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24 #ifndef ACL_ARM_COMPUTE_CORE_TYPES_H
25 #define ACL_ARM_COMPUTE_CORE_TYPES_H
193 int end(
unsigned int d)
const
252 constexpr
BorderSize(
unsigned int top_bottom,
unsigned int left_right)
324 return !(*
this == rhs);
515 int detections = 100,
526 _detections_per_im(detections),
540 return _score_thresh;
550 return _detections_per_im;
555 return _soft_nms_enabled;
560 return _soft_nms_method;
565 return _soft_nms_sigma;
570 return _soft_nms_min_score_thres;
575 return _suppress_size;
596 int _detections_per_im;
597 bool _soft_nms_enabled;
599 float _soft_nms_sigma;
600 float _soft_nms_min_score_thres;
680 const std::vector<float> &
max_sizes = {},
683 const std::array<float, 2> &
steps = {{0.f, 0.f}})
694 _aspect_ratios.push_back(1.);
698 bool already_exist =
false;
699 for (
auto ar_new : _aspect_ratios)
701 if (fabs(ar - ar_new) < 1e-6)
703 already_exist =
true;
709 _aspect_ratios.push_back(ar);
712 _aspect_ratios.push_back(1.f / ar);
760 return _aspect_ratios;
764 std::vector<float> _min_sizes;
765 std::vector<float> _variances;
769 std::vector<float> _max_sizes;
770 std::vector<float> _aspect_ratios;
772 std::array<float, 2> _steps;
776 using BBox = std::array<float, 4>;
801 _background_label_id(),
802 _confidence_threshold(),
803 _variance_encoded_in_target(false),
807 _num_loc_classes = _share_location ? 1 : _num_classes;
844 _num_loc_classes = _share_location ? 1 : _num_classes;
854 return _share_location;
864 return _variance_encoded_in_target;
874 return _nms_threshold;
884 return _background_label_id;
889 return _confidence_threshold;
899 return _num_loc_classes;
904 bool _share_location;
907 float _nms_threshold;
909 int _background_label_id;
910 float _confidence_threshold;
911 bool _variance_encoded_in_target;
913 int _num_loc_classes;
923 _max_classes_per_detection(),
924 _nms_score_threshold(),
929 _detection_per_class(),
950 std::array<float, 4> scales_values,
959 _scales_values(scales_values),
968 return _max_detections;
973 return _max_classes_per_detection;
978 return _detection_per_class;
983 return _nms_score_threshold;
988 return _iou_threshold;
998 return _use_regular_nms;
1004 return _scales_values[0];
1010 return _scales_values[1];
1016 return _scales_values[2];
1022 return _scales_values[3];
1027 return _dequantize_scores;
1031 unsigned int _max_detections;
1032 unsigned int _max_classes_per_detection;
1033 float _nms_score_threshold;
1034 float _iou_threshold;
1035 unsigned int _num_classes;
1036 std::array<float, 4> _scales_values;
1037 bool _use_regular_nms;
1038 unsigned int _detection_per_class;
1039 bool _dequantize_scores;
1282 return _pooled_width;
1287 return _pooled_height;
1292 return _spatial_scale;
1297 return _sampling_ratio;
1301 unsigned int _pooled_width;
1302 unsigned int _pooled_height;
1303 float _spatial_scale;
1304 unsigned int _sampling_ratio;
1362 return _pre_nms_topN;
1367 return _post_nms_topN;
1382 return _spatial_scale;
1387 return _values_per_roi;
1394 float _spatial_scale;
1399 size_t _values_per_roi;
1424 return _feat_height;
1436 return _spatial_scale;
1442 return _values_per_roi;
1448 float _spatial_scale;
1449 size_t _values_per_roi;
1470 const std::array<float, 4>
weights = {{1.f, 1.f, 1.f, 1.f}},
1490 return _bbox_xform_clip;
1510 return _apply_scale;
1515 return _correct_transform_coords;
1523 bool _correct_transform_coords;
1524 std::array<float, 4> _weights;
1525 float _bbox_xform_clip;
1544 float alpha = 0.0001f,
1600 const uint32_t size = (_type ==
NormType::IN_MAP_2D) ? _norm_size * _norm_size : _norm_size;
1601 return (_is_scaled) ? (_alpha / size) : _alpha;
1606 uint32_t _norm_size;
1642 return _shrink_axis_mask;
1646 int32_t _begin_mask;
1648 int32_t _shrink_axis_mask;
1654 return (
static_cast<int>(wf) >> 8) & 0xFFF;
1658 return (
static_cast<int>(wf) >> 20) & 0xF;
1666 return (
static_cast<int>(wf) >> 4) & 0x1;
1675 : _are_reshaped(false),
1679 _retain_internal_weights(false),
1712 return _are_reshaped;
1720 return _num_kernels;
1728 return std::make_pair(_kernel_width, _kernel_height);
1732 return _retain_internal_weights;
1736 return _weight_format;
1745 return _kernel_width;
1749 return _kernel_height;
1754 unsigned int _kernel_width;
1755 unsigned int _kernel_height;
1756 unsigned int _num_kernels;
1757 bool _retain_internal_weights;
1778 _mult_transpose1xW_width(1),
1779 _mult_interleave4x4_height(1),
1780 _depth_output_gemm3d(0),
1781 _reinterpret_input_as_3d(false),
1782 _broadcast_bias(false)
1846 return _mult_transpose1xW_width;
1854 return _mult_interleave4x4_height;
1865 return _depth_output_gemm3d;
1873 return _reinterpret_input_as_3d;
1881 return _broadcast_bias;
1888 int _mult_transpose1xW_width;
1889 int _mult_interleave4x4_height;
1890 int _depth_output_gemm3d;
1891 bool _reinterpret_input_as_3d;
1892 bool _broadcast_bias;
1914 GEMMRHSMatrixInfo(
unsigned int n,
unsigned int k,
unsigned int h,
bool trans,
bool inter,
bool export_to_cl_img)
2019 #endif // ACL_ARM_COMPUTE_CORE_TYPES_H
constexpr BorderSize(unsigned int size) noexcept
Border with equal size around the 2D plane.
constexpr BorderSize(unsigned int top, unsigned int right, unsigned int bottom, unsigned int left)
Border with different sizes.
std::vector< float > max_sizes() const
Get max sizes.
unsigned int right
right of the border
ValidRegion(const Coordinates &an_anchor, const TensorShape &a_shape, size_t num_dimensions)
Constructor for a valid region with specified number of dimensions.
@ LessEqual
Less equal comparison ( )
@ CONSTANT
Pixels outside the image are assumed to have a constant value.
uint16_t x
Top-left x coordinate.
std::vector< float > min_sizes() const
Get min sizes.
bool variance_encoded_in_target() const
Get if variance encoded in target.
float feat_height() const
Pooling3dLayerInfo(PoolingType pool_type, unsigned int pool_size, Size3D stride=Size3D(1U, 1U, 1U), Padding3D padding=Padding3D(), bool exclude_padding=false, bool fp_mixed_precision=false, DimensionRoundingType round_type=DimensionRoundingType::FLOOR)
Constructor.
Convolution Layer Weights Information class.
@ FFT
Convolution using FFT.
DataLayout output_data_layout
Data layout to use for the output tensor once the convolution has been applied (NCHW or NHWC)
bool share_location() const
Get share location.
float kappa() const
Get the kappa value.
int num_classes() const
Get num classes.
bool clip() const
Get the clip value.
PoolingLayerInfo(PoolingType pool_type, unsigned int pool_size, DataLayout data_layout, PadStrideInfo pad_stride_info=PadStrideInfo(), bool exclude_padding=false, bool fp_mixed_precision=false, bool use_inf_as_limit=true, bool use_kernel_indices=false)
Constructor.
float score_thresh() const
Get the score threshold.
unsigned int pooled_width() const
Get the pooled width of the layer.
std::vector< PaddingInfo > PaddingList
List of padding information.
int keep_top_k() const
Get the number of total bounding boxes to be kept per image.
std::vector< float > aspect_ratios() const
Get aspect ratios.
void set(size_t dimension, T value, bool increase_dim_unit=true)
Accessor to set the value of one of the dimensions.
unsigned int n0
Number of columns processed by the matrix multiplication.
GEMMRHSMatrixInfo()=default
DataLayout
[DataLayout enum definition]
PoolingLayerInfo()
Default Constructor.
bool dequantize_scores() const
Get dequantize_scores value.
WinogradInfo(Size2D output_tile_sz, Size2D kernel_sz, Size2D input_dims, PadStrideInfo conv_info, DataLayout data_layout)
Default constructor.
@ Equal
Equal comparison ( )
BilinearInterpolation
Bilinear Interpolation method used by LKTracker.
size_t bottom
Padding across the height dimension on the bottom, in elements.
Container for 2D border size.
@ IN_MAP_1D
Normalization applied within the same map in 1D region.
ROIPoolingLayerInfo(unsigned int pooled_width, unsigned int pooled_height, float spatial_scale, unsigned int sampling_ratio=0)
Constructor.
float alpha() const
Get the alpha value.
GEMM reshape information class.
@ UNDEFINED
Borders are left undefined.
bool operator==(const BorderSize &rhs) const
Check equality with another BorderSize struct.
int32_t shrink_axis_mask() const
int k() const
Number of matrix A columns or matrix B rows.
float nms_score_threshold() const
Get nms threshold.
@ TOP_LEFT
Samples are taken at pixel top left corner.
int n() const
Number of matrix B columns.
@ AREA
Output values are determined by averaging the source pixels whose areas fall under the area of the de...
SamplingPolicy
Available Sampling Policies.
DetectionOutputLayerCodeType
Available Detection Output code types.
unsigned int max_detections() const
Get max detections.
NormalizationLayerInfo(NormType type, uint32_t norm_size=5, float alpha=0.0001f, float beta=0.5f, float kappa=1.f, bool is_scaled=true)
Default Constructor.
@ Greater
Greater comparison ( )
Coordinates2D img_size() const
Get the image size coordinates.
float iou_threshold() const
Get intersection over union threshold.
@ CORNER_SIZE
Use box centers and size.
Padding information for 3D operations like Conv3d.
@ PRELU
y*x if x < 0, x otherwise
size_t values_per_roi() const
Size2D output_tile_size
Width and height of the output tile.
@ INDIRECT
Indirect convolution.
int post_nms_topN() const
float spatial_scale() const
DeconvolutionMethod
Available DeconvolutionMethod.
bool interleave
True if the v0 (m0xk0) blocks have to be interleaved in the output row.
bool export_to_cl_image
True if the reshaped rhs has to be exported to cl_image.
PoolingLayerInfo(PoolingType pool_type, DataLayout data_layout)
Constructor.
PriorBoxLayerInfo()
Default Constructor.
int interleave_by(const WeightFormat wf)
Size2D input_dimensions
Width and height of the input tensor before the convolution is applied.
float score
Confidence value for the detection window.
Class for specifying the size of an image or rectangle.
InterpolationPolicy
Interpolation method.
unsigned int top
top of the border
unsigned int kernel_height() const
PriorBoxLayerInfo(const std::vector< float > &min_sizes, const std::vector< float > &variances, float offset, bool flip=true, bool clip=false, const std::vector< float > &max_sizes={}, const std::vector< float > &aspect_ratios={}, const Coordinates2D &img_size=Coordinates2D{0, 0}, const std::array< float, 2 > &steps={{0.f, 0.f}})
Constructor.
DepthwiseConvolutionFunction
Available DepthwiseConvolutionFunction.
float scale_value_x() const
Get x scale value.
unsigned int num_kernels() const
Return the number of convolution kernels.
unsigned int kernel_width() const
float scale_coeff() const
Return the scaling factor of the normalization function.
float im_height() const
Get image height (NMS may suppress boxes whose center sits beyond the image height)
BoxWithNonMaximaSuppressionLimit Information class.
DimensionRoundingType
Dimension rounding type when down-scaling on CNNs.
GEMMLHSMatrixInfo(unsigned int m, unsigned int k, unsigned int v, bool trans, bool inter)
bool are_reshaped() const
Flag which specifies if the weights tensor has been reshaped.
Detection window used for the object detection.
constexpr bool empty() const
Check if the entire border is zero.
size_t top
Padding across the height dimension on the top, in elements.
unsigned int v0
Number of vertical blocks of size (m0xk0) stored on the same output row.
unsigned int pooled_height() const
Get the pooled height of the layer.
float scale_value_y() const
Get y scale value.
Padding3D(size_t pad_x, size_t pad_y, size_t pad_z)
BoxNMSLimitInfo(float score_thresh=0.05f, float nms=0.3f, int detections=100, bool soft_nms_enabled=false, NMSType soft_nms_method=NMSType::LINEAR, float soft_nms_sigma=0.5f, float soft_nms_min_score_thres=0.001f, bool suppress_size=false, float min_size=1.0f, float im_width=1.0f, float im_height=1.0f)
Constructor.
ReductionOperation
Available reduction operations.
StridedSliceLayerInfo(int32_t begin_mask=0, int32_t end_mask=0, int32_t shrink_axis_mask=0)
Default Constructor.
@ BILINEAR_OLD_NEW
Old-new method.
@ RSQRT
Reverse square root.
ComputeAnchors information class.
PaddingMode
Padding mode to use for PadLayer.
bool reinterpret_input_as_3d() const
Flag which specifies if the input tensor has to be reinterpreted as 3D.
constexpr auto data_layout
std::array< float, 2 > steps() const
Get the step coordinates.
FuseBatchNormalizationType
Available FuseBatchNormalizationType.
int m() const
Number of matrix A rows.
ValidRegion(const Coordinates &an_anchor, const TensorShape &a_shape)
Constructor for a valid region with default number of dimensions.
ConvolutionMethod
Available ConvolutionMethod.
bool flip() const
Get the flip value.
Padding2D(size_t left, size_t right, size_t top, size_t bottom)
constexpr BorderSize() noexcept
Empty border, i.e.
bool operator!=(const BorderSize &rhs) const
Check non-equality with another BorderSize struct.
bool operator==(const Dimensions< T > &lhs, const Dimensions< T > &rhs)
Check that given dimensions are equal.
std::array< float, 4 > BBox
size_t right
Padding across the width dimension on the right, in elements.
DetectionOutputLayerInfo(int num_classes, bool share_location, DetectionOutputLayerCodeType code_type, int keep_top_k, float nms_threshold, int top_k=-1, int background_label_id=-1, float confidence_threshold=std::numeric_limits< float >::lowest(), bool variance_encoded_in_target=false, float eta=1)
Constructor.
constexpr bool uniform() const
Check if the border is the same size on all sides.
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
unsigned int bottom
bottom of the border
int block_by(const WeightFormat wf)
bool retain_internal_weights() const
@ Less
Less comparison ( )
void limit(const BorderSize &limit)
Limit this border size.
WeightFormat
Memory layouts for the weights tensor.
bool soft_nms_enabled() const
Check if soft NMS is enabled.
unsigned int max_classes_per_detection() const
Get max_classes per detection.
float confidence_threshold() const
Get confidence threshold.
size_t left
Padding across the width dimension on the left, in elements.
size_t top
Padding across the height dimenstion on the top, in elements.
ComparisonOperation
Supported comparison operations.
bool is_scaled() const
Get the is_scaled value.
float scale_value_w() const
Get w scale value.
std::pair< unsigned int, unsigned int > kernel_size() const
Return the width and height of the kernel.
@ SUM_SQUARE
Sum of squares.
@ TF_CENTER
Use box centers and size but flip x and y co-ordinates.
unsigned int k0
Number of partial accumulations performed by the matrix multiplication.
uint16_t width
Width of the detection window.
uint16_t height
Height of the rectangle.
unsigned int m0
Number of rows processed by the matrix multiplication.
arm_compute::WeightFormat weight_format() const
@ AND
Bitwise AND operation.
BitwiseOperation
Available bitwise operations.
DetectionPostProcessLayerInfo(unsigned int max_detections, unsigned int max_classes_per_detection, float nms_score_threshold, float iou_threshold, unsigned int num_classes, std::array< float, 4 > scales_values, bool use_regular_nms=false, unsigned int detection_per_class=100, bool dequantize_scores=true)
Constructor.
uint16_t x
Top-left x coordinate.
Container for valid region of a window.
Pooling Layer Information struct.
@ CONVOLUTION
For Convolution weights.
bool suppress_size() const
Get if NMS will suppress boxes based on their size/position.
uint32_t norm_size() const
Get the normalization size.
@ REPLICATE
Pixels outside the image are assumed to have the same value as the closest image pixel.
constexpr BorderSize(unsigned int top_bottom, unsigned int left_right)
Border with same size for top/bottom and left/right.
DetectionPostProcessLayerInfo()
Default Constructor.
@ NotEqual
NotEqual comparison ( )
Detection Output layer info.
int background_label_id() const
Get background label ID.
@ WINOGRAD
Convolution using Winograd.
NMSType
Available non maxima suppression types.
PoolingType
Available pooling types.
BorderSize & operator*=(float scale)
Scale this border size.
@ OPTIMIZED
Optimized Depthwise Convolution.
int start(unsigned int d) const
Return the start of the valid region for the given dimension d.
int top_k() const
Get top K.
@ GEMM_CONV2D
Direct 2D GEMM convolution.
uint16_t idx_class
Index of the class.
void set_weight_format(arm_compute::WeightFormat weight_format)
NMSType soft_nms_method() const
Get soft NMS method.
@ DEPTHWISECONVOLUTION
For Depthwise Convolution weights.
size_t back
Padding across the depth dimenstion on the back, in elements.
@ XOR
Bitwise XOR operation
size_t front
Padding across the depth dimenstion on the front, in elements.
@ GEMM
Convolution using GEMM.
size_t values_per_roi() const
bool is_fixed_format(const WeightFormat &wf)
@ GEMM
Deconvolution using GEMM.
@ ARG_IDX_MAX
Index of the max value.
@ IN_MAP_2D
Normalization applied within the same map in 2D region.
bool broadcast_bias() const
Flag which specifies whether to broadcast the shape of the bias tensor.
bool is_cross_map() const
Check if normalization is cross map.
DimensionRoundingType round_type
friend bool operator==(const ValidRegion &lhs, const ValidRegion &rhs)
Check whether two valid regions are equal.
GEMMReshapeInfo(int m, int n, int k, int mult_transpose1xW_width=1, int mult_interleave4x4_height=1, int depth_output_gemm3d=0, bool reinterpret_input_as_3d=false, bool broadcast_bias=false)
Constructor.
Pooling3dLayerInfo() noexcept
Default Constructor.
float eta() const
Get eta.
Detection Output layer info.
@ DIRECT
Direct convolution.
@ BILINEAR
Output values are defined by bilinear interpolation between the pixels.
Class for specifying the size of a 3D shape or object.
float im_width() const
Get image width (NMS may suppress boxes whose center sits beyond the image width)
GEMMLHSMatrixInfo()=default
Pooling Layer Information struct.
bool interleave
True if the h0 (k0xn0) blocks have to be interleaved in the output row.
GEMMReshapeInfo()
Default constructor.
uint16_t height
Height of the detection window.
float nms_threshold() const
Get nms threshold.
float offset() const
Get the offset.
bool is_fixed_format_fast_math(const WeightFormat &wf)
size_t left
Padding across the width dimenstion on the left, in elements.
GEMM LHS (Left Hand Side) matrix information.
@ ARG_IDX_MIN
Index of the min value.
BorderSize operator*(float scale)
Scale a copy of this border size.
float scale_value_h() const
Get h scale value.
bool use_regular_nms() const
Get if use regular nms.
Normalization Layer Information class.
int mult_transpose1xW_width() const
Multiplication factor for the width of the 1xW transposed block.
TensorShape shape
Shape of the valid region.
bool transpose
True if the (k0xn0) block has to be transposed before been stored.
WeightsInfo(bool are_reshaped, unsigned int kernel_width, unsigned int kernel_height, unsigned int num_kernels, bool retain_internal_weights=false, arm_compute::WeightFormat weight_format=arm_compute::WeightFormat::UNSPECIFIED)
Constructor.
@ DIRECT
Direct deconvolution.
int num_loc_classes() const
Get number of location classes.
ComputeAnchorsInfo(float feat_width, float feat_height, float spatial_scale, size_t values_per_roi=4)
Constructor.
float soft_nms_min_score_thres() const
Get soft nms min score threshold.
DetectionOutputLayerCodeType code_type() const
Get detection output code type.
float soft_nms_sigma() const
Get soft NMS sigma.
int depth_output_gemm3d() const
Depth (third dimension) of the output tensor to be used with the GEMM3D kernel.
float nms() const
Get the NMS.
Copyright (c) 2017-2024 Arm Limited.
@ BILINEAR_SCHARR
Scharr method.
ConvertPolicy
Policy to handle integer overflow.
@ UNKNOWN
Unknown CL kernel type.
int32_t begin_mask() const
unsigned int left
left of the border
void set_num_dimensions(size_t num_dimensions)
Set number of dimensions.
std::vector< uint32_t > Multiples
Information to produce a tiled version of a Tensor.
Size2D kernel_size
Width and height of the kernel.
@ CROSS_MAP
Normalization applied cross maps.
std::pair< uint32_t, uint32_t > PaddingInfo
Padding information as a pair of unsigned int start/end.
bool transpose
True if the (m0xk0) block has to be transposed before been stored.
float spatial_scale() const
Get the spatial scale.
@ GreaterEqual
Greater equal comparison ( )
unsigned int num_classes() const
Get num classes.
int end(unsigned int d) const
Return the end of the valid region for the given dimension d.
uint16_t y
Top-left y coordinate.
size_t right
Padding across the width dimenstion on the right, in elements.
std::vector< float > variances() const
Get min variances.
@ GENERIC
Generic Depthwise Convolution.
@ NEAREST_NEIGHBOR
Output values are defined to match the source pixel whose center is nearest to the sample position.
@ NOT
Bitwise NOT operation.
@ CENTER
Samples are taken at pixel center.
BorderMode
Methods available to handle borders.
PoolingLayerInfo(PoolingType pool_type, Size2D pool_size, DataLayout data_layout, PadStrideInfo pad_stride_info=PadStrideInfo(), bool exclude_padding=false, bool fp_mixed_precision=false, bool use_inf_as_limit=true, bool use_kernel_indices=false)
Constructor.
@ UPSCALE_CONV2D
Deconvolution with Upscaling.
ValidRegion & set(size_t dimension, int start, size_t size)
Accessor to set the value of anchor and shape for one of the dimensions.
size_t bottom
Padding across the height dimenstion on the bottom, in elements.
@ CENTER_SIZE
Use box centers and size.
float beta() const
Get the beta value.
NormType
The normalization type used for the normalization layer.
int mult_interleave4x4_height() const
Multiplication factor for the height of the 4x4 interleaved block.
unsigned int k0
Number of partial accumulations performed by the matrix multiplication.
Padding and stride information class.
Pooling3dLayerInfo(PoolingType pool_type, Size3D pool_size, Size3D stride=Size3D(1U, 1U, 1U), Padding3D padding=Padding3D(), bool exclude_padding=false, bool fp_mixed_precision=false, DimensionRoundingType round_type=DimensionRoundingType::FLOOR)
Constructor.
PadStrideInfo convolution_info
Convolution info (Pads, strides,...)
TensorShape & set(size_t dimension, size_t value, bool apply_dim_correction=true, bool increase_dim_unit=true)
Accessor to set the value of one of the dimensions.
GEMMRHSMatrixInfo(unsigned int n, unsigned int k, unsigned int h, bool trans, bool inter, bool export_to_cl_img)
GEMM RHS (Right Hand Side) matrix information.
DetectionOutputLayerInfo()
Default Constructor.
unsigned int detection_per_class() const
Get detection per class.
int detections_per_im() const
Get the number of detections.
PadStrideInfo pad_stride_info
Pooling3dLayerInfo(PoolingType pool_type)
Constructor.
unsigned int num_dimensions() const
Returns the effective dimensionality of the tensor.
uint16_t width
Width of the rectangle.
unsigned int h0
Number of horizontal blocks of size (k0xn0) stored on the same output row.
ValidRegion()
Default constructor.
bool is_in_map() const
Check if normalization is not cross map.
ROI Pooling Layer Information class.
uint16_t y
Top-left y coordinate.
@ LOGICAL_NOT
Logical Not.
ValidRegion & operator=(const ValidRegion &)=default
Allow instances of this class to be copied.
WeightsInfo()
Default constructor.
Generate Proposals Information class.
float spatial_scale() const
ElementWiseUnary
Available element wise unary operations.
Padding3D(size_t left, size_t right, size_t top, size_t bottom, size_t front, size_t back)
float min_size() const
Get size suppression threshold.
NormType type() const
Get the normalization type.
Coordinates anchor
Anchor for the start of the valid region.
std::map< int, std::vector< BBox > > LabelBBox
unsigned int sampling_ratio() const
Get sampling ratio.
~ValidRegion()=default
Default destructor.
GenerateProposalsInfo(float im_width, float im_height, float im_scale, float spatial_scale=1.0, int pre_nms_topN=6000, int post_nms_topN=300, float nms_thres=0.7, float min_size=16.0, size_t values_per_roi=4)
Constructor.
ArithmeticOperation
Available element-wise operations.