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Merge pull request #12599 from mshabunin:printf

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pull/12655/head
Alexander Alekhin 7 years ago
parent 8811dabbac e0f524d3b7
commit d8d025c33b
17 changed files with 57 additions and 39 deletions
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  1. 2
      apps/interactive-calibration/calibController.cpp
  2. 2
      apps/interactive-calibration/frameProcessor.cpp
  3. 19
      modules/core/include/opencv2/core/operations.hpp
  4. 10
      modules/core/src/channels.cpp
  5. 6
      modules/core/src/lda.cpp
  6. 2
      modules/core/src/matrix_operations.cpp
  7. 6
      modules/core/src/ocl.cpp
  8. 10
      modules/core/test/test_io.cpp
  9. 2
      modules/dnn/src/dnn.cpp
  10. 2
      modules/dnn/src/layers/permute_layer.cpp
  11. 6
      modules/dnn/src/torch/THDiskFile.cpp
  12. 2
      modules/imgproc/src/featureselect.cpp
  13. 4
      modules/imgproc/src/histogram.cpp
  14. 12
      modules/objdetect/src/hog.cpp
  15. 5
      modules/photo/src/fast_nlmeans_denoising_opencl.hpp
  16. 2
      modules/videoio/src/container_avi.cpp
  17. 4
      samples/dnn/segmentation.cpp

2
apps/interactive-calibration/calibController.cpp
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@ -210,7 +210,7 @@ void calib::calibDataController::filterFrames()
worstElemIndex = i; worstElemIndex = i;
} }
} }
showOverlayMessage(cv::format("Frame %d is worst", worstElemIndex + 1)); showOverlayMessage(cv::format("Frame %zu is worst", worstElemIndex + 1));
if(mCalibData->imagePoints.size()) { if(mCalibData->imagePoints.size()) {
mCalibData->imagePoints.erase(mCalibData->imagePoints.begin() + worstElemIndex); mCalibData->imagePoints.erase(mCalibData->imagePoints.begin() + worstElemIndex);

2
apps/interactive-calibration/frameProcessor.cpp
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@ -318,7 +318,7 @@ cv::Mat CalibProcessor::processFrame(const cv::Mat &frame)
saveFrameData(); saveFrameData();
bool isFrameBad = checkLastFrame(); bool isFrameBad = checkLastFrame();
if (!isFrameBad) { if (!isFrameBad) {
std::string displayMessage = cv::format("Frame # %d captured", std::max(mCalibData->imagePoints.size(), std::string displayMessage = cv::format("Frame # %zu captured", std::max(mCalibData->imagePoints.size(),
mCalibData->allCharucoCorners.size())); mCalibData->allCharucoCorners.size()));
if(!showOverlayMessage(displayMessage)) if(!showOverlayMessage(displayMessage))
showCaptureMessage(frame, displayMessage); showCaptureMessage(frame, displayMessage);

19
modules/core/include/opencv2/core/operations.hpp
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@ -51,6 +51,12 @@
#include <cstdio> #include <cstdio>
#if defined(__GNUC__) || defined(__clang__) // at least GCC 3.1+, clang 3.5+
# define CV_FORMAT_PRINTF(string_idx, first_to_check) __attribute__ ((format (printf, string_idx, first_to_check)))
#else
# define CV_FORMAT_PRINTF(A, B)
#endif
//! @cond IGNORED //! @cond IGNORED
namespace cv namespace cv
@ -386,8 +392,19 @@ template<typename _Tp> static inline _Tp randu()
The function acts like sprintf but forms and returns an STL string. It can be used to form an error The function acts like sprintf but forms and returns an STL string. It can be used to form an error
message in the Exception constructor. message in the Exception constructor.
@param fmt printf-compatible formatting specifiers. @param fmt printf-compatible formatting specifiers.
**Note**:
|Type|Specifier|
|-|-|
|`const char*`|`%s`|
|`char`|`%c`|
|`float` / `double`|`%f`,`%g`|
|`int`, `long`, `long long`|`%d`, `%ld`, ``%lld`|
|`unsigned`, `unsigned long`, `unsigned long long`|`%u`, `%lu`, `%llu`|
|`uint64` -> `uintmax_t`, `int64` -> `intmax_t`|`%ju`, `%jd`|
|`size_t`|`%zu`|
*/ */
CV_EXPORTS String format( const char* fmt, ... ); CV_EXPORTS String format( const char* fmt, ... ) CV_FORMAT_PRINTF(1, 2);
///////////////////////////////// Formatted output of cv::Mat ///////////////////////////////// ///////////////////////////////// Formatted output of cv::Mat /////////////////////////////////

10
modules/core/src/channels.cpp
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@ -237,11 +237,11 @@ static bool ocl_mixChannels(InputArrayOfArrays _src, InputOutputArrayOfArrays _d
dstargs[i] = dst[dst_idx]; dstargs[i] = dst[dst_idx];
dstargs[i].offset += dst_cnidx * esz; dstargs[i].offset += dst_cnidx * esz;
declsrc += format("DECLARE_INPUT_MAT(%d)", i); declsrc += format("DECLARE_INPUT_MAT(%zu)", i);
decldst += format("DECLARE_OUTPUT_MAT(%d)", i); decldst += format("DECLARE_OUTPUT_MAT(%zu)", i);
indexdecl += format("DECLARE_INDEX(%d)", i); indexdecl += format("DECLARE_INDEX(%zu)", i);
declproc += format("PROCESS_ELEM(%d)", i); declproc += format("PROCESS_ELEM(%zu)", i);
declcn += format(" -D scn%d=%d -D dcn%d=%d", i, src[src_idx].channels(), i, dst[dst_idx].channels()); declcn += format(" -D scn%zu=%d -D dcn%zu=%d", i, src[src_idx].channels(), i, dst[dst_idx].channels());
} }
ocl::Kernel k("mixChannels", ocl::core::mixchannels_oclsrc, ocl::Kernel k("mixChannels", ocl::core::mixchannels_oclsrc,

6
modules/core/src/lda.cpp
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@ -184,7 +184,7 @@ Mat LDA::subspaceProject(InputArray _W, InputArray _mean, InputArray _src) {
} }
// make sure mean is correct if not empty // make sure mean is correct if not empty
if(!mean.empty() && (mean.total() != (size_t) d)) { if(!mean.empty() && (mean.total() != (size_t) d)) {
String error_message = format("Wrong mean shape for the given data matrix. Expected %d, but was %d.", d, mean.total()); String error_message = format("Wrong mean shape for the given data matrix. Expected %d, but was %zu.", d, mean.total());
CV_Error(Error::StsBadArg, error_message); CV_Error(Error::StsBadArg, error_message);
} }
// create temporary matrices // create temporary matrices
@ -222,7 +222,7 @@ Mat LDA::subspaceReconstruct(InputArray _W, InputArray _mean, InputArray _src)
} }
// make sure mean is correct if not empty // make sure mean is correct if not empty
if(!mean.empty() && (mean.total() != (size_t) W.rows)) { if(!mean.empty() && (mean.total() != (size_t) W.rows)) {
String error_message = format("Wrong mean shape for the given eigenvector matrix. Expected %d, but was %d.", W.cols, mean.total()); String error_message = format("Wrong mean shape for the given eigenvector matrix. Expected %d, but was %zu.", W.cols, mean.total());
CV_Error(Error::StsBadArg, error_message); CV_Error(Error::StsBadArg, error_message);
} }
// initialize temporary matrices // initialize temporary matrices
@ -1076,7 +1076,7 @@ void LDA::lda(InputArrayOfArrays _src, InputArray _lbls) {
} }
// throw error if less labels, than samples // throw error if less labels, than samples
if (labels.size() != static_cast<size_t>(N)) { if (labels.size() != static_cast<size_t>(N)) {
String error_message = format("The number of samples must equal the number of labels. Given %d labels, %d samples. ", labels.size(), N); String error_message = format("The number of samples must equal the number of labels. Given %zu labels, %d samples. ", labels.size(), N);
CV_Error(Error::StsBadArg, error_message); CV_Error(Error::StsBadArg, error_message);
} }
// warn if within-classes scatter matrix becomes singular // warn if within-classes scatter matrix becomes singular

2
modules/core/src/matrix_operations.cpp
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@ -892,7 +892,7 @@ static bool ocl_reduce(InputArray _src, OutputArray _dst,
tileHeight = min(tileHeight, defDev.localMemSize() / buf_cols / CV_ELEM_SIZE(CV_MAKETYPE(wdepth, cn)) / maxItemInGroupCount); tileHeight = min(tileHeight, defDev.localMemSize() / buf_cols / CV_ELEM_SIZE(CV_MAKETYPE(wdepth, cn)) / maxItemInGroupCount);
} }
char cvt[3][40]; char cvt[3][40];
cv::String build_opt = format("-D OP_REDUCE_PRE -D BUF_COLS=%d -D TILE_HEIGHT=%d -D %s -D dim=1" cv::String build_opt = format("-D OP_REDUCE_PRE -D BUF_COLS=%d -D TILE_HEIGHT=%zu -D %s -D dim=1"
" -D cn=%d -D ddepth=%d" " -D cn=%d -D ddepth=%d"
" -D srcT=%s -D bufT=%s -D dstT=%s" " -D srcT=%s -D bufT=%s -D dstT=%s"
" -D convertToWT=%s -D convertToBufT=%s -D convertToDT=%s%s", " -D convertToWT=%s -D convertToBufT=%s -D convertToDT=%s%s",

6
modules/core/src/ocl.cpp
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@ -3104,9 +3104,9 @@ bool Kernel::Impl::run(int dims, size_t globalsize[], size_t localsize[],
if (retval != CL_SUCCESS) if (retval != CL_SUCCESS)
#endif #endif
{ {
cv::String msg = cv::format("clEnqueueNDRangeKernel('%s', dims=%d, globalsize=%dx%dx%d, localsize=%s) sync=%s", name.c_str(), (int)dims, cv::String msg = cv::format("clEnqueueNDRangeKernel('%s', dims=%d, globalsize=%zux%zux%zu, localsize=%s) sync=%s", name.c_str(), (int)dims,
globalsize[0], (dims > 1 ? globalsize[1] : 1), (dims > 2 ? globalsize[2] : 1), globalsize[0], (dims > 1 ? globalsize[1] : 1), (dims > 2 ? globalsize[2] : 1),
(localsize ? cv::format("%dx%dx%d", localsize[0], (dims > 1 ? localsize[1] : 1), (dims > 2 ? localsize[2] : 1)) : cv::String("NULL")).c_str(), (localsize ? cv::format("%zux%zux%zu", localsize[0], (dims > 1 ? localsize[1] : 1), (dims > 2 ? localsize[2] : 1)) : cv::String("NULL")).c_str(),
sync ? "true" : "false" sync ? "true" : "false"
); );
if (retval != CL_SUCCESS) if (retval != CL_SUCCESS)
@ -3317,7 +3317,7 @@ struct ProgramSource::Impl
default: default:
CV_Error(Error::StsInternal, "Internal error"); CV_Error(Error::StsInternal, "Internal error");
} }
sourceHash_ = cv::format("%08llx", hash); sourceHash_ = cv::format("%08jx", (uintmax_t)hash);
isHashUpdated = true; isHashUpdated = true;
} }

10
modules/core/test/test_io.cpp
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@ -584,29 +584,29 @@ TEST(Core_InputOutput, FileStorageSpaces)
const int valueCount = 5; const int valueCount = 5;
std::string values[5] = { "", " ", " ", " a", " some string" }; std::string values[5] = { "", " ", " ", " a", " some string" };
for (size_t i = 0; i < valueCount; i++) { for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(f << cv::format("key%d", i) << values[i]); EXPECT_NO_THROW(f << cv::format("key%zu", i) << values[i]);
} }
cv::FileStorage f2(f.releaseAndGetString(), cv::FileStorage::READ | cv::FileStorage::MEMORY); cv::FileStorage f2(f.releaseAndGetString(), cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::string valuesRead[valueCount]; std::string valuesRead[valueCount];
for (size_t i = 0; i < valueCount; i++) { for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(f2[cv::format("key%d", i)] >> valuesRead[i]); EXPECT_NO_THROW(f2[cv::format("key%zu", i)] >> valuesRead[i]);
ASSERT_STREQ(values[i].c_str(), valuesRead[i].c_str()); ASSERT_STREQ(values[i].c_str(), valuesRead[i].c_str());
} }
std::string fileName = cv::tempfile(".xml"); std::string fileName = cv::tempfile(".xml");
cv::FileStorage g1(fileName, cv::FileStorage::WRITE); cv::FileStorage g1(fileName, cv::FileStorage::WRITE);
for (size_t i = 0; i < 2; i++) { for (size_t i = 0; i < 2; i++) {
EXPECT_NO_THROW(g1 << cv::format("key%d", i) << values[i]); EXPECT_NO_THROW(g1 << cv::format("key%zu", i) << values[i]);
} }
g1.release(); g1.release();
cv::FileStorage g2(fileName, cv::FileStorage::APPEND); cv::FileStorage g2(fileName, cv::FileStorage::APPEND);
for (size_t i = 2; i < valueCount; i++) { for (size_t i = 2; i < valueCount; i++) {
EXPECT_NO_THROW(g2 << cv::format("key%d", i) << values[i]); EXPECT_NO_THROW(g2 << cv::format("key%zu", i) << values[i]);
} }
g2.release(); g2.release();
cv::FileStorage g3(fileName, cv::FileStorage::READ); cv::FileStorage g3(fileName, cv::FileStorage::READ);
std::string valuesReadAppend[valueCount]; std::string valuesReadAppend[valueCount];
for (size_t i = 0; i < valueCount; i++) { for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(g3[cv::format("key%d", i)] >> valuesReadAppend[i]); EXPECT_NO_THROW(g3[cv::format("key%zu", i)] >> valuesReadAppend[i]);
ASSERT_STREQ(values[i].c_str(), valuesReadAppend[i].c_str()); ASSERT_STREQ(values[i].c_str(), valuesReadAppend[i].c_str());
} }
g3.release(); g3.release();

2
modules/dnn/src/dnn.cpp
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@ -2347,7 +2347,7 @@ struct Net::Impl
LayerData &ld = layers[pin.lid]; LayerData &ld = layers[pin.lid];
if ((size_t)pin.oid >= ld.outputBlobs.size()) if ((size_t)pin.oid >= ld.outputBlobs.size())
{ {
CV_Error(Error::StsOutOfRange, format("Layer \"%s\" produce only %d outputs, " CV_Error(Error::StsOutOfRange, format("Layer \"%s\" produce only %zu outputs, "
"the #%d was requested", ld.name.c_str(), "the #%d was requested", ld.name.c_str(),
ld.outputBlobs.size(), pin.oid)); ld.outputBlobs.size(), pin.oid));
} }

2
modules/dnn/src/layers/permute_layer.cpp
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@ -88,7 +88,7 @@ public:
{ {
CV_Error(Error::StsBadArg, CV_Error(Error::StsBadArg,
format("Orders of dimensions in Permute layer parameter" format("Orders of dimensions in Permute layer parameter"
"must be in [0...%d]", _numAxes - 1)); "must be in [0...%zu]", _numAxes - 1));
} }
if (std::find(_order.begin(), _order.end(), currentOrder) != _order.end()) if (std::find(_order.begin(), _order.end(), currentOrder) != _order.end())
{ {

6
modules/dnn/src/torch/THDiskFile.cpp
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@ -69,7 +69,7 @@ static size_t fread__(void *ptr, size_t size, size_t nitems, FILE *stream)
{ \ { \
dfself->file.hasError = 1; /* shouldn't we put hasError to 0 all the time ? */ \ dfself->file.hasError = 1; /* shouldn't we put hasError to 0 all the time ? */ \
if(!dfself->file.isQuiet) \ if(!dfself->file.isQuiet) \
THError("read error: read %d blocks instead of %d", nread, n); \ THError("read error: read %ld blocks instead of %ld", nread, n);\
} \ } \
\ \
return nread; \ return nread; \
@ -120,7 +120,7 @@ static void THDiskFile_seek(THFile *self, long position)
{ {
dfself->file.hasError = 1; dfself->file.hasError = 1;
if(!dfself->file.isQuiet) if(!dfself->file.isQuiet)
THError("unable to seek at position %d", position); THError("unable to seek at position %ld", position);
} }
} }
@ -351,7 +351,7 @@ static long THDiskFile_readLong(THFile *self, int64 *data, long n)
{ {
dfself->file.hasError = 1; /* shouldn't we put hasError to 0 all the time ? */ dfself->file.hasError = 1; /* shouldn't we put hasError to 0 all the time ? */
if(!dfself->file.isQuiet) if(!dfself->file.isQuiet)
THError("read error: read %d blocks instead of %d", nread, n); THError("read error: read %ld blocks instead of %ld", nread, n);
} }
return nread; return nread;

2
modules/imgproc/src/featureselect.cpp
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@ -126,7 +126,7 @@ static bool ocl_goodFeaturesToTrack( InputArray _image, OutputArray _corners,
return false; return false;
ocl::Kernel k2("maxEigenValTask", ocl::imgproc::gftt_oclsrc, ocl::Kernel k2("maxEigenValTask", ocl::imgproc::gftt_oclsrc,
format("-D OP_MAX_EIGEN_VAL -D WGS=%d -D WGS2_ALIGNED=%d -D groupnum=%d", format("-D OP_MAX_EIGEN_VAL -D WGS=%zu -D WGS2_ALIGNED=%d -D groupnum=%d",
wgs, wgs2_aligned, dbsize)); wgs, wgs2_aligned, dbsize));
if (k2.empty()) if (k2.empty())
return false; return false;

4
modules/imgproc/src/histogram.cpp
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@ -1123,7 +1123,7 @@ static bool ocl_calcHist1(InputArray _src, OutputArray _hist, int ddepth = CV_32
int kercn = dev.isAMD() && use16 ? 16 : std::min(4, ocl::predictOptimalVectorWidth(_src)); int kercn = dev.isAMD() && use16 ? 16 : std::min(4, ocl::predictOptimalVectorWidth(_src));
ocl::Kernel k1("calculate_histogram", ocl::imgproc::histogram_oclsrc, ocl::Kernel k1("calculate_histogram", ocl::imgproc::histogram_oclsrc,
format("-D BINS=%d -D HISTS_COUNT=%d -D WGS=%d -D kercn=%d -D T=%s%s", format("-D BINS=%d -D HISTS_COUNT=%d -D WGS=%zu -D kercn=%d -D T=%s%s",
BINS, compunits, wgs, kercn, BINS, compunits, wgs, kercn,
kercn == 4 ? "int" : ocl::typeToStr(CV_8UC(kercn)), kercn == 4 ? "int" : ocl::typeToStr(CV_8UC(kercn)),
_src.isContinuous() ? " -D HAVE_SRC_CONT" : "")); _src.isContinuous() ? " -D HAVE_SRC_CONT" : ""));
@ -3253,7 +3253,7 @@ static bool ocl_equalizeHist(InputArray _src, OutputArray _dst)
int kercn = dev.isAMD() && use16 ? 16 : std::min(4, ocl::predictOptimalVectorWidth(_src)); int kercn = dev.isAMD() && use16 ? 16 : std::min(4, ocl::predictOptimalVectorWidth(_src));
ocl::Kernel k1("calculate_histogram", ocl::imgproc::histogram_oclsrc, ocl::Kernel k1("calculate_histogram", ocl::imgproc::histogram_oclsrc,
format("-D BINS=%d -D HISTS_COUNT=%d -D WGS=%d -D kercn=%d -D T=%s%s", format("-D BINS=%d -D HISTS_COUNT=%d -D WGS=%zu -D kercn=%d -D T=%s%s",
BINS, compunits, wgs, kercn, BINS, compunits, wgs, kercn,
kercn == 4 ? "int" : ocl::typeToStr(CV_8UC(kercn)), kercn == 4 ? "int" : ocl::typeToStr(CV_8UC(kercn)),
_src.isContinuous() ? " -D HAVE_SRC_CONT" : "")); _src.isContinuous() ? " -D HAVE_SRC_CONT" : ""));

12
modules/objdetect/src/hog.cpp
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@ -1328,7 +1328,7 @@ static bool ocl_compute_hists(int nbins, int block_stride_x, int block_stride_y,
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("compute_hists_lut_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("compute_hists_lut_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;
@ -1401,7 +1401,7 @@ static bool ocl_normalize_hists(int nbins, int block_stride_x, int block_stride_
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("normalize_hists_36_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("normalize_hists_36_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;
@ -1420,7 +1420,7 @@ static bool ocl_normalize_hists(int nbins, int block_stride_x, int block_stride_
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("normalize_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("normalize_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;
@ -1870,7 +1870,7 @@ static bool ocl_classify_hists(int win_height, int win_width, int block_stride_y
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("classify_hists_180_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("classify_hists_180_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;
@ -1886,7 +1886,7 @@ static bool ocl_classify_hists(int win_height, int win_width, int block_stride_y
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("classify_hists_252_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("classify_hists_252_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;
@ -1902,7 +1902,7 @@ static bool ocl_classify_hists(int win_height, int win_width, int block_stride_y
if(is_cpu) if(is_cpu)
opts = "-D CPU "; opts = "-D CPU ";
else else
opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); opts = cv::format("-D WAVE_SIZE=%zu", k.preferedWorkGroupSizeMultiple());
k.create("classify_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); k.create("classify_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts);
if(k.empty()) if(k.empty())
return false; return false;

5
modules/photo/src/fast_nlmeans_denoising_opencl.hpp
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@ -95,12 +95,13 @@ static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, const fl
int almostTemplateWindowSizeSqBinShift = -1; int almostTemplateWindowSizeSqBinShift = -1;
char buf[4][40]; char buf[4][40];
const unsigned psz = (depth == CV_8U ? sizeof(uchar) : sizeof(ushort)) * (cn == 3 ? 4 : cn);
String opts = format("-D OP_CALC_FASTNLMEANS -D TEMPLATE_SIZE=%d -D SEARCH_SIZE=%d" String opts = format("-D OP_CALC_FASTNLMEANS -D TEMPLATE_SIZE=%d -D SEARCH_SIZE=%d"
" -D pixel_t=%s -D int_t=%s -D wlut_t=%s" " -D pixel_t=%s -D int_t=%s -D wlut_t=%s"
" -D weight_t=%s -D convert_weight_t=%s -D sum_t=%s -D convert_sum_t=%s" " -D weight_t=%s -D convert_weight_t=%s -D sum_t=%s -D convert_sum_t=%s"
" -D BLOCK_COLS=%d -D BLOCK_ROWS=%d" " -D BLOCK_COLS=%d -D BLOCK_ROWS=%d"
" -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d" " -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d"
" -D convert_int_t=%s -D cn=%d -D psz=%d -D convert_pixel_t=%s%s", " -D convert_int_t=%s -D cn=%d -D psz=%u -D convert_pixel_t=%s%s",
templateWindowSize, searchWindowSize, templateWindowSize, searchWindowSize,
ocl::typeToStr(type), ocl::typeToStr(CV_32SC(cn)), ocl::typeToStr(type), ocl::typeToStr(CV_32SC(cn)),
ocl::typeToStr(CV_32SC(hn)), ocl::typeToStr(CV_32SC(hn)),
@ -115,7 +116,7 @@ static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, const fl
BLOCK_COLS, BLOCK_ROWS, BLOCK_COLS, BLOCK_ROWS,
ctaSize, templateWindowHalfWize, searchWindowHalfSize, ctaSize, templateWindowHalfWize, searchWindowHalfSize,
ocl::convertTypeStr(depth, CV_32S, cn, buf[2]), cn, ocl::convertTypeStr(depth, CV_32S, cn, buf[2]), cn,
(depth == CV_8U ? sizeof(uchar) : sizeof(ushort)) * (cn == 3 ? 4 : cn), psz,
ocl::convertTypeStr(CV_32S, depth, cn, buf[3]), ocl::convertTypeStr(CV_32S, depth, cn, buf[3]),
normType == NORM_L1 ? " -D ABS" : ""); normType == NORM_L1 ? " -D ABS" : "");

2
modules/videoio/src/container_avi.cpp
Unescape View File

@ -22,7 +22,7 @@ inline D safe_int_cast(S val, const char * msg = 0)
if (!in_range_r || !in_range_l) if (!in_range_r || !in_range_l)
{ {
if (!msg) if (!msg)
CV_Error_(Error::StsOutOfRange, ("Can not convert integer values (%s -> %s), value 0x%llx is out of range", typeid(S).name(), typeid(D).name(), val)); CV_Error_(Error::StsOutOfRange, ("Can not convert integer values (%s -> %s), value 0x%jx is out of range", typeid(S).name(), typeid(D).name(), (uintmax_t)val));
else else
CV_Error(Error::StsOutOfRange, msg); CV_Error(Error::StsOutOfRange, msg);
} }

4
samples/dnn/segmentation.cpp
Unescape View File

@ -186,7 +186,7 @@ void colorizeSegmentation(const Mat &score, Mat &segm)
else if (chns != (int)colors.size()) else if (chns != (int)colors.size())
{ {
CV_Error(Error::StsError, format("Number of output classes does not match " CV_Error(Error::StsError, format("Number of output classes does not match "
"number of colors (%d != %d)", chns, colors.size())); "number of colors (%d != %zu)", chns, colors.size()));
} }
Mat maxCl = Mat::zeros(rows, cols, CV_8UC1); Mat maxCl = Mat::zeros(rows, cols, CV_8UC1);
@ -231,7 +231,7 @@ void showLegend()
if ((int)colors.size() != numClasses) if ((int)colors.size() != numClasses)
{ {
CV_Error(Error::StsError, format("Number of output classes does not match " CV_Error(Error::StsError, format("Number of output classes does not match "
"number of labels (%d != %d)", colors.size(), classes.size())); "number of labels (%zu != %zu)", colors.size(), classes.size()));
} }
legend.create(kBlockHeight * numClasses, 200, CV_8UC3); legend.create(kBlockHeight * numClasses, 200, CV_8UC3);
for (int i = 0; i < numClasses; i++) for (int i = 0; i < numClasses; i++)

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