vendor: OpenCV 5.0.0 snapshot at 40738fb16ceddb5fb3fea747585f7ce6abb0605b

This commit is contained in:
Gitea Mirror Bot
2026-08-22 00:10:33 +08:00
commit f7f077da11
6933 changed files with 2335208 additions and 0 deletions
+32
View File
@@ -0,0 +1,32 @@
if(HAVE_FASTCV)
set(FASTCV_HAL_VERSION 0.0.1 CACHE INTERNAL "")
set(FASTCV_HAL_LIBRARIES "fastcv_hal" CACHE INTERNAL "")
set(FASTCV_HAL_INCLUDE_DIRS "${CMAKE_CURRENT_SOURCE_DIR}/include" CACHE INTERNAL "")
set(FASTCV_HAL_HEADERS
"${CMAKE_CURRENT_SOURCE_DIR}/include/fastcv_hal_core.hpp"
"${CMAKE_CURRENT_SOURCE_DIR}/include/fastcv_hal_imgproc.hpp"
CACHE INTERNAL "")
file(GLOB FASTCV_HAL_FILES "${CMAKE_CURRENT_SOURCE_DIR}/src/*.cpp")
add_library(fastcv_hal STATIC ${OPENCV_3RDPARTY_EXCLUDE_FROM_ALL} ${FASTCV_HAL_FILES})
target_include_directories(fastcv_hal PRIVATE
${CMAKE_SOURCE_DIR}/modules/core/include
${CMAKE_SOURCE_DIR}/modules/imgproc/include
${FASTCV_HAL_INCLUDE_DIRS} ${FastCV_INCLUDE_PATH})
target_link_libraries(fastcv_hal PUBLIC ${FASTCV_LIBRARY})
set_target_properties(fastcv_hal PROPERTIES ARCHIVE_OUTPUT_DIRECTORY ${3P_LIBRARY_OUTPUT_PATH})
if(NOT BUILD_SHARED_LIBS)
ocv_install_target(fastcv_hal EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
endif()
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(fastcv_hal PROPERTIES FOLDER "3rdparty")
endif()
else()
message(STATUS "FastCV is not available, disabling related HAL")
endif(HAVE_FASTCV)
+270
View File
@@ -0,0 +1,270 @@
/*
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#ifndef OPENCV_FASTCV_HAL_CORE_HPP_INCLUDED
#define OPENCV_FASTCV_HAL_CORE_HPP_INCLUDED
#include <opencv2/core/base.hpp>
#undef cv_hal_lut
#define cv_hal_lut fastcv_hal_lut
#undef cv_hal_normHammingDiff8u
#define cv_hal_normHammingDiff8u fastcv_hal_normHammingDiff8u
#undef cv_hal_mul8u16u
#define cv_hal_mul8u16u fastcv_hal_mul8u16u
#undef cv_hal_sub8u32f
#define cv_hal_sub8u32f fastcv_hal_sub8u32f
#undef cv_hal_transpose2d
#define cv_hal_transpose2d fastcv_hal_transpose2d
#undef cv_hal_meanStdDev
#define cv_hal_meanStdDev fastcv_hal_meanStdDev
#undef cv_hal_flip
#define cv_hal_flip fastcv_hal_flip
#undef cv_hal_rotate90
#define cv_hal_rotate90 fastcv_hal_rotate
#undef cv_hal_addWeighted8u
#define cv_hal_addWeighted8u fastcv_hal_addWeighted8u
#undef cv_hal_mul8u
#define cv_hal_mul8u fastcv_hal_mul8u
#undef cv_hal_mul16s
#define cv_hal_mul16s fastcv_hal_mul16s
#undef cv_hal_mul32f
#define cv_hal_mul32f fastcv_hal_mul32f
#undef cv_hal_SVD32f
#define cv_hal_SVD32f fastcv_hal_SVD32f
#undef cv_hal_gemm32f
#define cv_hal_gemm32f fastcv_hal_gemm32f
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief look-up table transform of an array.
/// @param src_data Source image data
/// @param src_step Source image step
/// @param src_type Source image type
/// @param lut_data Pointer to lookup table
/// @param lut_channel_size Size of each channel in bytes
/// @param lut_channels Number of channels in lookup table
/// @param dst_data Destination data
/// @param dst_step Destination step
/// @param width Width of images
/// @param height Height of images
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_lut(
const uchar* src_data,
size_t src_step,
size_t src_type,
const uchar* lut_data,
size_t lut_channel_size,
size_t lut_channels,
uchar* dst_data,
size_t dst_step,
int width,
int height);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Hamming distance between two vectors
/// @param a pointer to first vector data
/// @param b pointer to second vector data
/// @param n length of vectors
/// @param cellSize how many bits of the vectors will be added and treated as a single bit, can be 1 (standard Hamming distance), 2 or 4
/// @param result pointer to result output
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_normHammingDiff8u(const uchar* a, const uchar* b, int n, int cellSize, int* result);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_mul8u16u(
const uchar * src1_data,
size_t src1_step,
const uchar * src2_data,
size_t src2_step,
ushort * dst_data,
size_t dst_step,
int width,
int height,
double scale);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_sub8u32f(
const uchar *src1_data,
size_t src1_step,
const uchar *src2_data,
size_t src2_step,
float *dst_data,
size_t dst_step,
int width,
int height);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_transpose2d(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int src_width,
int src_height,
int element_size);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_meanStdDev(
const uchar * src_data,
size_t src_step,
int width,
int height,
int src_type,
double * mean_val,
double * stddev_val,
uchar * mask,
size_t mask_step);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Flips a 2D array around vertical, horizontal, or both axes
/// @param src_type source and destination image type
/// @param src_data source image data
/// @param src_step source image step
/// @param src_width source and destination image width
/// @param src_height source and destination image height
/// @param dst_data destination image data
/// @param dst_step destination image step
/// @param flip_mode 0 flips around x-axis, 1 around y-axis, -1 both
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_flip(
int src_type,
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int flip_mode);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Rotates a 2D array in multiples of 90 degrees.
/// @param src_type source and destination image type
/// @param src_data source image data
/// @param src_step source image step
/// @param src_width source image width
/// @If angle has value [180] it is also destination image width
/// If angle has values [90, 270] it is also destination image height
/// @param src_height source and destination image height (destination image width for angles [90, 270])
/// If angle has value [180] it is also destination image height
/// If angle has values [90, 270] it is also destination image width
/// @param dst_data destination image data
/// @param dst_step destination image step
/// @param angle clockwise angle for rotation in degrees from set [90, 180, 270]
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_rotate(
int src_type,
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int angle);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief weighted sum of two arrays using formula: dst[i] = a * src1[i] + b * src2[i]
/// @param src1_data first source image data
/// @param src1_step first source image step
/// @param src2_data second source image data
/// @param src2_step second source image step
/// @param dst_data destination image data
/// @param dst_step destination image step
/// @param width width of the images
/// @param height height of the images
/// @param scalars numbers a, b, and c
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_addWeighted8u(
const uchar* src1_data,
size_t src1_step,
const uchar* src2_data,
size_t src2_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
const double scalars[3]);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_mul8u(
const uchar *src1_data,
size_t src1_step,
const uchar *src2_data,
size_t src2_step,
uchar *dst_data,
size_t dst_step,
int width,
int height,
double scale);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_mul16s(
const short *src1_data,
size_t src1_step,
const short *src2_data,
size_t src2_step,
short *dst_data,
size_t dst_step,
int width,
int height,
double scale);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_mul32f(
const float *src1_data,
size_t src1_step,
const float *src2_data,
size_t src2_step,
float *dst_data,
size_t dst_step,
int width,
int height,
double scale);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// Performs singular value decomposition of \f$M\times N\f$(\f$M>N\f$) matrix \f$A = U*\Sigma*V^T\f$.
///
/// @param src Pointer to input MxN matrix A stored in column major order.
/// After finish of work src will be filled with rows of U or not modified (depends of flag CV_HAL_SVD_MODIFY_A).
/// @param src_step Number of bytes between two consequent columns of matrix A.
/// @param w Pointer to array for singular values of matrix A (i. e. first N diagonal elements of matrix \f$\Sigma\f$).
/// @param u Pointer to output MxN or MxM matrix U (size depends of flags).
/// Pointer must be valid if flag CV_HAL_SVD_MODIFY_A not used.
/// @param u_step Number of bytes between two consequent rows of matrix U.
/// @param vt Pointer to array for NxN matrix V^T.
/// @param vt_step Number of bytes between two consequent rows of matrix V^T.
/// @param m Number fo rows in matrix A.
/// @param n Number of columns in matrix A.
/// @param flags Algorithm options (combination of CV_HAL_SVD_FULL_UV, ...).
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_SVD32f(
float* src,
size_t src_step,
float* w,
float* u,
size_t u_step,
float* vt,
size_t vt_step,
int m,
int n,
int flags);
int fastcv_hal_gemm32f(
const float* src1,
size_t src1_step,
const float* src2,
size_t src2_step,
float alpha,
const float* src3,
size_t src3_step,
float beta,
float* dst,
size_t dst_step,
int m,
int n,
int k,
int flags);
#endif
+268
View File
@@ -0,0 +1,268 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#ifndef OPENCV_FASTCV_HAL_IMGPROC_HPP_INCLUDED
#define OPENCV_FASTCV_HAL_IMGPROC_HPP_INCLUDED
#include <opencv2/core/base.hpp>
#undef cv_hal_medianBlur
#define cv_hal_medianBlur fastcv_hal_medianBlur
#undef cv_hal_sobel
#define cv_hal_sobel fastcv_hal_sobel
#undef cv_hal_boxFilter
#define cv_hal_boxFilter fastcv_hal_boxFilter
#undef cv_hal_adaptiveThreshold
#define cv_hal_adaptiveThreshold fastcv_hal_adaptiveThreshold
#undef cv_hal_gaussianBlurBinomial
#define cv_hal_gaussianBlurBinomial fastcv_hal_gaussianBlurBinomial
#undef cv_hal_warpPerspective
#define cv_hal_warpPerspective fastcv_hal_warpPerspective
#undef cv_hal_pyrdown
#define cv_hal_pyrdown fastcv_hal_pyrdown
#undef cv_hal_cvtBGRtoHSV
#define cv_hal_cvtBGRtoHSV fastcv_hal_cvtBGRtoHSV
#undef cv_hal_cvtBGRtoYUVApprox
#define cv_hal_cvtBGRtoYUVApprox fastcv_hal_cvtBGRtoYUVApprox
#undef cv_hal_canny
#define cv_hal_canny fastcv_hal_canny
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Calculate medianBlur filter
/// @param src_data Source image data
/// @param src_step Source image step
/// @param dst_data Destination image data
/// @param dst_step Destination image step
/// @param width Source image width
/// @param height Source image height
/// @param depth Depths of source and destination image
/// @param cn Number of channels
/// @param ksize Size of kernel
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_medianBlur(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
int depth,
int cn,
int ksize);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Computes Sobel derivatives
///
/// @param src_data Source image data
/// @param src_step Source image step
/// @param dst_data Destination image data
/// @param dst_step Destination image step
/// @param width Source image width
/// @param height Source image height
/// @param src_depth Depth of source image
/// @param dst_depth Depths of destination image
/// @param cn Number of channels
/// @param margin_left Left margins for source image
/// @param margin_top Top margins for source image
/// @param margin_right Right margins for source image
/// @param margin_bottom Bottom margins for source image
/// @param dx orders of the derivative x
/// @param dy orders of the derivative y
/// @param ksize Size of kernel
/// @param scale Scale factor for the computed derivative values
/// @param delta Delta value that is added to the results prior to storing them in dst
/// @param border_type Border type
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_sobel(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
int src_depth,
int dst_depth,
int cn,
int margin_left,
int margin_top,
int margin_right,
int margin_bottom,
int dx,
int dy,
int ksize,
double scale,
double delta,
int border_type);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_boxFilter(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
int src_depth,
int dst_depth,
int cn,
int margin_left,
int margin_top,
int margin_right,
int margin_bottom,
size_t ksize_width,
size_t ksize_height,
int anchor_x,
int anchor_y,
bool normalize,
int border_type);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_adaptiveThreshold(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
double maxValue,
int adaptiveMethod,
int thresholdType,
int blockSize,
double C);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Blurs an image using a Gaussian filter.
/// @param src_data Source image data
/// @param src_step Source image step
/// @param dst_data Destination image data
/// @param dst_step Destination image step
/// @param width Source image width
/// @param height Source image height
/// @param depth Depth of source and destination image
/// @param cn Number of channels
/// @param margin_left Left margins for source image
/// @param margin_top Top margins for source image
/// @param margin_right Right margins for source image
/// @param margin_bottom Bottom margins for source image
/// @param ksize Kernel size
/// @param border_type Border type
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_gaussianBlurBinomial(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
int depth,
int cn,
size_t margin_left,
size_t margin_top,
size_t margin_right,
size_t margin_bottom,
size_t ksize,
int border_type);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Applies a perspective transformation to an image.
///
/// @param src_type Source and destination image type
/// @param src_data Source image data
/// @param src_step Source image step
/// @param src_width Source image width
/// @param src_height Source image height
/// @param dst_data Destination image data
/// @param dst_step Destination image step
/// @param dst_width Destination image width
/// @param dst_height Destination image height
/// @param M 3x3 matrix with transform coefficients
/// @param interpolation Interpolation mode (CV_HAL_INTER_NEAREST, ...)
/// @param border_type Border processing mode (CV_HAL_BORDER_REFLECT, ...)
/// @param border_value Values to use for CV_HAL_BORDER_CONSTANT mode
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_warpPerspective(
int src_type,
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int dst_width,
int dst_height,
const double M[9],
int interpolation,
int border_type,
const double border_value[4]);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_pyrdown(
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int dst_width,
int dst_height,
int depth,
int cn,
int border_type);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_cvtBGRtoHSV(
const uchar * src_data,
size_t src_step,
uchar * dst_data,
size_t dst_step,
int width,
int height,
int depth,
int scn,
bool swapBlue,
bool isFullRange,
bool isHSV);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_cvtBGRtoYUVApprox(
const uchar * src_data,
size_t src_step,
uchar * dst_data,
size_t dst_step,
int width,
int height,
int depth,
int scn,
bool swapBlue,
bool isCbCr);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// @brief Canny edge detector
/// @param src_data Source image data
/// @param src_step Source image step
/// @param dst_data Destination image data
/// @param dst_step Destination image step
/// @param width Source image width
/// @param height Source image height
/// @param cn Number of channels
/// @param lowThreshold low thresholds value
/// @param highThreshold high thresholds value
/// @param ksize Kernel size for Sobel operator.
/// @param L2gradient Flag, indicating use of L2 or L1 norma.
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int fastcv_hal_canny(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
int cn,
double lowThreshold,
double highThreshold,
int ksize,
bool L2gradient);
#endif
+84
View File
@@ -0,0 +1,84 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#ifndef OPENCV_FASTCV_HAL_UTILS_HPP_INCLUDED
#define OPENCV_FASTCV_HAL_UTILS_HPP_INCLUDED
#include "fastcv.h"
#include <opencv2/core/utils/logger.hpp>
#define INITIALIZATION_CHECK \
{ \
if (!FastCvContext::getContext().isInitialized) \
{ \
return CV_HAL_ERROR_UNKNOWN; \
} \
}
#define CV_HAL_RETURN(status, func) \
{ \
if( status == FASTCV_SUCCESS ) \
{ \
CV_LOG_DEBUG(NULL, "FastCV HAL for "<<#func<<" run successfully!"); \
return CV_HAL_ERROR_OK; \
} \
else if(status == FASTCV_EBADPARAM || status == FASTCV_EUNALIGNPARAM || \
status == FASTCV_EUNSUPPORTED || status == FASTCV_EHWQDSP || \
status == FASTCV_EHWGPU) \
{ \
CV_LOG_DEBUG(NULL, "FastCV status:"<<getFastCVErrorString(status) \
<<", Switching to default OpenCV solution!"); \
return CV_HAL_ERROR_NOT_IMPLEMENTED; \
} \
else \
{ \
CV_LOG_ERROR(NULL,"FastCV error:"<<getFastCVErrorString(status)); \
return CV_HAL_ERROR_UNKNOWN; \
} \
}
#define CV_HAL_RETURN_NOT_IMPLEMENTED(reason) \
{ \
CV_LOG_DEBUG(NULL,"Switching to default OpenCV\nInfo: "<<reason); \
return CV_HAL_ERROR_NOT_IMPLEMENTED; \
}
#define FCV_KernelSize_SHIFT 3
#define FCV_MAKETYPE(ksize,depth) ((ksize<<FCV_KernelSize_SHIFT) + depth)
#define FCV_CMP_EQ(val1,val2) (fabs(val1 - val2) < FLT_EPSILON)
const char* getFastCVErrorString(int status);
const char* borderToString(int border);
const char* interpolationToString(int interpolation);
struct FastCvContext
{
public:
// initialize at first call
// Defines a static local variable context. Variable is created only once.
static FastCvContext& getContext()
{
static FastCvContext context;
return context;
}
FastCvContext()
{
if (fcvSetOperationMode(FASTCV_OP_CPU_PERFORMANCE) != 0)
{
CV_LOG_WARNING(NULL, "Failed to switch FastCV operation mode");
isInitialized = false;
}
else
{
CV_LOG_INFO(NULL, "FastCV Operation Mode Switched");
isInitialized = true;
}
}
bool isInitialized;
};
#endif
+740
View File
@@ -0,0 +1,740 @@
/*
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#include "fastcv_hal_core.hpp"
#include "fastcv_hal_utils.hpp"
#include <opencv2/core/core.hpp>
#include <opencv2/core/base.hpp>
class ParallelTableLookup : public cv::ParallelLoopBody
{
public:
ParallelTableLookup(const uchar* src_data_, int width_, size_t src_step_, const uchar* lut_data_, uchar* dst_data_, size_t dst_step_) :
cv::ParallelLoopBody(), src_data(src_data_), width(width_), src_step(src_step_), lut_data(lut_data_), dst_data(dst_data_), dst_step(dst_step_)
{
}
virtual void operator()(const cv::Range& range) const CV_OVERRIDE
{
fcvStatus status = FASTCV_SUCCESS;
for (int y = range.start; y < range.end; y++) {
status = fcvTableLookupu8((uint8_t*)src_data + y * src_step, width, 1, src_step, (uint8_t*)lut_data, (uint8_t*)dst_data + y * dst_step, dst_step);
if(status != FASTCV_SUCCESS)
CV_LOG_ERROR(NULL,"FastCV error:"<<getFastCVErrorString(status));
}
}
private:
const uchar* src_data;
int width;
size_t src_step;
const uchar* lut_data;
uchar* dst_data;
size_t dst_step;
};
int fastcv_hal_lut(
const uchar* src_data,
size_t src_step,
size_t src_type,
const uchar* lut_data,
size_t lut_channel_size,
size_t lut_channels,
uchar* dst_data,
size_t dst_step,
int width,
int height)
{
if((width*height)<=(320*240))
CV_HAL_RETURN_NOT_IMPLEMENTED("Switching to default OpenCV solution!");
INITIALIZATION_CHECK;
fcvStatus status;
if (src_type == CV_8UC1 && lut_channels == 1 && lut_channel_size == 1)
{
cv::parallel_for_(cv::Range(0, height),
ParallelTableLookup(src_data, width, src_step, lut_data, dst_data, dst_step));
status = FASTCV_SUCCESS;
CV_HAL_RETURN(status, hal_lut);
}
else
{
CV_HAL_RETURN_NOT_IMPLEMENTED("Multi-channel input is not supported");
}
}
int fastcv_hal_normHammingDiff8u(
const uchar* a,
const uchar* b,
int n,
int cellSize,
int* result)
{
fcvStatus status;
if (cellSize != 1)
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("NORM_HAMMING2 cellSize:%d is not supported", cellSize));
INITIALIZATION_CHECK;
uint32_t dist = 0;
dist = fcvHammingDistanceu8((uint8_t*)a, (uint8_t*)b, n);
*result = dist;
status = FASTCV_SUCCESS;
CV_HAL_RETURN(status, hal_normHammingDiff8u);
}
int fastcv_hal_mul8u16u(
const uchar* src1_data,
size_t src1_step,
const uchar* src2_data,
size_t src2_step,
ushort* dst_data,
size_t dst_step,
int width,
int height,
double scale)
{
if(scale != 1.0)
CV_HAL_RETURN_NOT_IMPLEMENTED("Scale factor not supported");
INITIALIZATION_CHECK;
fcvStatus status = FASTCV_SUCCESS;
if (src1_step < (size_t)width && src2_step < (size_t)width)
{
src1_step = width*sizeof(uchar);
src2_step = width*sizeof(uchar);
dst_step = width*sizeof(ushort);
}
status = fcvElementMultiplyu8u16_v2(src1_data, width, height, src1_step,
src2_data, src2_step, dst_data, dst_step);
CV_HAL_RETURN(status,hal_multiply);
}
int fastcv_hal_sub8u32f(
const uchar* src1_data,
size_t src1_step,
const uchar* src2_data,
size_t src2_step,
float* dst_data,
size_t dst_step,
int width,
int height)
{
INITIALIZATION_CHECK;
fcvStatus status = FASTCV_SUCCESS;
if (src1_step < (size_t)width && src2_step < (size_t)width)
{
src1_step = width*sizeof(uchar);
src2_step = width*sizeof(uchar);
dst_step = width*sizeof(float);
}
status = fcvImageDiffu8f32_v2(src1_data, src2_data, width, height, src1_step,
src2_step, dst_data, dst_step);
CV_HAL_RETURN(status,hal_subtract);
}
int fastcv_hal_transpose2d(
const uchar* src_data,
size_t src_step,
uchar* dst_data,
size_t dst_step,
int src_width,
int src_height,
int element_size)
{
INITIALIZATION_CHECK;
if (src_data == dst_data)
CV_HAL_RETURN_NOT_IMPLEMENTED("In-place not supported");
fcvStatus status = FASTCV_SUCCESS;
switch (element_size)
{
case 1:
status = fcvTransposeu8_v2(src_data, src_width, src_height, src_step,
dst_data, dst_step);
break;
case 2:
status = fcvTransposeu16_v2((const uint16_t*)src_data, src_width, src_height,
src_step, (uint16_t*)dst_data, dst_step);
break;
case 4:
status = fcvTransposef32_v2((const float32_t*)src_data, src_width, src_height,
src_step, (float32_t*)dst_data, dst_step);
break;
default:
CV_HAL_RETURN_NOT_IMPLEMENTED("srcType not supported");
}
CV_HAL_RETURN(status,hal_transpose);
}
int fastcv_hal_meanStdDev(
const uchar* src_data,
size_t src_step,
int width,
int height,
int src_type,
double* mean_val,
double* stddev_val,
uchar* mask,
size_t mask_step)
{
INITIALIZATION_CHECK;
CV_UNUSED(mask_step);
if(src_type != CV_8UC1)
{
CV_HAL_RETURN_NOT_IMPLEMENTED("src type not supported");
}
else if(mask != nullptr)
{
CV_HAL_RETURN_NOT_IMPLEMENTED("mask not supported");
}
else if(mean_val == nullptr && stddev_val == nullptr)
{
CV_HAL_RETURN_NOT_IMPLEMENTED("null ptr for mean and stddev");
}
float32_t mean, variance;
fcvStatus status = fcvImageIntensityStats_v2(src_data, src_step, 0, 0, width, height,
&mean, &variance, FASTCV_BIASED_VARIANCE_ESTIMATOR);
if(mean_val != nullptr)
*mean_val = mean;
if(stddev_val != nullptr)
*stddev_val = std::sqrt(variance);
CV_HAL_RETURN(status,hal_meanStdDev);
}
int fastcv_hal_flip(
int src_type,
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int flip_mode)
{
INITIALIZATION_CHECK;
if(src_type!=CV_8UC1 && src_type!=CV_16UC1 && src_type!=CV_8UC3)
CV_HAL_RETURN_NOT_IMPLEMENTED("Data type is not supported, Switching to default OpenCV solution!");
if((src_width*src_height)<=(640*480))
CV_HAL_RETURN_NOT_IMPLEMENTED("Switching to default OpenCV solution!");
fcvStatus status = FASTCV_SUCCESS;;
fcvFlipDir dir;
switch (flip_mode)
{
//Flip around X-Axis: Vertical Flip or FLIP_ROWS
case 0:
CV_HAL_RETURN_NOT_IMPLEMENTED("Switching to default OpenCV solution due to low perf!");
dir = FASTCV_FLIP_VERT;
break;
//Flip around Y-Axis: Horizontal Flip or FLIP_COLS
case 1:
dir = FASTCV_FLIP_HORIZ;
break;
//Flip around both X and Y-Axis or FLIP_BOTH
case -1:
dir = FASTCV_FLIP_BOTH;
break;
default:
CV_HAL_RETURN_NOT_IMPLEMENTED("Invalid flip_mode, Switching to default OpenCV solution!");
}
if(src_type==CV_8UC1)
fcvFlipu8(src_data, src_width, src_height, src_step, dst_data, dst_step, dir);
else if(src_type==CV_16UC1)
fcvFlipu16((uint16_t*)src_data, src_width, src_height, src_step, (uint16_t*)dst_data, dst_step, dir);
else if(src_type==CV_8UC3)
status = fcvFlipRGB888u8((uint8_t*)src_data, src_width, src_height, src_step, (uint8_t*)dst_data, dst_step, dir);
else
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("Data type:%d is not supported, Switching to default OpenCV solution!", src_type));
CV_HAL_RETURN(status, hal_flip);
}
int fastcv_hal_rotate(
int src_type,
const uchar* src_data,
size_t src_step,
int src_width,
int src_height,
uchar* dst_data,
size_t dst_step,
int angle)
{
if((src_width*src_height)<(120*80))
CV_HAL_RETURN_NOT_IMPLEMENTED("Switching to default OpenCV solution for lower resolution!");
fcvStatus status;
fcvRotateDegree degree;
if (src_type != CV_8UC1 && src_type != CV_8UC2)
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("src_type:%d is not supported", src_type));
INITIALIZATION_CHECK;
switch (angle)
{
case 90:
degree = FASTCV_ROTATE_90;
break;
case 180:
degree = FASTCV_ROTATE_180;
break;
case 270:
degree = FASTCV_ROTATE_270;
break;
default:
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("Rotation angle:%d is not supported", angle));
}
switch(src_type)
{
case CV_8UC1:
status = fcvRotateImageu8(src_data, src_width, src_height, src_step, dst_data, dst_step, degree);
break;
case CV_8UC2:
status = fcvRotateImageInterleavedu8((uint8_t*)src_data, src_width, src_height, src_step, (uint8_t*)dst_data,
dst_step, degree);
break;
default:
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("src_type:%d is not supported", src_type));
}
CV_HAL_RETURN(status, hal_rotate);
}
int fastcv_hal_addWeighted8u(
const uchar* src1_data,
size_t src1_step,
const uchar* src2_data,
size_t src2_step,
uchar* dst_data,
size_t dst_step,
int width,
int height,
const double scalars[3])
{
if( (scalars[0] < -128.0f) || (scalars[0] >= 128.0f) ||
(scalars[1] < -128.0f) || (scalars[1] >= 128.0f) ||
(scalars[2] < -(1<<23))|| (scalars[2] >= 1<<23))
CV_HAL_RETURN_NOT_IMPLEMENTED(
cv::format("Alpha:%f,Beta:%f,Gamma:%f is not supported because it's too large or too small\n",
scalars[0],scalars[1],scalars[2]));
INITIALIZATION_CHECK;
fcvStatus status = FASTCV_SUCCESS;
if (height == 1)
{
src1_step = width*sizeof(uchar);
src2_step = width*sizeof(uchar);
dst_step = width*sizeof(uchar);
cv::parallel_for_(cv::Range(0, width), [&](const cv::Range &range){
int rangeWidth = range.end - range.start;
const uint8_t *src1 = src1_data + range.start;
const uint8_t *src2 = src2_data + range.start;
uint8_t *dst = dst_data + range.start;
fcvAddWeightedu8_v2(src1, rangeWidth, height, src1_step, src2, src2_step,
scalars[0], scalars[1], scalars[2], dst, dst_step);
});
}
else
{
cv::parallel_for_(cv::Range(0, height), [&](const cv::Range &range){
int rangeHeight = range.end - range.start;
const uint8_t *src1 = src1_data + range.start * src1_step;
const uint8_t *src2 = src2_data + range.start * src2_step;
uint8_t *dst = dst_data + range.start * dst_step;
fcvAddWeightedu8_v2(src1, width, rangeHeight, src1_step, src2, src2_step,
scalars[0], scalars[1], scalars[2], dst, dst_step);
});
}
CV_HAL_RETURN(status, hal_addWeighted8u_v2);
}
int fastcv_hal_mul8u(
const uchar *src1_data,
size_t src1_step,
const uchar *src2_data,
size_t src2_step,
uchar *dst_data,
size_t dst_step,
int width,
int height,
double scale)
{
int8_t sF;
if(FCV_CMP_EQ(scale,1.0)) { sF = 0; }
else if(scale > 1.0)
{
if(FCV_CMP_EQ(scale,2.0)) { sF = -1; }
else if(FCV_CMP_EQ(scale,4.0)) { sF = -2; }
else if(FCV_CMP_EQ(scale,8.0)) { sF = -3; }
else if(FCV_CMP_EQ(scale,16.0)) { sF = -4; }
else if(FCV_CMP_EQ(scale,32.0)) { sF = -5; }
else if(FCV_CMP_EQ(scale,64.0)) { sF = -6; }
else if(FCV_CMP_EQ(scale,128.0)) { sF = -7; }
else if(FCV_CMP_EQ(scale,256.0)) { sF = -8; }
else CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
}
else if(scale > 0 && scale < 1.0)
{
if(FCV_CMP_EQ(scale,1/2.0)) { sF = 1; }
else if(FCV_CMP_EQ(scale,1/4.0)) { sF = 2; }
else if(FCV_CMP_EQ(scale,1/8.0)) { sF = 3; }
else if(FCV_CMP_EQ(scale,1/16.0)) { sF = 4; }
else if(FCV_CMP_EQ(scale,1/32.0)) { sF = 5; }
else if(FCV_CMP_EQ(scale,1/64.0)) { sF = 6; }
else if(FCV_CMP_EQ(scale,1/128.0)) { sF = 7; }
else if(FCV_CMP_EQ(scale,1/256.0)) { sF = 8; }
else CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
}
else
CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
INITIALIZATION_CHECK;
int nStripes = cv::getNumThreads();
if(height == 1)
{
cv::parallel_for_(cv::Range(0, width), [&](const cv::Range &range){
int rangeWidth = range.end - range.start;
const uchar* yS1 = src1_data + static_cast<size_t>(range.start);
const uchar* yS2 = src2_data + static_cast<size_t>(range.start);
uchar* yD = dst_data + static_cast<size_t>(range.start);
fcvElementMultiplyu8(yS1, rangeWidth, 1, 0, yS2, 0, sF,
FASTCV_CONVERT_POLICY_SATURATE, yD, 0);
}, nStripes);
}
else
{
cv::parallel_for_(cv::Range(0, height), [&](const cv::Range &range){
int rangeHeight = range.end - range.start;
const uchar* yS1 = src1_data + static_cast<size_t>(range.start)*src1_step;
const uchar* yS2 = src2_data + static_cast<size_t>(range.start)*src2_step;
uchar* yD = dst_data + static_cast<size_t>(range.start)*dst_step;
fcvElementMultiplyu8(yS1, width, rangeHeight, src1_step, yS2, src2_step,
sF, FASTCV_CONVERT_POLICY_SATURATE, yD, dst_step);
}, nStripes);
}
fcvStatus status = FASTCV_SUCCESS;
CV_HAL_RETURN(status, hal_mul8u);
}
int fastcv_hal_mul16s(
const short *src1_data,
size_t src1_step,
const short *src2_data,
size_t src2_step,
short *dst_data,
size_t dst_step,
int width,
int height,
double scale)
{
int8_t sF;
if(FCV_CMP_EQ(scale,1.0)) { sF = 0; }
else if(scale > 1.0)
{
if(FCV_CMP_EQ(scale,2.0)) { sF = -1; }
else if(FCV_CMP_EQ(scale,4.0)) { sF = -2; }
else if(FCV_CMP_EQ(scale,8.0)) { sF = -3; }
else if(FCV_CMP_EQ(scale,16.0)) { sF = -4; }
else if(FCV_CMP_EQ(scale,32.0)) { sF = -5; }
else if(FCV_CMP_EQ(scale,64.0)) { sF = -6; }
else if(FCV_CMP_EQ(scale,128.0)) { sF = -7; }
else if(FCV_CMP_EQ(scale,256.0)) { sF = -8; }
else CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
}
else if(scale > 0 && scale < 1.0)
{
if(FCV_CMP_EQ(scale,1/2.0)) { sF = 1; }
else if(FCV_CMP_EQ(scale,1/4.0)) { sF = 2; }
else if(FCV_CMP_EQ(scale,1/8.0)) { sF = 3; }
else if(FCV_CMP_EQ(scale,1/16.0)) { sF = 4; }
else if(FCV_CMP_EQ(scale,1/32.0)) { sF = 5; }
else if(FCV_CMP_EQ(scale,1/64.0)) { sF = 6; }
else if(FCV_CMP_EQ(scale,1/128.0)) { sF = 7; }
else if(FCV_CMP_EQ(scale,1/256.0)) { sF = 8; }
else CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
}
else
CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
INITIALIZATION_CHECK;
int nStripes = cv::getNumThreads();
if(height == 1)
{
cv::parallel_for_(cv::Range(0, width), [&](const cv::Range &range){
int rangeWidth = range.end - range.start;
const short* yS1 = src1_data + static_cast<size_t>(range.start);
const short* yS2 = src2_data + static_cast<size_t>(range.start);
short* yD = dst_data + static_cast<size_t>(range.start);
fcvElementMultiplys16(yS1, rangeWidth, 1, 0, yS2, 0, sF,
FASTCV_CONVERT_POLICY_SATURATE, yD, 0);
}, nStripes);
}
else
{
cv::parallel_for_(cv::Range(0, height), [&](const cv::Range &range){
int rangeHeight = range.end - range.start;
const short* yS1 = src1_data + static_cast<size_t>(range.start) * (src1_step/sizeof(short));
const short* yS2 = src2_data + static_cast<size_t>(range.start) * (src2_step/sizeof(short));
short* yD = dst_data + static_cast<size_t>(range.start) * (dst_step/sizeof(short));
fcvElementMultiplys16(yS1, width, rangeHeight, src1_step, yS2, src2_step,
sF, FASTCV_CONVERT_POLICY_SATURATE, yD, dst_step);
}, nStripes);
}
fcvStatus status = FASTCV_SUCCESS;
CV_HAL_RETURN(status, hal_mul16s);
}
int fastcv_hal_mul32f(
const float *src1_data,
size_t src1_step,
const float *src2_data,
size_t src2_step,
float *dst_data,
size_t dst_step,
int width,
int height,
double scale)
{
if(!FCV_CMP_EQ(scale,1.0))
CV_HAL_RETURN_NOT_IMPLEMENTED("scale factor not supported");
INITIALIZATION_CHECK;
int nStripes = cv::getNumThreads();
if(height == 1)
{
cv::parallel_for_(cv::Range(0, width), [&](const cv::Range &range){
int rangeWidth = range.end - range.start;
const float* yS1 = src1_data + static_cast<size_t>(range.start);
const float* yS2 = src2_data + static_cast<size_t>(range.start);
float* yD = dst_data + static_cast<size_t>(range.start);
fcvElementMultiplyf32(yS1, rangeWidth, 1, 0, yS2, 0, yD, 0);
}, nStripes);
}
else
{
cv::parallel_for_(cv::Range(0, height), [&](const cv::Range &range){
int rangeHeight = range.end - range.start;
const float* yS1 = src1_data + static_cast<size_t>(range.start) * (src1_step/sizeof(float));
const float* yS2 = src2_data + static_cast<size_t>(range.start) * (src2_step/sizeof(float));
float* yD = dst_data + static_cast<size_t>(range.start) * (dst_step/sizeof(float));
fcvElementMultiplyf32(yS1, width, rangeHeight, src1_step,
yS2, src2_step, yD, dst_step);
}, nStripes);
}
fcvStatus status = FASTCV_SUCCESS;
CV_HAL_RETURN(status, hal_mul32f);
}
int fastcv_hal_SVD32f(
float* src,
size_t src_step,
float* w,
float* u,
size_t u_step,
float* vt,
size_t vt_step,
int m,
int n,
int flags)
{
if (n * sizeof(float) != src_step)
CV_HAL_RETURN_NOT_IMPLEMENTED("step is not supported");
INITIALIZATION_CHECK;
fcvStatus status = FASTCV_SUCCESS;
cv::Mat tmpU(m, n, CV_32F);
cv::Mat tmpV(n, n, CV_32F);
switch (flags)
{
case CV_HAL_SVD_NO_UV:
{
status = fcvSVDf32_v2(src, m, n, w, u, vt, (float32_t *)tmpU.data, (float32_t *)tmpV.data, false);
break;
}
case CV_HAL_SVD_SHORT_UV:
{
if ((n * sizeof(float) == u_step) && (n * sizeof(float) == vt_step))
status = fcvSVDf32_v2(src, m, n, w, u, vt, (float32_t *)tmpU.data, (float32_t *)tmpV.data, false);
else
CV_HAL_RETURN_NOT_IMPLEMENTED("step is not supported");
break;
}
case CV_HAL_SVD_FULL_UV:
{
if ((n * sizeof(float) == u_step) && (n * sizeof(float) == vt_step))
status = fcvSVDf32_v2(src, m, n, w, u, vt, (float32_t *)tmpU.data, (float32_t *)tmpV.data, true);
else
CV_HAL_RETURN_NOT_IMPLEMENTED("step is not supported");
break;
}
default:
CV_HAL_RETURN_NOT_IMPLEMENTED(cv::format("Flags:%d is not supported", flags));
}
CV_HAL_RETURN(status, fastcv_hal_SVD32f);
}
int fastcv_hal_gemm32f(
const float* src1,
size_t src1_step,
const float* src2,
size_t src2_step,
float alpha,
const float* src3,
size_t src3_step,
float beta,
float* dst,
size_t dst_step,
int m,
int n,
int k,
int flags)
{
cv::Mat src1_t, src2_t, src3_t, dst_temp1;
int height_a = m, width_a = n, width_d = k;
const float *src1p = src1, *src2p = src2, *src3p = src3;
INITIALIZATION_CHECK;
if((flags & (cv::GEMM_1_T)) && (flags & (cv::GEMM_2_T)))
{
height_a = n; width_a = m;
}
else if(flags & (cv::GEMM_1_T))
{
src1_t = cv::Mat(width_a, height_a, CV_32FC1);
fcvTransposef32_v2(src1, width_a, height_a, src1_step, src1_t.ptr<float>(), src1_t.step[0]);
src1p = src1_t.ptr<float>();
src1_step = src1_t.step[0];
height_a = n; width_a = m;
}
else if(flags & (cv::GEMM_2_T))
{
src2_t = cv::Mat(width_a, width_d, CV_32FC1);
fcvTransposef32_v2(src2, width_a, width_d, src2_step, src2_t.ptr<float>(), src2_t.step[0]);
src2p = src2_t.ptr<float>();
src2_step = src2_t.step[0];
}
if((flags & cv::GEMM_3_T) && beta != 0.0 && src3 != NULL)
{
src3_t = cv::Mat(height_a, width_d, CV_32FC1);
fcvTransposef32_v2(src3, height_a, width_d, src3_step, src3_t.ptr<float>(), src3_t.step[0]);
src3p = src3_t.ptr<float>();
src3_step = src3_t.step[0];
}
bool inplace = false;
size_t dst_stride;
float *dstp = NULL;
if(src1 == dst || src2 == dst || src3 == dst)
{
dst_temp1 = cv::Mat(height_a, width_d, CV_32FC1);
dstp = dst_temp1.ptr<float>();
inplace = true;
dst_stride = dst_temp1.step[0];
}
else
{
dstp = dst;
dst_stride = dst_step;
}
float *dstp1 = dstp;
fcvStatus status = FASTCV_SUCCESS;
if(alpha != 0.0)
{
if((flags & (cv::GEMM_1_T)) && (flags & (cv::GEMM_2_T)))
{
cv::Mat dst_temp2 = cv::Mat(k, n, CV_32FC1);
fcvMatrixMultiplyf32_v2(src2p, m, k, src2_step, src1p, n, src1_step,
dst_temp2.ptr<float>(), dst_temp2.step[0]);
fcvTransposef32_v2(dst_temp2.ptr<float>(), n, k, dst_temp2.step[0], dstp, dst_stride);
}
else
{
status = fcvMatrixMultiplyf32_v2(src1p, width_a, height_a, src1_step, src2p, width_d,
src2_step, dstp, dst_stride);
}
}
if(alpha != 1.0 && alpha != 0.0 && status == FASTCV_SUCCESS)
{
status = fcvMultiplyScalarf32(dstp, width_d, height_a, dst_stride, alpha, dstp1, dst_stride);
}
if(src3 != NULL && beta != 0.0 && status == FASTCV_SUCCESS)
{
cv::Mat dst3 = cv::Mat(height_a, width_d, CV_32FC1);
if(beta != 1.0)
{
status = fcvMultiplyScalarf32(src3p, width_d, height_a, src3_step, beta, (float32_t*)dst3.data, dst3.step);
if(status == FASTCV_SUCCESS)
fcvAddf32_v2(dstp, width_d, height_a, dst_stride, (float32_t*)dst3.data, dst3.step, dstp1, dst_stride);
}
else
fcvAddf32_v2(dstp, width_d, height_a, dst_stride, src3p, src3_step, dstp1, dst_stride);
}
if(inplace)
{
cv::Mat dst_mat = cv::Mat(height_a, width_d, CV_32FC1, (void*)dst, dst_step);
dst_temp1.copyTo(dst_mat);
}
CV_HAL_RETURN(status,hal_gemm32f);
}
File diff suppressed because it is too large Load Diff
+56
View File
@@ -0,0 +1,56 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#include "fastcv_hal_utils.hpp"
const char* getFastCVErrorString(int status)
{
switch(status)
{
case FASTCV_SUCCESS: return "Successful";
case FASTCV_EFAIL: return "General failure";
case FASTCV_EUNALIGNPARAM: return "Unaligned pointer parameter";
case FASTCV_EBADPARAM: return "Bad parameters";
case FASTCV_EINVALSTATE: return "Called at invalid state";
case FASTCV_ENORES: return "Insufficient resources, memory, thread, etc";
case FASTCV_EUNSUPPORTED: return "Unsupported feature";
case FASTCV_EHWQDSP: return "Hardware QDSP failed to respond";
case FASTCV_EHWGPU: return "Hardware GPU failed to respond";
default: return "Unknown FastCV Error";
}
}
const char* borderToString(int border)
{
switch (border)
{
case 0: return "BORDER_CONSTANT";
case 1: return "BORDER_REPLICATE";
case 2: return "BORDER_REFLECT";
case 3: return "BORDER_WRAP";
case 4: return "BORDER_REFLECT_101";
case 5: return "BORDER_TRANSPARENT";
default: return "Unknown border type";
}
}
const char* interpolationToString(int interpolation)
{
switch (interpolation)
{
case 0: return "INTER_NEAREST";
case 1: return "INTER_LINEAR";
case 2: return "INTER_CUBIC";
case 3: return "INTER_AREA";
case 4: return "INTER_LANCZOS4";
case 5: return "INTER_LINEAR_EXACT";
case 6: return "INTER_NEAREST_EXACT";
case 7: return "INTER_MAX";
case 8: return "WARP_FILL_OUTLIERS";
case 16: return "WARP_INVERSE_MAP";
case 32: return "WARP_RELATIVE_MAP";
default: return "Unknown interpolation type";
}
}