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authorJohn Richardson <john.richardson@arm.com>2018-01-09 11:17:00 +0000
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:49:16 +0000
commit684cb0f29d23fbe418e5e5347234abf9eccef363 (patch)
tree60731b6bb63b1a0dc997107d3bd55d8b4b82626b /src/core/TensorInfo.cpp
parent7da29b6b12ff319ed2b6e2c46588dfa1991556fb (diff)
downloadComputeLibrary-684cb0f29d23fbe418e5e5347234abf9eccef363.tar.gz
COMPMID-596: Port HOGDetector to new validation
Change-Id: I73231fc71c5166268e6c909b7930b7e034f3794e Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118876 Reviewed-by: Anthony Barbier <anthony.barbier@arm.com> Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/TensorInfo.cpp')
-rw-r--r--src/core/TensorInfo.cpp12
1 files changed, 6 insertions, 6 deletions
diff --git a/src/core/TensorInfo.cpp b/src/core/TensorInfo.cpp
index 2190e3415c..539d0f84b3 100644
--- a/src/core/TensorInfo.cpp
+++ b/src/core/TensorInfo.cpp
@@ -168,13 +168,13 @@ void TensorInfo::init(const HOGInfo &hog_info, unsigned int width, unsigned int
// Number of cells for each block
const Size2D num_cells_per_block = hog_info.num_cells_per_block();
- // Tensor Size = (Number of horizontal blocks) * (Number of vertical blocks )
- const Size2D num_blocks_per_img = hog_info.num_blocks_per_image(Size2D(width, height));
+ // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
+ const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
// Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
- init(TensorShape(num_blocks_per_img.width, num_blocks_per_img.height), num_channels, DataType::F32);
+ init(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
}
size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, Format format)
@@ -212,13 +212,13 @@ size_t TensorInfo::init_auto_padding(const HOGInfo &hog_info, unsigned int width
// Number of cells for each block
const Size2D num_cells_per_block = hog_info.num_cells_per_block();
- // Tensor Size = (Number of horizontal blocks) * (Number of vertical blocks )
- const Size2D num_blocks_per_img = hog_info.num_blocks_per_image(Size2D(width, height));
+ // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
+ const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
// Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
- return init_auto_padding(TensorShape(num_blocks_per_img.width, num_blocks_per_img.height), num_channels, DataType::F32);
+ return init_auto_padding(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
}
bool TensorInfo::auto_padding()