COMPMID-1676: Change CLROIAlign interface to accept ROIs as tensors

Change-Id: I69e995973597ba3927d29e4f6ed5438560e53d77

1 files changed, 20 insertions, 15 deletions

diff --git a/tests/validation/reference/ROIAlignLayer.cpp b/tests/validation/reference/ROIAlignLayer.cpp
index 68a465d18f..8a76983d44 100644
--- a/tests/validation/reference/ROIAlignLayer.cpp
+++ b/tests/validation/reference/ROIAlignLayer.cpp
@@ -114,30 +114,35 @@ T clamp(T value, T lower, T upper)
 }
 } // namespace
 template <typename T>
-SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info)
+SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &rois, const ROIPoolingLayerInfo &pool_info)
 {
-    const size_t num_rois      = rois.size();
-    DataType     dst_data_type = src.data_type();
+    const size_t values_per_roi = rois.shape()[0];
+    const size_t num_rois       = rois.shape()[1];
+    DataType     dst_data_type  = src.data_type();
+
+    const auto *rois_ptr = static_cast<const T *>(rois.data());
 
     TensorShape     input_shape = src.shape();
     TensorShape     output_shape(pool_info.pooled_width(), pool_info.pooled_height(), src.shape()[2], num_rois);
     SimpleTensor<T> dst(output_shape, dst_data_type);
 
     // Iterate over every pixel of the input image
-    for(size_t px = 0; px < pool_info.pooled_width(); px++)
+    for(size_t px = 0; px < pool_info.pooled_width(); ++px)
     {
-        for(size_t py = 0; py < pool_info.pooled_height(); py++)
+        for(size_t py = 0; py < pool_info.pooled_height(); ++py)
         {
-            for(size_t pw = 0; pw < num_rois; pw++)
+            for(size_t pw = 0; pw < num_rois; ++pw)
             {
-                ROI       roi       = rois[pw];
-                const int roi_batch = roi.batch_idx;
+                const unsigned int roi_batch = rois_ptr[values_per_roi * pw];
+                const auto         x1        = float(rois_ptr[values_per_roi * pw + 1]);
+                const auto         y1        = float(rois_ptr[values_per_roi * pw + 2]);
+                const auto         x2        = float(rois_ptr[values_per_roi * pw + 3]);
+                const auto         y2        = float(rois_ptr[values_per_roi * pw + 4]);
 
-                const float roi_anchor_x = roi.rect.x * pool_info.spatial_scale();
-                const float roi_anchor_y = roi.rect.y * pool_info.spatial_scale();
-                const float roi_dims_x   = std::max(roi.rect.width * pool_info.spatial_scale(), 1.0f);
-                const float roi_dims_y   = std::max(roi.rect.height * pool_info.spatial_scale(), 1.0f);
-                ;
+                const float roi_anchor_x = x1 * pool_info.spatial_scale();
+                const float roi_anchor_y = y1 * pool_info.spatial_scale();
+                const float roi_dims_x   = std::max((x2 - x1) * pool_info.spatial_scale(), 1.0f);
+                const float roi_dims_y   = std::max((y2 - y1) * pool_info.spatial_scale(), 1.0f);
 
                 float bin_size_x     = roi_dims_x / pool_info.pooled_width();
                 float bin_size_y     = roi_dims_y / pool_info.pooled_height();
@@ -178,8 +183,8 @@ SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const std::vector<RO
     }
     return dst;
 }
-template SimpleTensor<float> roi_align_layer(const SimpleTensor<float> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
-template SimpleTensor<half> roi_align_layer(const SimpleTensor<half> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
+template SimpleTensor<float> roi_align_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &rois, const ROIPoolingLayerInfo &pool_info);
+template SimpleTensor<half> roi_align_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &rois, const ROIPoolingLayerInfo &pool_info);
 } // namespace reference
 } // namespace validation
 } // namespace test