-// Copyright (C) 2018 Intel Corporation
+// Copyright (C) 2018-2019 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
spatial_scale_ = layer->GetParamAsFloat("spatial_scale");
pooled_height_ = group_size_;
pooled_width_ = group_size_;
+ spatial_bins_x_ = static_cast<size_t>(layer->GetParamAsInt("spatial_bins_x", 1));
+ spatial_bins_y_ = static_cast<size_t>(layer->GetParamAsInt("spatial_bins_y", 1));
+ mode_ = layer->GetParamAsString("mode", "average");
SizeVector inDims = layer->insData[0].lock()->getTensorDesc().getDims();
channels = static_cast<int>(inDims[1]);
}
}
+ size_t num_bins = spatial_bins_x_*spatial_bins_y_;
+
parallel_for(real_rois, [&](int n) {
const float* bottom_rois = bottom_rois_beginning + n * 5;
int roi_batch_ind = static_cast<int>(bottom_rois[0]);
- float roi_start_w = static_cast<float>(round(bottom_rois[1])) * spatial_scale_;
- float roi_start_h = static_cast<float>(round(bottom_rois[2])) * spatial_scale_;
- float roi_end_w = static_cast<float>(round(bottom_rois[3]) + 1.0f) * spatial_scale_;
- float roi_end_h = static_cast<float>(round(bottom_rois[4]) + 1.0f) * spatial_scale_;
-
- // Force too small ROIs to be 1x1
- float roi_width = std::max<float>(roi_end_w - roi_start_w, 0.1f); // avoid 0
- float roi_height = std::max<float>(roi_end_h - roi_start_h, 0.1f);
-
- float bin_size_h = roi_height / static_cast<float>(pooled_height_);
- float bin_size_w = roi_width / static_cast<float>(pooled_width_);
+ float roi_start_w = 0.0f;
+ float roi_start_h = 0.0f;
+ float roi_end_w = 0.0f;
+ float roi_end_h = 0.0f;
+ float roi_width = 0.0f;
+ float roi_height = 0.0f;
+
+ if (mode_ == "bilinear") {
+ roi_start_w = bottom_rois[1] * spatial_scale_;
+ roi_start_h = bottom_rois[2] * spatial_scale_;
+ roi_end_w = bottom_rois[3] * spatial_scale_;
+ roi_end_h = bottom_rois[4] * spatial_scale_;
+ roi_width = roi_end_w - roi_start_w;
+ roi_height = roi_end_h - roi_start_h;
+ } else if (mode_ == "average") {
+ roi_start_w = static_cast<float>(round(bottom_rois[1])) * spatial_scale_;
+ roi_start_h = static_cast<float>(round(bottom_rois[2])) * spatial_scale_;
+ roi_end_w = static_cast<float>(round(bottom_rois[3]) + 1.0f) * spatial_scale_;
+ roi_end_h = static_cast<float>(round(bottom_rois[4]) + 1.0f) * spatial_scale_;
+ // Force too small ROIs to be 1x1
+ roi_width = std::max<float>(roi_end_w - roi_start_w, 0.1f); // avoid 0
+ roi_height = std::max<float>(roi_end_h - roi_start_h, 0.1f);
+ }
for (int c = 0; c < nc; c++) {
for (int h = 0; h < nh; h++) {
- int hstart = floor(static_cast<float>(h + 0) * bin_size_h + roi_start_h);
- int hend = ceil(static_cast<float>(h + 1) * bin_size_h + roi_start_h);
-
- hstart = std::min<int>(std::max<int>(hstart, 0), height);
- hend = std::min<int>(std::max<int>(hend, 0), height);
-
for (int w = 0; w < nw; w++) {
- int index = n * nc * nh * nw + c * nh * nw + h * nw + w;
+ size_t index = n*nc*nh*nw + c*nh*nw + h*nw + w;
dst_data[index] = 0.0f;
- int wstart = floor(static_cast<float>(w + 0) * bin_size_w + roi_start_w);
- int wend = ceil(static_cast<float>(w + 1) * bin_size_w + roi_start_w);
-
- wstart = std::min<int>(std::max<int>(wstart, 0), width);
- wend = std::min<int>(std::max<int>(wend, 0), width);
-
- float bin_area = (hend - hstart) * (wend - wstart);
- if (bin_area) {
- int gc = (c * group_size_ + h) * group_size_ + w;
- const float *bottom_data =
- bottom_data_beginning + ((roi_batch_ind * channels + gc) * height * width);
-
- float out_sum = 0.0f;
- for (int hh = hstart; hh < hend; ++hh)
- for (int ww = wstart; ww < wend; ++ww)
- out_sum += bottom_data[hh * width + ww];
-
- dst_data[index] = out_sum / bin_area;
+ if (mode_ == "average") {
+ float bin_size_h = roi_height / static_cast<float>(pooled_height_);
+ float bin_size_w = roi_width / static_cast<float>(pooled_width_);
+
+ int hstart = static_cast<int>(floor(static_cast<float>(h + 0) * bin_size_h + roi_start_h));
+ int hend = static_cast<int>(ceil(static_cast<float>(h + 1) * bin_size_h + roi_start_h));
+
+ hstart = std::min<int>(std::max<int>(hstart, 0), height);
+ hend = std::min<int>(std::max<int>(hend, 0), height);
+ int wstart = static_cast<int>(floor(static_cast<float>(w + 0) * bin_size_w + roi_start_w));
+ int wend = static_cast<int>(ceil(static_cast<float>(w + 1) * bin_size_w + roi_start_w));
+
+ wstart = std::min<int>(std::max<int>(wstart, 0), width);
+ wend = std::min<int>(std::max<int>(wend, 0), width);
+
+ float bin_area = static_cast<float>((hend - hstart) * (wend - wstart));
+ if (bin_area) {
+ int gc = (c * group_size_ + h) * group_size_ + w;
+ const float *bottom_data =
+ bottom_data_beginning + ((roi_batch_ind * channels + gc) * height * width);
+
+ float out_sum = 0.0f;
+ for (int hh = hstart; hh < hend; ++hh)
+ for (int ww = wstart; ww < wend; ++ww)
+ out_sum += bottom_data[hh * width + ww];
+
+ dst_data[index] = out_sum / bin_area;
+ }
+ } else if (mode_ == "bilinear") {
+ for (size_t bin_y = 0; bin_y < spatial_bins_y_; bin_y++) {
+ for (size_t bin_x = 0; bin_x < spatial_bins_x_; bin_x++) {
+ float box_xmin = roi_start_w + (bin_x + 0) * (roi_width / spatial_bins_x_);
+ float box_xmax = roi_start_w + (bin_x + 1) * (roi_width / spatial_bins_x_);
+ float box_ymin = roi_start_h + (bin_y + 0) * (roi_height / spatial_bins_y_);
+ float box_ymax = roi_start_h + (bin_y + 1) * (roi_height / spatial_bins_y_);
+
+ size_t gc = c + (bin_y*spatial_bins_x_ + bin_x)*nc;
+ size_t src_idx = (roi_batch_ind * channels + gc) * height * width;
+ const float *bottom_data = bottom_data_beginning + src_idx;
+
+ float height_scale = nh > 1 ? (box_ymax - box_ymin) * (height - 1) / (pooled_height_ - 1)
+ : 0.0f;
+ float width_scale = nw > 1 ? (box_xmax - box_xmin) * (width - 1) / (pooled_width_ - 1)
+ : 0.0f;
+
+ float in_y = nh > 1 ? (h * height_scale + box_ymin * (height - 1))
+ : 0.5f * (box_ymin + box_ymax) * (height - 1);
+ float in_x = nw > 1 ? (w * width_scale + box_xmin * (width - 1))
+ : 0.5f * (box_xmin + box_xmax) * (width - 1);
+
+ if (!(in_y < 0 || in_y > height - 1 || in_x < 0 || in_x > width - 1)) {
+ int top_y_index = static_cast<int>(floorf(in_y));
+ int bottom_y_index = static_cast<int>(ceilf(in_y));
+ int left_x_index = static_cast<int>(floorf(in_x));
+ int right_x_index = static_cast<int>(ceilf(in_x));
+
+ if (right_x_index > width - 1)
+ right_x_index = width - 1;
+
+ if (bottom_y_index > height - 1)
+ bottom_y_index = height - 1;
+
+ const float top_left = bottom_data[top_y_index * width + left_x_index];
+ const float top_right = bottom_data[top_y_index * width + right_x_index];
+ const float bottom_left = bottom_data[bottom_y_index * width + left_x_index];
+ const float bottom_right = bottom_data[bottom_y_index * width + right_x_index];
+
+ const float top = top_left + (top_right - top_left) * (in_x - left_x_index);
+ const float bottom = bottom_left + (bottom_right - bottom_left) * (in_x - left_x_index);
+
+ dst_data[index] += top + (bottom - top) * (in_y - top_y_index);
+ }
+ }
+ }
+ dst_data[index] /= num_bins;
}
}
}
float spatial_scale_ = 0;
size_t pooled_height_ = 0;
size_t pooled_width_ = 0;
+ size_t spatial_bins_x_ = 0;
+ size_t spatial_bins_y_ = 0;
+ std::string mode_ = "";
int channels = 0;
int height = 0;
projects / platform / upstream / dldt.git / blobdiff