diff options
Diffstat (limited to 'src/core/TensorInfo.cpp')
| -rw-r--r-- | src/core/TensorInfo.cpp | 12 |
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() |