RoIPooling

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代码：

template <typename Dtype>

void ROIPoolingLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,

      const vector<Blob<Dtype>*>& top) {

  //输入有两部分组成，data和rois

  const Dtype* bottom_data = bottom[0]->cpu_data();

  const Dtype* bottom_rois = bottom[1]->cpu_data();

  // Number of ROIs

  int num_rois = bottom[1]->num();

  int batch_size = bottom[0]->num();

  int top_count = top[0]->count();

  Dtype* top_data = top[0]->mutable_cpu_data();

  caffe_set(top_count, Dtype(-FLT_MAX), top_data);

  int* argmax_data = max_idx_.mutable_cpu_data();

  caffe_set(top_count, -1, argmax_data);

  // For each ROI R = [batch_index x1 y1 x2 y2]: max pool over R

  for (int n = 0; n < num_rois; ++n) {

    int roi_batch_ind = bottom_rois[0];

    //把原图的坐标映射到feature map上面

    int roi_start_w = round(bottom_rois[1] * spatial_scale_);

    int roi_start_h = round(bottom_rois[2] * spatial_scale_);

    int roi_end_w = round(bottom_rois[3] * spatial_scale_);

    int roi_end_h = round(bottom_rois[4] * spatial_scale_);

    //计算每个roi在feature map上面的大小

    int roi_height = max(roi_end_h - roi_start_h + 1, 1);

    int roi_width = max(roi_end_w - roi_start_w + 1, 1);

    //pooling之后的feature map的一个值对应于pooling之前的feature map上的大小

    //注：由于roi的大小不一致，所以每次都需要计算一次

    const Dtype bin_size_h = static_cast<Dtype>(roi_height)

                             / static_cast<Dtype>(pooled_height_);

    const Dtype bin_size_w = static_cast<Dtype>(roi_width)

                             / static_cast<Dtype>(pooled_width_);

    //找到对应的roi的feature map，如果input data的batch size为1

    //那么roi_batch_ind=0

    const Dtype* batch_data = bottom_data + bottom[0]->offset(roi_batch_ind);

    //pooling的过程是针对每一个channel的，所以需要循环遍历

    for (int c = 0; c < channels_; ++c) {

      //计算output的每一个值，所以需要遍历一遍output，然后求出所有值

      for (int ph = 0; ph < pooled_height_; ++ph) {

        for (int pw = 0; pw < pooled_width_; ++pw) {

          // Compute pooling region for this output unit:

          //  start (included) = floor(ph * roi_height / pooled_height_)

          //  end (excluded) = ceil((ph + 1) * roi_height / pooled_height_)

          // 计算output上的一点对应于input上面区域的大小[hstart, wstart, hend, wend]

          int hstart = static_cast<int>(floor(static_cast<Dtype>(ph)

                                              * bin_size_h));

          int hend = static_cast<int>(ceil(static_cast<Dtype>(ph + 1)

                                           * bin_size_h));

          int wstart = static_cast<int>(floor(static_cast<Dtype>(pw)

                                              * bin_size_w));

          int wend = static_cast<int>(ceil(static_cast<Dtype>(pw + 1)

                                           * bin_size_w));

          //将映射后的区域平动到对应的位置[hstart, wstart, hend, wend]

          hstart = min(max(hstart + roi_start_h, 0), height_);

          hend = min(max(hend + roi_start_h, 0), height_);

          wstart = min(max(wstart + roi_start_w, 0), width_);

          wend = min(max(wend + roi_start_w, 0), width_);

          //如果映射后的矩形框不符合

          bool is_empty = (hend <= hstart) || (wend <= wstart);

          //pool_index指的是此时计算的output的值对应于output的位置

          const int pool_index = ph * pooled_width_ + pw;

          //如果矩形不符合，此处output的值设为0，此处的对应于输入区域的最大值为-1

          if (is_empty) {

            top_data[pool_index] = 0;

            argmax_data[pool_index] = -1;

          }

          //遍历output的值对应于input的区域块

          for (int h = hstart; h < hend; ++h) {

            for (int w = wstart; w < wend; ++w) {

             // 对应于input上的位置

              const int index = h * width_ + w;

              //计算区域块的最大值，保存在output对应的位置上

              //同时记录最大值的索引

              if (batch_data[index] > top_data[pool_index]) {

                top_data[pool_index] = batch_data[index];

                argmax_data[pool_index] = index;

              }

            }

          }

        }

      }

      // Increment all data pointers by one channel

      batch_data += bottom[0]->offset(0, 1);

      top_data += top[0]->offset(0, 1);

      argmax_data += max_idx_.offset(0, 1);

    }

    // Increment ROI data pointer

    bottom_rois += bottom[1]->offset(1);

  }

}