,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="stringliteral">"Output batch splits for scores/boxes after applying NMS"</span>)</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  .Output(4, <span class="stringliteral">"keeps"</span>, <span class="stringliteral">"Optional filtered indices, size (n)"</span>)</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  .Output(</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  5,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="stringliteral">"keeps_size"</span>,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="stringliteral">"Optional number of filtered indices per class, size (num_classes)"</span>);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> SHOULD_NOT_DO_GRADIENT(BoxWithNMSLimit);</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> } <span class="comment">// namespace caffe2</span></div><div class="ttc" id="namespacecaffe2_html"><div class="ttname"><a href="namespacecaffe2.html">caffe2</a></div><div class="ttdoc">A global dictionary that holds information about what Caffe2 modules have been loaded in the current ...</div><div class="ttdef"><b>Definition:</b> <a href="convert__encoded__to__raw__leveldb_8cc_source.html#l00047">convert_encoded_to_raw_leveldb.cc:47</a></div></div>
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