Fix spelling typos

backport commit 659ffaddb4
This commit is contained in:
Brian Wignall
2019-12-26 06:45:03 -05:00
committed by Alexander Alekhin
parent 5e2bcc9149
commit f9c514b391
70 changed files with 89 additions and 89 deletions
+1 -1
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@@ -1218,7 +1218,7 @@ struct CV_EXPORTS_W_SIMPLE CirclesGridFinderParameters2 : public CirclesGridFind
CV_WRAP CirclesGridFinderParameters2();
CV_PROP_RW float squareSize; //!< Distance between two adjacent points. Used by CALIB_CB_CLUSTERING.
CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from predicion. Used by CALIB_CB_CLUSTERING.
CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from prediction. Used by CALIB_CB_CLUSTERING.
};
/** @brief Finds centers in the grid of circles.
+1 -1
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@@ -48,7 +48,7 @@
#include <iterator>
/*
This is stright-forward port v3 of Matlab calibration engine by Jean-Yves Bouguet
This is straight-forward port v3 of Matlab calibration engine by Jean-Yves Bouguet
that is (in a large extent) based on the paper:
Z. Zhang. "A flexible new technique for camera calibration".
IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000.
@@ -115,7 +115,7 @@ void CV_ChessboardDetectorBadArgTest::run( int /*start_from */)
img = cb.clone();
pattern_size = Size(2,2);
errors += run_test_case( CV_StsOutOfRange, "Invlid pattern size" );
errors += run_test_case( CV_StsOutOfRange, "Invalid pattern size" );
pattern_size = cbg.cornersSize();
cb.convertTo(img, CV_32F);
+1 -1
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@@ -1309,7 +1309,7 @@ CVAPI(void) cvMulTransposed( const CvArr* src, CvArr* dst, int order,
const CvArr* delta CV_DEFAULT(NULL),
double scale CV_DEFAULT(1.) );
/** Tranposes matrix. Square matrices can be transposed in-place */
/** Transposes matrix. Square matrices can be transposed in-place */
CVAPI(void) cvTranspose( const CvArr* src, CvArr* dst );
#define cvT cvTranspose
@@ -569,7 +569,7 @@ inline v_int64x4 v256_blend(const v_int64x4& a, const v_int64x4& b)
{ return v_int64x4(v256_blend<m>(v_uint64x4(a.val), v_uint64x4(b.val)).val); }
// shuffle
// todo: emluate 64bit
// todo: emulate 64bit
#define OPENCV_HAL_IMPL_AVX_SHUFFLE(_Tpvec, intrin) \
template<int m> \
inline _Tpvec v256_shuffle(const _Tpvec& a) \
@@ -73,7 +73,7 @@ implemented as a structure based on a one SIMD register.
- cv::v_uint8x16 and cv::v_int8x16: sixteen 8-bit integer values (unsigned/signed) - char
- cv::v_uint16x8 and cv::v_int16x8: eight 16-bit integer values (unsigned/signed) - short
- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsgined/signed) - int
- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsigned/signed) - int
- cv::v_uint64x2 and cv::v_int64x2: two 64-bit integer values (unsigned/signed) - int64
- cv::v_float32x4: four 32-bit floating point values (signed) - float
- cv::v_float64x2: two 64-bit floating point values (signed) - double
@@ -1805,7 +1805,7 @@ inline v_float32x4 v_broadcast_element(const v_float32x4& a)
return v_setall_f32(v_extract_n<i>(a));
}
////// FP16 suport ///////
////// FP16 support ///////
#if CV_FP16
inline v_float32x4 v_load_expand(const float16_t* ptr)
{
@@ -94,7 +94,7 @@ struct v_uint16x8
}
ushort get0() const
{
return (ushort)wasm_i16x8_extract_lane(val, 0); // wasm_u16x8_extract_lane() unimplemeted yet
return (ushort)wasm_i16x8_extract_lane(val, 0); // wasm_u16x8_extract_lane() unimplemented yet
}
v128_t val;
@@ -50,7 +50,7 @@ typedef double v1f64 __attribute__ ((vector_size(8), aligned(8)));
#define msa_ld1q_f32(__a) ((v4f32)__builtin_msa_ld_w(__a, 0))
#define msa_ld1q_f64(__a) ((v2f64)__builtin_msa_ld_d(__a, 0))
/* Store 64bits vector elments values to the given memory address. */
/* Store 64bits vector elements values to the given memory address. */
#define msa_st1_s8(__a, __b) (*((v8i8*)(__a)) = __b)
#define msa_st1_s16(__a, __b) (*((v4i16*)(__a)) = __b)
#define msa_st1_s32(__a, __b) (*((v2i32*)(__a)) = __b)
@@ -377,7 +377,7 @@ typedef double v1f64 __attribute__ ((vector_size(8), aligned(8)));
})
/* Right shift elements in a 128 bits vector by an immediate value, saturate the results and them in a 64 bits vector.
Input is signed and outpus is unsigned. */
Input is signed and output is unsigned. */
#define msa_qrshrun_n_s16(__a, __b) \
({ \
v8i16 __d = __builtin_msa_srlri_h(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a)), (int)(__b)); \
@@ -62,7 +62,7 @@ static String getDeviceTypeString(const cv::ocl::Device& device)
}
}
return "unkown";
return "unknown";
}
} // namespace
+1 -1
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@@ -165,7 +165,7 @@ public:
/** @brief Sets the initial step that will be used in downhill simplex algorithm.
Step, together with initial point (givin in DownhillSolver::minimize) are two `n`-dimensional
Step, together with initial point (given in DownhillSolver::minimize) are two `n`-dimensional
vectors that are used to determine the shape of initial simplex. Roughly said, initial point
determines the position of a simplex (it will become simplex's centroid), while step determines the
spread (size in each dimension) of a simplex. To be more precise, if \f$s,x_0\in\mathbb{R}^n\f$ are
@@ -317,7 +317,7 @@ VSX_IMPL_1RG(vec_udword2, wi, vec_float4, wf, xvcvspuxds, vec_ctulo)
* Also there's already an open bug https://bugs.llvm.org/show_bug.cgi?id=31837
*
* So we're not able to use inline asm and only use built-in functions that CLANG supports
* and use __builtin_convertvector if clang missng any of vector conversions built-in functions
* and use __builtin_convertvector if clang missing any of vector conversions built-in functions
*
* todo: clang asm template bug is fixed, need to reconsider the current workarounds.
*/
@@ -491,7 +491,7 @@ VSX_IMPL_CONV_EVEN_2_4(vec_uint4, vec_double2, vec_ctu, vec_ctuo)
// Only for Eigen!
/*
* changing behavior of conversion intrinsics for gcc has effect on Eigen
* so we redfine old behavior again only on gcc, clang
* so we redefine old behavior again only on gcc, clang
*/
#if !defined(__clang__) || __clang_major__ > 4
// ignoring second arg since Eigen only truncates toward zero
+2 -2
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@@ -250,7 +250,7 @@ cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes,
for( int i = dims - 1; i >= 0; i-- )
{
if( sizes[i] < 0 )
CV_Error( CV_StsBadSize, "one of dimesion sizes is non-positive" );
CV_Error( CV_StsBadSize, "one of dimension sizes is non-positive" );
mat->dim[i].size = sizes[i];
if( step > INT_MAX )
CV_Error( CV_StsOutOfRange, "The array is too big" );
@@ -545,7 +545,7 @@ cvCreateSparseMat( int dims, const int* sizes, int type )
for( i = 0; i < dims; i++ )
{
if( sizes[i] <= 0 )
CV_Error( CV_StsBadSize, "one of dimesion sizes is non-positive" );
CV_Error( CV_StsBadSize, "one of dimension sizes is non-positive" );
}
CvSparseMat* arr = (CvSparseMat*)cvAlloc(sizeof(*arr)+MAX(0,dims-CV_MAX_DIM)*sizeof(arr->size[0]));
+2 -2
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@@ -53,7 +53,7 @@ cvtabs_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep,
}
}
// variant for convrsions 16f <-> ... w/o unrolling
// variant for conversions 16f <-> ... w/o unrolling
template<typename _Ts, typename _Td> inline void
cvtabs1_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep,
Size size, float a, float b )
@@ -123,7 +123,7 @@ cvt_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep,
}
}
// variant for convrsions 16f <-> ... w/o unrolling
// variant for conversions 16f <-> ... w/o unrolling
template<typename _Ts, typename _Td> inline void
cvt1_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep,
Size size, float a, float b )
+1 -1
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@@ -77,7 +77,7 @@ Replaced y(1,ndim,0.0) ------> y(1,ndim+1,0.0)
***********************************************************************************************************************************
The code below was used in tesing the source code.
The code below was used in testing the source code.
Created by @SareeAlnaghy
#include <iostream>
+3 -3
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@@ -1592,7 +1592,7 @@ public:
{
TlsAbstraction* tls = getTlsAbstraction();
if (NULL == tls)
return; // TLS signleton is not available (terminated)
return; // TLS singleton is not available (terminated)
ThreadData *pTD = tlsValue == NULL ? (ThreadData*)tls->getData() : (ThreadData*)tlsValue;
if (pTD == NULL)
return; // no OpenCV TLS data for this thread
@@ -1683,7 +1683,7 @@ public:
TlsAbstraction* tls = getTlsAbstraction();
if (NULL == tls)
return NULL; // TLS signleton is not available (terminated)
return NULL; // TLS singleton is not available (terminated)
ThreadData* threadData = (ThreadData*)tls->getData();
if(threadData && threadData->slots.size() > slotIdx)
@@ -1719,7 +1719,7 @@ public:
TlsAbstraction* tls = getTlsAbstraction();
if (NULL == tls)
return; // TLS signleton is not available (terminated)
return; // TLS singleton is not available (terminated)
ThreadData* threadData = (ThreadData*)tls->getData();
if(!threadData)
@@ -134,7 +134,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
virtual void setOutShape(const MatShape &outTailShape = MatShape()) = 0;
/** @deprecated Use flag `produce_cell_output` in LayerParams.
* @brief Specifies either interpret first dimension of input blob as timestamp dimenion either as sample.
* @brief Specifies either interpret first dimension of input blob as timestamp dimension either as sample.
*
* If flag is set to true then shape of input blob will be interpreted as [`T`, `N`, `[data dims]`] where `T` specifies number of timestamps, `N` is number of independent streams.
* In this case each forward() call will iterate through `T` timestamps and update layer's state `T` times.
+2 -2
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@@ -622,7 +622,7 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
try {
wrapper->outProms[processedOutputs].setException(std::current_exception());
} catch(...) {
CV_LOG_ERROR(NULL, "DNN: Exception occured during async inference exception propagation");
CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
}
}
}
@@ -635,7 +635,7 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
try {
wrapper->outProms[processedOutputs].setException(e);
} catch(...) {
CV_LOG_ERROR(NULL, "DNN: Exception occured during async inference exception propagation");
CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
}
}
}
+3 -3
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@@ -116,7 +116,7 @@ message AttributeProto {
// The type field MUST be present for this version of the IR.
// For 0.0.1 versions of the IR, this field was not defined, and
// implementations needed to use has_field hueristics to determine
// implementations needed to use has_field heuristics to determine
// which value field was in use. For IR_VERSION 0.0.2 or later, this
// field MUST be set and match the f|i|s|t|... field in use. This
// change was made to accommodate proto3 implementations.
@@ -323,7 +323,7 @@ message TensorProto {
// For float and complex64 values
// Complex64 tensors are encoded as a single array of floats,
// with the real components appearing in odd numbered positions,
// and the corresponding imaginary component apparing in the
// and the corresponding imaginary component appearing in the
// subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i]
// is encoded as [1.0, 2.0 ,3.0 ,4.0]
// When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
@@ -373,7 +373,7 @@ message TensorProto {
// For double
// Complex64 tensors are encoded as a single array of doubles,
// with the real components appearing in odd numbered positions,
// and the corresponding imaginary component apparing in the
// and the corresponding imaginary component appearing in the
// subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i]
// is encoded as [1.0, 2.0 ,3.0 ,4.0]
// When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
@@ -385,7 +385,7 @@ code which is distributed under GPL.
class CV_EXPORTS_W MSER : public Feature2D
{
public:
/** @brief Full consturctor for %MSER detector
/** @brief Full constructor for %MSER detector
@param _delta it compares \f$(size_{i}-size_{i-delta})/size_{i-delta}\f$
@param _min_area prune the area which smaller than minArea
@@ -36,7 +36,7 @@ void image_derivatives_scharr(const cv::Mat& src, cv::Mat& dst, int xorder, int
// Nonlinear diffusion filtering scalar step
void nld_step_scalar(cv::Mat& Ld, const cv::Mat& c, cv::Mat& Lstep, float stepsize);
// For non-maxima suppresion
// For non-maxima suppression
bool check_maximum_neighbourhood(const cv::Mat& img, int dsize, float value, int row, int col, bool same_img);
// Image downsampling
+1 -1
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@@ -983,7 +983,7 @@ extractMSER_8uC3( const Mat& src,
double s = (double)(lr->size-lr->sizei)/(lr->dt-lr->di);
if ( s < lr->s )
{
// skip the first one and check stablity
// skip the first one and check stability
if ( i > lr->reinit+1 && MSCRStableCheck( lr, params ) )
{
if ( lr->tmsr == NULL )
@@ -131,7 +131,7 @@ float optimizeSimplexDownhill(T* points, int n, F func, float* vals = NULL )
}
if (val_r<vals[0]) {
// value is smaller than smalest in simplex
// value is smaller than smallest in simplex
// expand some more to see if it drops further
for (int i=0; i<n; ++i) {
@@ -1184,7 +1184,7 @@ CVAPI(CvScalar) cvColorToScalar( double packed_color, int arrtype );
/** @brief Returns the polygon points which make up the given ellipse.
The ellipse is define by the box of size 'axes' rotated 'angle' around the 'center'. A partial
sweep of the ellipse arc can be done by spcifying arc_start and arc_end to be something other than
sweep of the ellipse arc can be done by specifying arc_start and arc_end to be something other than
0 and 360, respectively. The input array 'pts' must be large enough to hold the result. The total
number of points stored into 'pts' is returned by this function.
@see cv::ellipse2Poly
+1 -1
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@@ -630,7 +630,7 @@ approxPolyDP_( const Point_<T>* src_contour, int count0, Point_<T>* dst_contour,
WRITE_PT( src_contour[count-1] );
// last stage: do final clean-up of the approximated contour -
// remove extra points on the [almost] stright lines.
// remove extra points on the [almost] straight lines.
is_closed = is_closed0;
count = new_count;
pos = is_closed ? count - 1 : 0;
+2 -2
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@@ -776,7 +776,7 @@ cv::RotatedRect cv::fitEllipseDirect( InputArray _points )
namespace cv
{
// Calculates bounding rectagnle of a point set or retrieves already calculated
// Calculates bounding rectangle of a point set or retrieves already calculated
static Rect pointSetBoundingRect( const Mat& points )
{
int npoints = points.checkVector(2);
@@ -1392,7 +1392,7 @@ cvFitEllipse2( const CvArr* array )
return cvBox2D(cv::fitEllipse(points));
}
/* Calculates bounding rectagnle of a point set or retrieves already calculated */
/* Calculates bounding rectangle of a point set or retrieves already calculated */
CV_IMPL CvRect
cvBoundingRect( CvArr* array, int update )
{
+1 -1
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@@ -325,7 +325,7 @@ void CV_ApproxPolyTest::run( int /*start_from*/ )
if( DstSeq == NULL )
{
ts->printf( cvtest::TS::LOG,
"cvApproxPoly returned NULL for contour #%d, espilon = %g\n", i, Eps );
"cvApproxPoly returned NULL for contour #%d, epsilon = %g\n", i, Eps );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
} // if( DstSeq == NULL )
+1 -1
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@@ -60,7 +60,7 @@ namespace opencv_test { namespace {
// 6 - partial intersection, rectangle on top of different size
// 7 - full intersection, rectangle fully enclosed in the other
// 8 - partial intersection, rectangle corner just touching. point contact
// 9 - partial intersetion. rectangle side by side, line contact
// 9 - partial intersection. rectangle side by side, line contact
static void compare(const std::vector<Point2f>& test, const std::vector<Point2f>& target)
{
+1 -1
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@@ -40,7 +40,7 @@ foreach(file ${seed_project_files_rel})
endforeach()
list(APPEND depends gen_opencv_java_source "${OPENCV_DEPHELPER}/gen_opencv_java_source")
ocv_copyfiles_add_target(${the_module}_android_source_copy JAVA_SRC_COPY "Copy Java(Andoid SDK) source files" ${depends})
ocv_copyfiles_add_target(${the_module}_android_source_copy JAVA_SRC_COPY "Copy Java(Android SDK) source files" ${depends})
file(REMOVE "${OPENCV_DEPHELPER}/${the_module}_android_source_copy") # force rebuild after CMake run
set(depends ${the_module}_android_source_copy "${OPENCV_DEPHELPER}/${the_module}_android_source_copy")
@@ -232,7 +232,7 @@ public abstract class CameraBridgeViewBase extends SurfaceView implements Surfac
/**
* This method is provided for clients, so they can disable camera connection and stop
* the delivery of frames even though the surface view itself is not destroyed and still stays on the scren
* the delivery of frames even though the surface view itself is not destroyed and still stays on the screen
*/
public void disableView() {
synchronized(mSyncObject) {
+1 -1
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@@ -32,4 +32,4 @@ To run performance tests, please launch a local web server in <build_dir>/bin fo
Navigate the web browser to the kernel page you want to test, like http://localhost:8080/perf/imgproc/cvtcolor.html.
You can input the paramater, and then click the `Run` button to run the specific case, or it will run all the cases.
You can input the parameter, and then click the `Run` button to run the specific case, or it will run all the cases.
+1 -1
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@@ -1679,7 +1679,7 @@ public:
/** @brief This function returns the trained parameters arranged across rows.
For a two class classifcation problem, it returns a row matrix. It returns learnt parameters of
For a two class classification problem, it returns a row matrix. It returns learnt parameters of
the Logistic Regression as a matrix of type CV_32F.
*/
CV_WRAP virtual Mat get_learnt_thetas() const = 0;
+1 -1
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@@ -1,5 +1,5 @@
#!/usr/bin/env python
"""Algorithm serializaion test."""
"""Algorithm serialization test."""
import tempfile
import os
import cv2 as cv
+1 -1
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@@ -1,5 +1,5 @@
#!/usr/bin/env python
""""Core serializaion tests."""
""""Core serialization tests."""
import tempfile
import os
import cv2 as cv
@@ -332,14 +332,14 @@ finds two best matches for each feature and leaves the best one only if the
ratio between descriptor distances is greater than the threshold match_conf.
Unlike cv::detail::BestOf2NearestMatcher this matcher uses affine
transformation (affine trasformation estimate will be placed in matches_info).
transformation (affine transformation estimate will be placed in matches_info).
@sa cv::detail::FeaturesMatcher cv::detail::BestOf2NearestMatcher
*/
class CV_EXPORTS AffineBestOf2NearestMatcher : public BestOf2NearestMatcher
{
public:
/** @brief Constructs a "best of 2 nearest" matcher that expects affine trasformation
/** @brief Constructs a "best of 2 nearest" matcher that expects affine transformation
between images
@param full_affine whether to use full affine transformation with 6 degress of freedom or reduced
+1 -1
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@@ -11367,7 +11367,7 @@ void UniversalTersePrint(const T& value, ::std::ostream* os) {
// NUL-terminated string.
template <typename T>
void UniversalPrint(const T& value, ::std::ostream* os) {
// A workarond for the bug in VC++ 7.1 that prevents us from instantiating
// A workaround for the bug in VC++ 7.1 that prevents us from instantiating
// UniversalPrinter with T directly.
typedef T T1;
UniversalPrinter<T1>::Print(value, os);
+2 -2
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@@ -94,11 +94,11 @@ class Aapt(Tool):
# get test instrumentation info
instrumentation_tag = [t for t in tags if t.startswith("instrumentation ")]
if not instrumentation_tag:
raise Err("Can not find instrumentation detials in: %s", exe)
raise Err("Can not find instrumentation details in: %s", exe)
res.pkg_runner = re.search(r"^[ ]+A: android:name\(0x[0-9a-f]{8}\)=\"(?P<runner>.*?)\" \(Raw: \"(?P=runner)\"\)\r?$", instrumentation_tag[0], flags=re.MULTILINE).group("runner")
res.pkg_target = re.search(r"^[ ]+A: android:targetPackage\(0x[0-9a-f]{8}\)=\"(?P<pkg>.*?)\" \(Raw: \"(?P=pkg)\"\)\r?$", instrumentation_tag[0], flags=re.MULTILINE).group("pkg")
if not res.pkg_name or not res.pkg_runner or not res.pkg_target:
raise Err("Can not find instrumentation detials in: %s", exe)
raise Err("Can not find instrumentation details in: %s", exe)
return res
+1 -1
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@@ -452,7 +452,7 @@ int BadArgTest::run_test_case( int expected_code, const string& _descr )
{
thrown = true;
if (e.code != expected_code &&
e.code != cv::Error::StsError && e.code != cv::Error::StsAssert // Exact error codes support will be dropped. Checks should provide proper text messages intead.
e.code != cv::Error::StsError && e.code != cv::Error::StsAssert // Exact error codes support will be dropped. Checks should provide proper text messages instead.
)
{
ts->printf(TS::LOG, "%s (test case #%d): the error code %d is different from the expected %d\n",
+2 -2
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@@ -110,7 +110,7 @@ public:
//set parameters
// N - the number of samples stored in memory per model
nN = defaultNsamples;
//kNN - k nearest neighbour - number on NN for detcting background - default K=[0.1*nN]
//kNN - k nearest neighbour - number on NN for detecting background - default K=[0.1*nN]
nkNN=MAX(1,cvRound(0.1*nN*3+0.40));
//Tb - Threshold Tb*kernelwidth
@@ -292,7 +292,7 @@ protected:
//less important parameters - things you might change but be careful
////////////////////////
int nN;//totlal number of samples
int nkNN;//number on NN for detcting background - default K=[0.1*nN]
int nkNN;//number on NN for detecting background - default K=[0.1*nN]
//shadow detection parameters
bool bShadowDetection;//default 1 - do shadow detection
+1 -1
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@@ -181,7 +181,7 @@ public:
//! computes a background image which are the mean of all background gaussians
virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE;
//! re-initiaization method
//! re-initialization method
void initialize(Size _frameSize, int _frameType)
{
frameSize = _frameSize;
@@ -319,8 +319,8 @@ enum
CV_CAP_PROP_XI_COOLING = 466, // Start camera cooling.
CV_CAP_PROP_XI_TARGET_TEMP = 467, // Set sensor target temperature for cooling.
CV_CAP_PROP_XI_CHIP_TEMP = 468, // Camera sensor temperature
CV_CAP_PROP_XI_HOUS_TEMP = 469, // Camera housing tepmerature
CV_CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, // Camera housing back side tepmerature
CV_CAP_PROP_XI_HOUS_TEMP = 469, // Camera housing temperature
CV_CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, // Camera housing back side temperature
CV_CAP_PROP_XI_SENSOR_BOARD_TEMP = 596, // Camera sensor board temperature
CV_CAP_PROP_XI_CMS = 470, // Mode of color management system.
CV_CAP_PROP_XI_APPLY_CMS = 471, // Enable applying of CMS profiles to xiGetImage (see XI_PRM_INPUT_CMS_PROFILE, XI_PRM_OUTPUT_CMS_PROFILE).
+1 -1
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@@ -299,7 +299,7 @@ bool CvCaptureCAM_Aravis::grabFrame()
size_t buffer_size;
framebuffer = (void*)arv_buffer_get_data (arv_buffer, &buffer_size);
// retrieve image size properites
// retrieve image size properties
arv_buffer_get_image_region (arv_buffer, &xoffset, &yoffset, &width, &height);
// retrieve image ID set by camera
+1 -1
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@@ -1293,7 +1293,7 @@ bool CvVideoWriter_AVFoundation::writeFrame(const IplImage* iplimage) {
colorSpace, kCGImageAlphaLast|kCGBitmapByteOrderDefault,
provider, NULL, false, kCGRenderingIntentDefault);
//CGImage -> CVPixelBufferRef coversion
//CGImage -> CVPixelBufferRef conversion
CVPixelBufferRef pixelBuffer = NULL;
CFDataRef cfData = CGDataProviderCopyData(CGImageGetDataProvider(cgImage));
int status = CVPixelBufferCreateWithBytes(NULL,
+2 -2
View File
@@ -805,7 +805,7 @@ bool CvCaptureFile::setupReadingAt(CMTime position) {
if (mMode == CV_CAP_MODE_BGR || mMode == CV_CAP_MODE_RGB) {
// For CV_CAP_MODE_BGR, read frames as BGRA (AV Foundation's YUV->RGB conversion is slightly faster than OpenCV's CV_YUV2BGR_YV12)
// kCVPixelFormatType_32ABGR is reportedly faster on OS X, but OpenCV doesn't have a CV_ABGR2BGR conversion.
// kCVPixelFormatType_24RGB is significanly slower than kCVPixelFormatType_32BGRA.
// kCVPixelFormatType_24RGB is significantly slower than kCVPixelFormatType_32BGRA.
pixelFormat = kCVPixelFormatType_32BGRA;
mFormat = CV_8UC3;
} else if (mMode == CV_CAP_MODE_GRAY) {
@@ -1323,7 +1323,7 @@ bool CvVideoWriter_AVFoundation::writeFrame(const IplImage* iplimage) {
colorSpace, kCGImageAlphaLast|kCGBitmapByteOrderDefault,
provider, NULL, false, kCGRenderingIntentDefault);
//CGImage -> CVPixelBufferRef coversion
//CGImage -> CVPixelBufferRef conversion
CVPixelBufferRef pixelBuffer = NULL;
CFDataRef cfData = CGDataProviderCopyData(CGImageGetDataProvider(cgImage));
int status = CVPixelBufferCreateWithBytes(NULL,
+1 -1
View File
@@ -1045,7 +1045,7 @@ bool GStreamerCapture::open(const String &filename_)
* \return property value
*
* There are two ways the properties can be retrieved. For seek-based properties we can query the pipeline.
* For frame-based properties, we use the caps of the lasst receivef sample. This means that some properties
* For frame-based properties, we use the caps of the last receivef sample. This means that some properties
* are not available until a first frame was received
*/
double GStreamerCapture::getProperty(int propId) const