Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Merge remote-tracking branch 'upstream/3.4' into merge-3.4

Browse Source
pull/15237/head
Alexander Alekhin 6 years ago
parent 0757a51e2b 90ccd2f37c
commit 174b4ce29d
41 changed files with 418 additions and 297 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 2
      3rdparty/carotene/hal/tegra_hal.hpp
  2. 2
      CMakeLists.txt
  3. 10
      cmake/templates/dllmain.cpp.in
  4. 2
      doc/js_tutorials/js_setup/js_setup/js_setup.markdown
  5. 7
      modules/core/misc/java/src/java/core+Mat.java
  6. 4
      modules/core/src/glob.cpp
  7. 6
      modules/core/src/mean.dispatch.cpp
  8. 15
      modules/core/src/utils/datafile.cpp
  9. 207
      modules/dnn/misc/caffe/opencv-caffe.pb.cc
  10. 174
      modules/dnn/misc/caffe/opencv-caffe.pb.h
  11. 9
      modules/dnn/misc/face_detector_accuracy.py
  12. 4
      modules/dnn/misc/quantize_face_detector.py
  13. 4
      modules/dnn/perf/perf_net.cpp
  14. 4
      modules/dnn/src/caffe/opencv-caffe.proto
  15. 3
      modules/dnn/src/layers/detection_output_layer.cpp
  16. 2
      modules/dnn/src/layers/elementwise_layers.cpp
  17. 64
      modules/dnn/src/layers/prior_box_layer.cpp
  18. 41
      modules/dnn/src/onnx/onnx_importer.cpp
  19. 10
      modules/dnn/test/test_backends.cpp
  20. 4
      modules/dnn/test/test_caffe_importer.cpp
  21. 2
      modules/dnn/test/test_darknet_importer.cpp
  22. 23
      modules/dnn/test/test_layers.cpp
  23. 15
      modules/dnn/test/test_onnx_importer.cpp
  24. 12
      modules/dnn/test/test_tf_importer.cpp
  25. 4
      modules/imgcodecs/src/exif.cpp
  26. 5
      modules/imgcodecs/src/exif.hpp
  27. 2
      modules/imgproc/perf/perf_cvt_color.cpp
  28. 4
      modules/imgproc/src/box_filter.dispatch.cpp
  29. 10
      modules/imgproc/src/demosaicing.cpp
  30. 6
      modules/imgproc/src/filter.dispatch.cpp
  31. 4
      modules/imgproc/src/median_blur.dispatch.cpp
  32. 4
      modules/imgproc/src/smooth.dispatch.cpp
  33. 4
      modules/videoio/src/cap_v4l.cpp
  34. 4
      modules/videoio/test/test_video_io.cpp
  35. 4
      platforms/wince/arm-wince-headless-overrides.cmake
  36. 8
      platforms/wince/readme.md
  37. 1
      samples/dnn/face_detector/deploy.prototxt
  38. 10
      samples/dnn/face_detector/opencv_face_detector.pbtxt
  39. 5
      samples/dnn/face_detector/test.prototxt
  40. 4
      samples/dnn/face_detector/train.prototxt
  41. 10
      samples/dnn/tf_text_graph_ssd.py

2
3rdparty/carotene/hal/tegra_hal.hpp vendored
Unescape View File

@ -1127,6 +1127,7 @@ inline int TEGRA_FILTERINIT(cvhalFilter2D **context, uchar *kernel_data, size_t
{
std::memcpy(ctx->kernel_data + kernel_width * j, kernel_data + kernel_step * j, kernel_width * sizeof(int16_t));
}
break;
default:
delete[] ctx->kernel_data;
delete ctx;
@ -1243,6 +1244,7 @@ inline int TEGRA_SEPFILTERINIT(cvhalFilter2D **context, int src_type, int dst_ty
ctx->kernely_data[0]=((int16_t*)kernely_data)[0];
ctx->kernely_data[1]=((int16_t*)kernely_data)[1];
ctx->kernely_data[2]=((int16_t*)kernely_data)[2];
break;
default:
delete ctx;
return CV_HAL_ERROR_NOT_IMPLEMENTED;

2
CMakeLists.txt
Unescape View File

@ -465,7 +465,7 @@ OCV_OPTION(INSTALL_TESTS "Install accuracy and performance test binar
# OpenCV build options
# ===================================================
OCV_OPTION(ENABLE_CCACHE "Use ccache" (UNIX AND NOT IOS AND (CMAKE_GENERATOR MATCHES "Makefile" OR CMAKE_GENERATOR MATCHES "Ninja")) )
OCV_OPTION(ENABLE_PRECOMPILED_HEADERS "Use precompiled headers" ON IF (MSVC OR (NOT IOS AND NOT CMAKE_CROSSCOMPILING) ) )
OCV_OPTION(ENABLE_PRECOMPILED_HEADERS "Use precompiled headers" MSVC IF (MSVC OR (NOT IOS AND NOT CMAKE_CROSSCOMPILING) ) )
OCV_OPTION(ENABLE_SOLUTION_FOLDERS "Solution folder in Visual Studio or in other IDEs" (MSVC_IDE OR CMAKE_GENERATOR MATCHES Xcode) )
OCV_OPTION(ENABLE_PROFILING "Enable profiling in the GCC compiler (Add flags: -g -pg)" OFF IF CV_GCC )
OCV_OPTION(ENABLE_COVERAGE "Enable coverage collection with GCov" OFF IF CV_GCC )

10
cmake/templates/dllmain.cpp.in
Unescape View File

@ -18,11 +18,17 @@ namespace cv {
extern __declspec(dllimport) bool __termination; // Details: #12750
}
#ifdef _WIN32_WCE
#define DLL_MAIN_ARG0 HANDLE
#else
#define DLL_MAIN_ARG0 HINSTANCE
#endif
extern "C"
BOOL WINAPI DllMain(HINSTANCE, DWORD fdwReason, LPVOID lpReserved);
BOOL WINAPI DllMain(DLL_MAIN_ARG0, DWORD fdwReason, LPVOID lpReserved);
extern "C"
BOOL WINAPI DllMain(HINSTANCE, DWORD fdwReason, LPVOID lpReserved)
BOOL WINAPI DllMain(DLL_MAIN_ARG0, DWORD fdwReason, LPVOID lpReserved)
{
if (fdwReason == DLL_THREAD_DETACH || fdwReason == DLL_PROCESS_DETACH)
{

2
doc/js_tutorials/js_setup/js_setup/js_setup.markdown
Unescape View File

@ -127,4 +127,4 @@ docker run --rm --workdir /code -v "$(get-location):/code" "trzeci/emscripten:la
@endcode
@note
The example uses latest version of [trzeci/emscripten](https://hub.docker.com/r/trzeci/emscripten) docker container. At this time, the latest version works fine and is `trzeci/emscripten:sdk-tag-1.38.32-64bit`
The example uses latest version of [trzeci/emscripten](https://hub.docker.com/r/trzeci/emscripten) docker container. At this time, the latest version works fine and is `trzeci/emscripten:sdk-tag-1.38.32-64bit`

7
modules/core/misc/java/src/java/core+Mat.java
Unescape View File

@ -735,8 +735,11 @@ public class Mat {
// javadoc:Mat::toString()
@Override
public String toString() {
return "Mat [ " +
rows() + "*" + cols() + "*" + CvType.typeToString(type()) +
String _dims = (dims() > 0) ? "" : "-1*-1*";
for (int i=0; i<dims(); i++) {
_dims += size(i) + "*";
}
return "Mat [ " + _dims + CvType.typeToString(type()) +
", isCont=" + isContinuous() + ", isSubmat=" + isSubmatrix() +
", nativeObj=0x" + Long.toHexString(nativeObj) +
", dataAddr=0x" + Long.toHexString(dataAddr()) +

4
modules/core/src/glob.cpp
Unescape View File

@ -139,7 +139,7 @@ const char dir_separators[] = "/";
static bool isDir(const cv::String& path, DIR* dir)
{
#if defined _WIN32 || defined WINCE
#if defined _WIN32 || defined _WIN32_WCE
DWORD attributes;
BOOL status = TRUE;
if (dir)
@ -147,7 +147,7 @@ static bool isDir(const cv::String& path, DIR* dir)
else
{
WIN32_FILE_ATTRIBUTE_DATA all_attrs;
#ifdef WINRT
#if defined WINRT || defined _WIN32_WCE
wchar_t wpath[MAX_PATH];
size_t copied = mbstowcs(wpath, path.c_str(), MAX_PATH);
CV_Assert((copied != MAX_PATH) && (copied != (size_t)-1));

6
modules/core/src/mean.dispatch.cpp
Unescape View File

@ -17,6 +17,12 @@
#include "mean.simd.hpp"
#include "mean.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
#undef HAVE_IPP
#undef CV_IPP_RUN_FAST
#define CV_IPP_RUN_FAST(f, ...)
#undef CV_IPP_RUN
#define CV_IPP_RUN(c, f, ...)
namespace cv {
#if defined HAVE_IPP

15
modules/core/src/utils/datafile.cpp
Unescape View File

@ -115,13 +115,20 @@ static cv::String getModuleLocation(const void* addr)
#endif
if (m)
{
char path[MAX_PATH];
const size_t path_size = sizeof(path)/sizeof(*path);
size_t sz = GetModuleFileNameA(m, path, path_size); // no unicode support
TCHAR path[MAX_PATH];
const size_t path_size = sizeof(path) / sizeof(*path);
size_t sz = GetModuleFileName(m, path, path_size);
if (sz > 0 && sz < path_size)
{
path[sz] = '\0';
path[sz] = TCHAR('\0');
#ifdef _UNICODE
char char_path[MAX_PATH];
size_t copied = wcstombs(char_path, path, MAX_PATH);
CV_Assert((copied != MAX_PATH) && (copied != (size_t)-1));
return cv::String(char_path);
#else
return cv::String(path);
#endif
}
}
#elif defined(__linux__)

207
modules/dnn/misc/caffe/opencv-caffe.pb.cc
Unescape View File

@ -2092,19 +2092,19 @@ const ::google::protobuf::uint32 TableStruct::offsets[] GOOGLE_PROTOBUF_ATTRIBUT
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::PriorBoxParameter, offset_w_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::PriorBoxParameter, width_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::PriorBoxParameter, height_),
0,
1,
~0u,
8,
9,
~0u,
~0u,
6,
7,
~0u,
0,
1,
2,
3,
4,
5,
6,
7,
10,
8,
~0u,
~0u,
~0u,
@ -3528,8 +3528,8 @@ void AddDescriptorsImpl() {
"al\030\001 \001(\010:\004true\0223\n\014scale_filler\030\002 \001(\0132\035.o"
"pencv_caffe.FillerParameter\022\034\n\016channel_s"
"hared\030\003 \001(\010:\004true\022\022\n\003eps\030\004 \001(\002:\0051e-10\"\346\002"
"\n\021PriorBoxParameter\022\020\n\010min_size\030\001 \001(\002\022\020\n"
"\010max_size\030\002 \001(\002\022\024\n\014aspect_ratio\030\003 \003(\002\022\022\n"
"\n\021PriorBoxParameter\022\020\n\010min_size\030\001 \003(\002\022\020\n"
"\010max_size\030\002 \003(\002\022\024\n\014aspect_ratio\030\003 \003(\002\022\022\n"
"\004flip\030\004 \001(\010:\004true\022\022\n\004clip\030\005 \001(\010:\004true\022\020\n"
"\010variance\030\006 \003(\002\022\020\n\010img_size\030\007 \001(\r\022\r\n\005img"
"_h\030\010 \001(\r\022\r\n\005img_w\030\t \001(\r\022\014\n\004step\030\n \001(\002\022\016\n"
@ -6600,6 +6600,8 @@ PriorBoxParameter::PriorBoxParameter(const PriorBoxParameter& from)
_internal_metadata_(NULL),
_has_bits_(from._has_bits_),
_cached_size_(0),
min_size_(from.min_size_),
max_size_(from.max_size_),
aspect_ratio_(from.aspect_ratio_),
variance_(from.variance_),
offset_h_(from.offset_h_),
@ -6607,17 +6609,17 @@ PriorBoxParameter::PriorBoxParameter(const PriorBoxParameter& from)
width_(from.width_),
height_(from.height_) {
_internal_metadata_.MergeFrom(from._internal_metadata_);
::memcpy(&min_size_, &from.min_size_,
::memcpy(&img_size_, &from.img_size_,
static_cast<size_t>(reinterpret_cast<char*>(&offset_) -
reinterpret_cast<char*>(&min_size_)) + sizeof(offset_));
reinterpret_cast<char*>(&img_size_)) + sizeof(offset_));
// @@protoc_insertion_point(copy_constructor:opencv_caffe.PriorBoxParameter)
}
void PriorBoxParameter::SharedCtor() {
_cached_size_ = 0;
::memset(&min_size_, 0, static_cast<size_t>(
::memset(&img_size_, 0, static_cast<size_t>(
reinterpret_cast<char*>(&step_w_) -
reinterpret_cast<char*>(&min_size_)) + sizeof(step_w_));
reinterpret_cast<char*>(&img_size_)) + sizeof(step_w_));
flip_ = true;
clip_ = true;
offset_ = 0.5f;
@ -6660,6 +6662,8 @@ void PriorBoxParameter::Clear() {
// Prevent compiler warnings about cached_has_bits being unused
(void) cached_has_bits;
min_size_.Clear();
max_size_.Clear();
aspect_ratio_.Clear();
variance_.Clear();
offset_h_.Clear();
@ -6668,15 +6672,13 @@ void PriorBoxParameter::Clear() {
height_.Clear();
cached_has_bits = _has_bits_[0];
if (cached_has_bits & 255u) {
::memset(&min_size_, 0, static_cast<size_t>(
::memset(&img_size_, 0, static_cast<size_t>(
reinterpret_cast<char*>(&step_w_) -
reinterpret_cast<char*>(&min_size_)) + sizeof(step_w_));
}
if (cached_has_bits & 1792u) {
reinterpret_cast<char*>(&img_size_)) + sizeof(step_w_));
flip_ = true;
clip_ = true;
offset_ = 0.5f;
}
offset_ = 0.5f;
_has_bits_.Clear();
_internal_metadata_.Clear();
}
@ -6691,28 +6693,38 @@ bool PriorBoxParameter::MergePartialFromCodedStream(
tag = p.first;
if (!p.second) goto handle_unusual;
switch (::google::protobuf::internal::WireFormatLite::GetTagFieldNumber(tag)) {
// optional float min_size = 1;
// repeated float min_size = 1;
case 1: {
if (static_cast< ::google::protobuf::uint8>(tag) ==
static_cast< ::google::protobuf::uint8>(13u /* 13 & 0xFF */)) {
set_has_min_size();
DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
DO_((::google::protobuf::internal::WireFormatLite::ReadRepeatedPrimitive<
float, ::google::protobuf::internal::WireFormatLite::TYPE_FLOAT>(
input, &min_size_)));
1, 13u, input, this->mutable_min_size())));
} else if (
static_cast< ::google::protobuf::uint8>(tag) ==
static_cast< ::google::protobuf::uint8>(10u /* 10 & 0xFF */)) {
DO_((::google::protobuf::internal::WireFormatLite::ReadPackedPrimitiveNoInline<
float, ::google::protobuf::internal::WireFormatLite::TYPE_FLOAT>(
input, this->mutable_min_size())));
} else {
goto handle_unusual;
}
break;
}
// optional float max_size = 2;
// repeated float max_size = 2;
case 2: {
if (static_cast< ::google::protobuf::uint8>(tag) ==
static_cast< ::google::protobuf::uint8>(21u /* 21 & 0xFF */)) {
set_has_max_size();
DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
DO_((::google::protobuf::internal::WireFormatLite::ReadRepeatedPrimitive<
float, ::google::protobuf::internal::WireFormatLite::TYPE_FLOAT>(
1, 21u, input, this->mutable_max_size())));
} else if (
static_cast< ::google::protobuf::uint8>(tag) ==
static_cast< ::google::protobuf::uint8>(18u /* 18 & 0xFF */)) {
DO_((::google::protobuf::internal::WireFormatLite::ReadPackedPrimitiveNoInline<
float, ::google::protobuf::internal::WireFormatLite::TYPE_FLOAT>(
input, &max_size_)));
input, this->mutable_max_size())));
} else {
goto handle_unusual;
}
@ -6985,15 +6997,16 @@ void PriorBoxParameter::SerializeWithCachedSizes(
::google::protobuf::uint32 cached_has_bits = 0;
(void) cached_has_bits;
cached_has_bits = _has_bits_[0];
// optional float min_size = 1;
if (cached_has_bits & 0x00000001u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(1, this->min_size(), output);
// repeated float min_size = 1;
for (int i = 0, n = this->min_size_size(); i < n; i++) {
::google::protobuf::internal::WireFormatLite::WriteFloat(
1, this->min_size(i), output);
}
// optional float max_size = 2;
if (cached_has_bits & 0x00000002u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(2, this->max_size(), output);
// repeated float max_size = 2;
for (int i = 0, n = this->max_size_size(); i < n; i++) {
::google::protobuf::internal::WireFormatLite::WriteFloat(
2, this->max_size(i), output);
}
// repeated float aspect_ratio = 3;
@ -7002,13 +7015,14 @@ void PriorBoxParameter::SerializeWithCachedSizes(
3, this->aspect_ratio(i), output);
}
cached_has_bits = _has_bits_[0];
// optional bool flip = 4 [default = true];
if (cached_has_bits & 0x00000100u) {
if (cached_has_bits & 0x00000040u) {
::google::protobuf::internal::WireFormatLite::WriteBool(4, this->flip(), output);
}
// optional bool clip = 5 [default = true];
if (cached_has_bits & 0x00000200u) {
if (cached_has_bits & 0x00000080u) {
::google::protobuf::internal::WireFormatLite::WriteBool(5, this->clip(), output);
}
@ -7019,37 +7033,37 @@ void PriorBoxParameter::SerializeWithCachedSizes(
}
// optional uint32 img_size = 7;
if (cached_has_bits & 0x00000004u) {
if (cached_has_bits & 0x00000001u) {
::google::protobuf::internal::WireFormatLite::WriteUInt32(7, this->img_size(), output);
}
// optional uint32 img_h = 8;
if (cached_has_bits & 0x00000008u) {
if (cached_has_bits & 0x00000002u) {
::google::protobuf::internal::WireFormatLite::WriteUInt32(8, this->img_h(), output);
}
// optional uint32 img_w = 9;
if (cached_has_bits & 0x00000010u) {
if (cached_has_bits & 0x00000004u) {
::google::protobuf::internal::WireFormatLite::WriteUInt32(9, this->img_w(), output);
}
// optional float step = 10;
if (cached_has_bits & 0x00000020u) {
if (cached_has_bits & 0x00000008u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(10, this->step(), output);
}
// optional float step_h = 11;
if (cached_has_bits & 0x00000040u) {
if (cached_has_bits & 0x00000010u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(11, this->step_h(), output);
}
// optional float step_w = 12;
if (cached_has_bits & 0x00000080u) {
if (cached_has_bits & 0x00000020u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(12, this->step_w(), output);
}
// optional float offset = 13 [default = 0.5];
if (cached_has_bits & 0x00000400u) {
if (cached_has_bits & 0x00000100u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(13, this->offset(), output);
}
@ -7091,28 +7105,26 @@ void PriorBoxParameter::SerializeWithCachedSizes(
::google::protobuf::uint32 cached_has_bits = 0;
(void) cached_has_bits;
cached_has_bits = _has_bits_[0];
// optional float min_size = 1;
if (cached_has_bits & 0x00000001u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(1, this->min_size(), target);
}
// repeated float min_size = 1;
target = ::google::protobuf::internal::WireFormatLite::
WriteFloatToArray(1, this->min_size_, target);
// optional float max_size = 2;
if (cached_has_bits & 0x00000002u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(2, this->max_size(), target);
}
// repeated float max_size = 2;
target = ::google::protobuf::internal::WireFormatLite::
WriteFloatToArray(2, this->max_size_, target);
// repeated float aspect_ratio = 3;
target = ::google::protobuf::internal::WireFormatLite::
WriteFloatToArray(3, this->aspect_ratio_, target);
cached_has_bits = _has_bits_[0];
// optional bool flip = 4 [default = true];
if (cached_has_bits & 0x00000100u) {
if (cached_has_bits & 0x00000040u) {
target = ::google::protobuf::internal::WireFormatLite::WriteBoolToArray(4, this->flip(), target);
}
// optional bool clip = 5 [default = true];
if (cached_has_bits & 0x00000200u) {
if (cached_has_bits & 0x00000080u) {
target = ::google::protobuf::internal::WireFormatLite::WriteBoolToArray(5, this->clip(), target);
}
@ -7121,37 +7133,37 @@ void PriorBoxParameter::SerializeWithCachedSizes(
WriteFloatToArray(6, this->variance_, target);
// optional uint32 img_size = 7;
if (cached_has_bits & 0x00000004u) {
if (cached_has_bits & 0x00000001u) {
target = ::google::protobuf::internal::WireFormatLite::WriteUInt32ToArray(7, this->img_size(), target);
}
// optional uint32 img_h = 8;
if (cached_has_bits & 0x00000008u) {
if (cached_has_bits & 0x00000002u) {
target = ::google::protobuf::internal::WireFormatLite::WriteUInt32ToArray(8, this->img_h(), target);
}
// optional uint32 img_w = 9;
if (cached_has_bits & 0x00000010u) {
if (cached_has_bits & 0x00000004u) {
target = ::google::protobuf::internal::WireFormatLite::WriteUInt32ToArray(9, this->img_w(), target);
}
// optional float step = 10;
if (cached_has_bits & 0x00000020u) {
if (cached_has_bits & 0x00000008u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(10, this->step(), target);
}
// optional float step_h = 11;
if (cached_has_bits & 0x00000040u) {
if (cached_has_bits & 0x00000010u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(11, this->step_h(), target);
}
// optional float step_w = 12;
if (cached_has_bits & 0x00000080u) {
if (cached_has_bits & 0x00000020u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(12, this->step_w(), target);
}
// optional float offset = 13 [default = 0.5];
if (cached_has_bits & 0x00000400u) {
if (cached_has_bits & 0x00000100u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(13, this->offset(), target);
}
@ -7188,6 +7200,24 @@ size_t PriorBoxParameter::ByteSizeLong() const {
::google::protobuf::internal::WireFormat::ComputeUnknownFieldsSize(
_internal_metadata_.unknown_fields());
}
// repeated float min_size = 1;
{
unsigned int count = static_cast<unsigned int>(this->min_size_size());
size_t data_size = 4UL * count;
total_size += 1 *
::google::protobuf::internal::FromIntSize(this->min_size_size());
total_size += data_size;
}
// repeated float max_size = 2;
{
unsigned int count = static_cast<unsigned int>(this->max_size_size());
size_t data_size = 4UL * count;
total_size += 1 *
::google::protobuf::internal::FromIntSize(this->max_size_size());
total_size += data_size;
}
// repeated float aspect_ratio = 3;
{
unsigned int count = static_cast<unsigned int>(this->aspect_ratio_size());
@ -7243,16 +7273,6 @@ size_t PriorBoxParameter::ByteSizeLong() const {
}
if (_has_bits_[0 / 32] & 255u) {
// optional float min_size = 1;
if (has_min_size()) {
total_size += 1 + 4;
}
// optional float max_size = 2;
if (has_max_size()) {
total_size += 1 + 4;
}
// optional uint32 img_size = 7;
if (has_img_size()) {
total_size += 1 +
@ -7289,8 +7309,6 @@ size_t PriorBoxParameter::ByteSizeLong() const {
total_size += 1 + 4;
}
}
if (_has_bits_[8 / 32] & 1792u) {
// optional bool flip = 4 [default = true];
if (has_flip()) {
total_size += 1 + 1;
@ -7301,12 +7319,12 @@ size_t PriorBoxParameter::ByteSizeLong() const {
total_size += 1 + 1;
}
// optional float offset = 13 [default = 0.5];
if (has_offset()) {
total_size += 1 + 4;
}
}
// optional float offset = 13 [default = 0.5];
if (has_offset()) {
total_size += 1 + 4;
}
int cached_size = ::google::protobuf::internal::ToCachedSize(total_size);
GOOGLE_SAFE_CONCURRENT_WRITES_BEGIN();
_cached_size_ = cached_size;
@ -7336,6 +7354,8 @@ void PriorBoxParameter::MergeFrom(const PriorBoxParameter& from) {
::google::protobuf::uint32 cached_has_bits = 0;
(void) cached_has_bits;
min_size_.MergeFrom(from.min_size_);
max_size_.MergeFrom(from.max_size_);
aspect_ratio_.MergeFrom(from.aspect_ratio_);
variance_.MergeFrom(from.variance_);
offset_h_.MergeFrom(from.offset_h_);
@ -7345,43 +7365,34 @@ void PriorBoxParameter::MergeFrom(const PriorBoxParameter& from) {
cached_has_bits = from._has_bits_[0];
if (cached_has_bits & 255u) {
if (cached_has_bits & 0x00000001u) {
min_size_ = from.min_size_;
}
if (cached_has_bits & 0x00000002u) {
max_size_ = from.max_size_;
}
if (cached_has_bits & 0x00000004u) {
img_size_ = from.img_size_;
}
if (cached_has_bits & 0x00000008u) {
if (cached_has_bits & 0x00000002u) {
img_h_ = from.img_h_;
}
if (cached_has_bits & 0x00000010u) {
if (cached_has_bits & 0x00000004u) {
img_w_ = from.img_w_;
}
if (cached_has_bits & 0x00000020u) {
if (cached_has_bits & 0x00000008u) {
step_ = from.step_;
}
if (cached_has_bits & 0x00000040u) {
if (cached_has_bits & 0x00000010u) {
step_h_ = from.step_h_;
}
if (cached_has_bits & 0x00000080u) {
if (cached_has_bits & 0x00000020u) {
step_w_ = from.step_w_;
}
_has_bits_[0] |= cached_has_bits;
}
if (cached_has_bits & 1792u) {
if (cached_has_bits & 0x00000100u) {
if (cached_has_bits & 0x00000040u) {
flip_ = from.flip_;
}
if (cached_has_bits & 0x00000200u) {
if (cached_has_bits & 0x00000080u) {
clip_ = from.clip_;
}
if (cached_has_bits & 0x00000400u) {
offset_ = from.offset_;
}
_has_bits_[0] |= cached_has_bits;
}
if (cached_has_bits & 0x00000100u) {
set_offset(from.offset());
}
}
void PriorBoxParameter::CopyFrom(const ::google::protobuf::Message& from) {
@ -7408,14 +7419,14 @@ void PriorBoxParameter::Swap(PriorBoxParameter* other) {
}
void PriorBoxParameter::InternalSwap(PriorBoxParameter* other) {
using std::swap;
min_size_.InternalSwap(&other->min_size_);
max_size_.InternalSwap(&other->max_size_);
aspect_ratio_.InternalSwap(&other->aspect_ratio_);
variance_.InternalSwap(&other->variance_);
offset_h_.InternalSwap(&other->offset_h_);
offset_w_.InternalSwap(&other->offset_w_);
width_.InternalSwap(&other->width_);
height_.InternalSwap(&other->height_);
swap(min_size_, other->min_size_);
swap(max_size_, other->max_size_);
swap(img_size_, other->img_size_);
swap(img_h_, other->img_h_);
swap(img_w_, other->img_w_);

174
modules/dnn/misc/caffe/opencv-caffe.pb.h
Unescape View File

@ -1886,6 +1886,30 @@ class PriorBoxParameter : public ::google::protobuf::Message /* @@protoc_inserti
// accessors -------------------------------------------------------
// repeated float min_size = 1;
int min_size_size() const;
void clear_min_size();
static const int kMinSizeFieldNumber = 1;
float min_size(int index) const;
void set_min_size(int index, float value);
void add_min_size(float value);
const ::google::protobuf::RepeatedField< float >&
min_size() const;
::google::protobuf::RepeatedField< float >*
mutable_min_size();
// repeated float max_size = 2;
int max_size_size() const;
void clear_max_size();
static const int kMaxSizeFieldNumber = 2;
float max_size(int index) const;
void set_max_size(int index, float value);
void add_max_size(float value);
const ::google::protobuf::RepeatedField< float >&
max_size() const;
::google::protobuf::RepeatedField< float >*
mutable_max_size();
// repeated float aspect_ratio = 3;
int aspect_ratio_size() const;
void clear_aspect_ratio();
@ -1958,20 +1982,6 @@ class PriorBoxParameter : public ::google::protobuf::Message /* @@protoc_inserti
::google::protobuf::RepeatedField< float >*
mutable_height();
// optional float min_size = 1;
bool has_min_size() const;
void clear_min_size();
static const int kMinSizeFieldNumber = 1;
float min_size() const;
void set_min_size(float value);
// optional float max_size = 2;
bool has_max_size() const;
void clear_max_size();
static const int kMaxSizeFieldNumber = 2;
float max_size() const;
void set_max_size(float value);
// optional uint32 img_size = 7;
bool has_img_size() const;
void clear_img_size();
@ -2037,10 +2047,6 @@ class PriorBoxParameter : public ::google::protobuf::Message /* @@protoc_inserti
// @@protoc_insertion_point(class_scope:opencv_caffe.PriorBoxParameter)
private:
void set_has_min_size();
void clear_has_min_size();
void set_has_max_size();
void clear_has_max_size();
void set_has_flip();
void clear_has_flip();
void set_has_clip();
@ -2063,14 +2069,14 @@ class PriorBoxParameter : public ::google::protobuf::Message /* @@protoc_inserti
::google::protobuf::internal::InternalMetadataWithArena _internal_metadata_;
::google::protobuf::internal::HasBits<1> _has_bits_;
mutable int _cached_size_;
::google::protobuf::RepeatedField< float > min_size_;
::google::protobuf::RepeatedField< float > max_size_;
::google::protobuf::RepeatedField< float > aspect_ratio_;
::google::protobuf::RepeatedField< float > variance_;
::google::protobuf::RepeatedField< float > offset_h_;
::google::protobuf::RepeatedField< float > offset_w_;
::google::protobuf::RepeatedField< float > width_;
::google::protobuf::RepeatedField< float > height_;
float min_size_;
float max_size_;
::google::protobuf::uint32 img_size_;
::google::protobuf::uint32 img_h_;
::google::protobuf::uint32 img_w_;
@ -15271,53 +15277,65 @@ inline void NormalizeBBoxParameter::set_eps(float value) {
// PriorBoxParameter
// optional float min_size = 1;
inline bool PriorBoxParameter::has_min_size() const {
return (_has_bits_[0] & 0x00000001u) != 0;
}
inline void PriorBoxParameter::set_has_min_size() {
_has_bits_[0] |= 0x00000001u;
}
inline void PriorBoxParameter::clear_has_min_size() {
_has_bits_[0] &= ~0x00000001u;
// repeated float min_size = 1;
inline int PriorBoxParameter::min_size_size() const {
return min_size_.size();
}
inline void PriorBoxParameter::clear_min_size() {
min_size_ = 0;
clear_has_min_size();
min_size_.Clear();
}
inline float PriorBoxParameter::min_size() const {
inline float PriorBoxParameter::min_size(int index) const {
// @@protoc_insertion_point(field_get:opencv_caffe.PriorBoxParameter.min_size)
return min_size_;
return min_size_.Get(index);
}
inline void PriorBoxParameter::set_min_size(float value) {
set_has_min_size();
min_size_ = value;
inline void PriorBoxParameter::set_min_size(int index, float value) {
min_size_.Set(index, value);
// @@protoc_insertion_point(field_set:opencv_caffe.PriorBoxParameter.min_size)
}
// optional float max_size = 2;
inline bool PriorBoxParameter::has_max_size() const {
return (_has_bits_[0] & 0x00000002u) != 0;
inline void PriorBoxParameter::add_min_size(float value) {
min_size_.Add(value);
// @@protoc_insertion_point(field_add:opencv_caffe.PriorBoxParameter.min_size)
}
inline void PriorBoxParameter::set_has_max_size() {
_has_bits_[0] |= 0x00000002u;
inline const ::google::protobuf::RepeatedField< float >&
PriorBoxParameter::min_size() const {
// @@protoc_insertion_point(field_list:opencv_caffe.PriorBoxParameter.min_size)
return min_size_;
}
inline void PriorBoxParameter::clear_has_max_size() {
_has_bits_[0] &= ~0x00000002u;
inline ::google::protobuf::RepeatedField< float >*
PriorBoxParameter::mutable_min_size() {
// @@protoc_insertion_point(field_mutable_list:opencv_caffe.PriorBoxParameter.min_size)
return &min_size_;
}
// repeated float max_size = 2;
inline int PriorBoxParameter::max_size_size() const {
return max_size_.size();
}
inline void PriorBoxParameter::clear_max_size() {
max_size_ = 0;
clear_has_max_size();
max_size_.Clear();
}
inline float PriorBoxParameter::max_size() const {
inline float PriorBoxParameter::max_size(int index) const {
// @@protoc_insertion_point(field_get:opencv_caffe.PriorBoxParameter.max_size)
return max_size_;
return max_size_.Get(index);
}
inline void PriorBoxParameter::set_max_size(float value) {
set_has_max_size();
max_size_ = value;
inline void PriorBoxParameter::set_max_size(int index, float value) {
max_size_.Set(index, value);
// @@protoc_insertion_point(field_set:opencv_caffe.PriorBoxParameter.max_size)
}
inline void PriorBoxParameter::add_max_size(float value) {
max_size_.Add(value);
// @@protoc_insertion_point(field_add:opencv_caffe.PriorBoxParameter.max_size)
}
inline const ::google::protobuf::RepeatedField< float >&
PriorBoxParameter::max_size() const {
// @@protoc_insertion_point(field_list:opencv_caffe.PriorBoxParameter.max_size)
return max_size_;
}
inline ::google::protobuf::RepeatedField< float >*
PriorBoxParameter::mutable_max_size() {
// @@protoc_insertion_point(field_mutable_list:opencv_caffe.PriorBoxParameter.max_size)
return &max_size_;
}
// repeated float aspect_ratio = 3;
inline int PriorBoxParameter::aspect_ratio_size() const {
@ -15351,13 +15369,13 @@ PriorBoxParameter::mutable_aspect_ratio() {
// optional bool flip = 4 [default = true];
inline bool PriorBoxParameter::has_flip() const {
return (_has_bits_[0] & 0x00000100u) != 0;
return (_has_bits_[0] & 0x00000040u) != 0;
}
inline void PriorBoxParameter::set_has_flip() {
_has_bits_[0] |= 0x00000100u;
_has_bits_[0] |= 0x00000040u;
}
inline void PriorBoxParameter::clear_has_flip() {
_has_bits_[0] &= ~0x00000100u;
_has_bits_[0] &= ~0x00000040u;
}
inline void PriorBoxParameter::clear_flip() {
flip_ = true;
@ -15375,13 +15393,13 @@ inline void PriorBoxParameter::set_flip(bool value) {
// optional bool clip = 5 [default = true];
inline bool PriorBoxParameter::has_clip() const {
return (_has_bits_[0] & 0x00000200u) != 0;
return (_has_bits_[0] & 0x00000080u) != 0;
}
inline void PriorBoxParameter::set_has_clip() {
_has_bits_[0] |= 0x00000200u;
_has_bits_[0] |= 0x00000080u;
}
inline void PriorBoxParameter::clear_has_clip() {
_has_bits_[0] &= ~0x00000200u;
_has_bits_[0] &= ~0x00000080u;
}
inline void PriorBoxParameter::clear_clip() {
clip_ = true;
@ -15429,13 +15447,13 @@ PriorBoxParameter::mutable_variance() {
// optional uint32 img_size = 7;
inline bool PriorBoxParameter::has_img_size() const {
return (_has_bits_[0] & 0x00000004u) != 0;
return (_has_bits_[0] & 0x00000001u) != 0;
}
inline void PriorBoxParameter::set_has_img_size() {
_has_bits_[0] |= 0x00000004u;
_has_bits_[0] |= 0x00000001u;
}
inline void PriorBoxParameter::clear_has_img_size() {
_has_bits_[0] &= ~0x00000004u;
_has_bits_[0] &= ~0x00000001u;
}
inline void PriorBoxParameter::clear_img_size() {
img_size_ = 0u;
@ -15453,13 +15471,13 @@ inline void PriorBoxParameter::set_img_size(::google::protobuf::uint32 value) {
// optional uint32 img_h = 8;
inline bool PriorBoxParameter::has_img_h() const {
return (_has_bits_[0] & 0x00000008u) != 0;
return (_has_bits_[0] & 0x00000002u) != 0;
}
inline void PriorBoxParameter::set_has_img_h() {
_has_bits_[0] |= 0x00000008u;
_has_bits_[0] |= 0x00000002u;
}
inline void PriorBoxParameter::clear_has_img_h() {
_has_bits_[0] &= ~0x00000008u;
_has_bits_[0] &= ~0x00000002u;
}
inline void PriorBoxParameter::clear_img_h() {
img_h_ = 0u;
@ -15477,13 +15495,13 @@ inline void PriorBoxParameter::set_img_h(::google::protobuf::uint32 value) {
// optional uint32 img_w = 9;
inline bool PriorBoxParameter::has_img_w() const {
return (_has_bits_[0] & 0x00000010u) != 0;
return (_has_bits_[0] & 0x00000004u) != 0;
}
inline void PriorBoxParameter::set_has_img_w() {
_has_bits_[0] |= 0x00000010u;
_has_bits_[0] |= 0x00000004u;
}
inline void PriorBoxParameter::clear_has_img_w() {
_has_bits_[0] &= ~0x00000010u;
_has_bits_[0] &= ~0x00000004u;
}
inline void PriorBoxParameter::clear_img_w() {
img_w_ = 0u;
@ -15501,13 +15519,13 @@ inline void PriorBoxParameter::set_img_w(::google::protobuf::uint32 value) {
// optional float step = 10;
inline bool PriorBoxParameter::has_step() const {
return (_has_bits_[0] & 0x00000020u) != 0;
return (_has_bits_[0] & 0x00000008u) != 0;
}
inline void PriorBoxParameter::set_has_step() {
_has_bits_[0] |= 0x00000020u;
_has_bits_[0] |= 0x00000008u;
}
inline void PriorBoxParameter::clear_has_step() {
_has_bits_[0] &= ~0x00000020u;
_has_bits_[0] &= ~0x00000008u;
}
inline void PriorBoxParameter::clear_step() {
step_ = 0;
@ -15525,13 +15543,13 @@ inline void PriorBoxParameter::set_step(float value) {
// optional float step_h = 11;
inline bool PriorBoxParameter::has_step_h() const {
return (_has_bits_[0] & 0x00000040u) != 0;
return (_has_bits_[0] & 0x00000010u) != 0;
}
inline void PriorBoxParameter::set_has_step_h() {
_has_bits_[0] |= 0x00000040u;
_has_bits_[0] |= 0x00000010u;
}
inline void PriorBoxParameter::clear_has_step_h() {
_has_bits_[0] &= ~0x00000040u;
_has_bits_[0] &= ~0x00000010u;
}
inline void PriorBoxParameter::clear_step_h() {
step_h_ = 0;
@ -15549,13 +15567,13 @@ inline void PriorBoxParameter::set_step_h(float value) {
// optional float step_w = 12;
inline bool PriorBoxParameter::has_step_w() const {
return (_has_bits_[0] & 0x00000080u) != 0;
return (_has_bits_[0] & 0x00000020u) != 0;
}
inline void PriorBoxParameter::set_has_step_w() {
_has_bits_[0] |= 0x00000080u;
_has_bits_[0] |= 0x00000020u;
}
inline void PriorBoxParameter::clear_has_step_w() {
_has_bits_[0] &= ~0x00000080u;
_has_bits_[0] &= ~0x00000020u;
}
inline void PriorBoxParameter::clear_step_w() {
step_w_ = 0;
@ -15573,13 +15591,13 @@ inline void PriorBoxParameter::set_step_w(float value) {
// optional float offset = 13 [default = 0.5];
inline bool PriorBoxParameter::has_offset() const {
return (_has_bits_[0] & 0x00000400u) != 0;
return (_has_bits_[0] & 0x00000100u) != 0;
}
inline void PriorBoxParameter::set_has_offset() {
_has_bits_[0] |= 0x00000400u;
_has_bits_[0] |= 0x00000100u;
}
inline void PriorBoxParameter::clear_has_offset() {
_has_bits_[0] &= ~0x00000400u;
_has_bits_[0] &= ~0x00000100u;
}
inline void PriorBoxParameter::clear_offset() {
offset_ = 0.5f;

9
modules/dnn/misc/face_detector_accuracy.py
Unescape View File

@ -154,8 +154,13 @@ if args.proto and args.model:
top = int(out[0, 0, i, 4] * img.shape[0])
right = int(out[0, 0, i, 5] * img.shape[1])
bottom = int(out[0, 0, i, 6] * img.shape[0])
addDetection(detections, imageId, left, top, width=right - left + 1,
height=bottom - top + 1, score=confidence)
x = max(0, min(left, img.shape[1] - 1))
y = max(0, min(top, img.shape[0] - 1))
w = max(0, min(right - x + 1, img.shape[1] - x))
h = max(0, min(bottom - y + 1, img.shape[0] - y))
addDetection(detections, imageId, x, y, w, h, score=confidence)
elif args.cascade:
cascade = cv.CascadeClassifier(args.cascade)

4
modules/dnn/misc/quantize_face_detector.py
Unescape View File

@ -173,9 +173,9 @@ conv7_2_h = tf.space_to_batch_nd(conv7_1_h, [1, 1], [[1, 1], [1, 1]], name='Pad_
conv7_2_h = conv(conv7_2_h, stride=2, pad='VALID', name='conv7_2_h', activ=tf.nn.relu)
conv8_1_h = conv(conv7_2_h, pad='SAME', name='conv8_1_h', activ=tf.nn.relu)
conv8_2_h = conv(conv8_1_h, pad='SAME', name='conv8_2_h', activ=tf.nn.relu)
conv8_2_h = conv(conv8_1_h, pad='VALID', name='conv8_2_h', activ=tf.nn.relu)
conv9_1_h = conv(conv8_2_h, 'conv9_1_h', activ=tf.nn.relu)
conv9_2_h = conv(conv9_1_h, pad='SAME', name='conv9_2_h', activ=tf.nn.relu)
conv9_2_h = conv(conv9_1_h, pad='VALID', name='conv9_2_h', activ=tf.nn.relu)
conv4_3_norm = l2norm(layer_256_1_relu1, 'conv4_3_norm')

4
modules/dnn/perf/perf_net.cpp
Unescape View File

@ -142,8 +142,6 @@ PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
{
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("");
processNet("dnn/ssd_mobilenet_v1_coco_2017_11_17.pb", "ssd_mobilenet_v1_coco_2017_11_17.pbtxt", "",
Mat(cv::Size(300, 300), CV_32FC3));
}
@ -152,8 +150,6 @@ PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
{
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("");
processNet("dnn/ssd_mobilenet_v2_coco_2018_03_29.pb", "ssd_mobilenet_v2_coco_2018_03_29.pbtxt", "",
Mat(cv::Size(300, 300), CV_32FC3));
}

4
modules/dnn/src/caffe/opencv-caffe.proto
Unescape View File

@ -116,9 +116,9 @@ message PriorBoxParameter {
CENTER_SIZE = 2;
}
// Minimum box size (in pixels). Required!
optional float min_size = 1;
repeated float min_size = 1;
// Maximum box size (in pixels). Required!
optional float max_size = 2;
repeated float max_size = 2;
// Various of aspect ratios. Duplicate ratios will be ignored.
// If none is provided, we use default ratio 1.
repeated float aspect_ratio = 3;

3
modules/dnn/src/layers/detection_output_layer.cpp
Unescape View File

@ -198,7 +198,7 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
(backendId == DNN_BACKEND_INFERENCE_ENGINE && !_locPredTransposed && _bboxesNormalized && !_clip);
(backendId == DNN_BACKEND_INFERENCE_ENGINE && !_locPredTransposed && _bboxesNormalized);
}
bool getMemoryShapes(const std::vector<MatShape> &inputs,
@ -936,6 +936,7 @@ public:
InferenceEngine::Builder::Layer l = ieLayer;
l.getParameters()["eta"] = std::string("1.0");
l.getParameters()["clip"] = _clip;
return Ptr<BackendNode>(new InfEngineBackendNode(l));
}

2
modules/dnn/src/layers/elementwise_layers.cpp
Unescape View File

@ -796,7 +796,7 @@ struct AbsValFunctor
#ifdef HAVE_INF_ENGINE
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
return InferenceEngine::Builder::ReLULayer("").setNegativeSlope(-1);
return InferenceEngine::Builder::ReLULayer("").setNegativeSlope(-0.999999f);
}
#endif // HAVE_INF_ENGINE

64
modules/dnn/src/layers/prior_box_layer.cpp
Unescape View File

@ -181,21 +181,20 @@ public:
PriorBoxLayerImpl(const LayerParams &params)
{
setParamsFrom(params);
_minSize = getParameter<float>(params, "min_size", 0, false, 0);
_flip = getParameter<bool>(params, "flip", 0, false, true);
_clip = getParameter<bool>(params, "clip", 0, false, true);
_bboxesNormalized = getParameter<bool>(params, "normalized_bbox", 0, false, true);
_aspectRatios.clear();
getParams("min_size", params, &_minSize);
getAspectRatios(params);
getVariance(params);
_maxSize = -1;
if (params.has("max_size"))
{
_maxSize = params.get("max_size").get<float>(0);
CV_Assert(_maxSize > _minSize);
getParams("max_size", params, &_maxSize);
CV_Assert(_minSize.size() == _maxSize.size());
for (int i = 0; i < _maxSize.size(); i++)
CV_Assert(_minSize[i] < _maxSize[i]);
}
std::vector<float> widths, heights;
@ -214,25 +213,28 @@ public:
}
else
{
CV_Assert(_minSize > 0);
_boxWidths.resize(1 + (_maxSize > 0 ? 1 : 0) + _aspectRatios.size());
_boxHeights.resize(_boxWidths.size());
_boxWidths[0] = _boxHeights[0] = _minSize;
int i = 1;
if (_maxSize > 0)
CV_Assert(!_minSize.empty());
for (int i = 0; i < _minSize.size(); ++i)
{
// second prior: aspect_ratio = 1, size = sqrt(min_size * max_size)
_boxWidths[i] = _boxHeights[i] = sqrt(_minSize * _maxSize);
i += 1;
}
float minSize = _minSize[i];
CV_Assert(minSize > 0);
_boxWidths.push_back(minSize);
_boxHeights.push_back(minSize);
// rest of priors
for (size_t r = 0; r < _aspectRatios.size(); ++r)
{
float arSqrt = sqrt(_aspectRatios[r]);
_boxWidths[i + r] = _minSize * arSqrt;
_boxHeights[i + r] = _minSize / arSqrt;
if (_maxSize.size() > 0)
{
float size = sqrt(minSize * _maxSize[i]);
_boxWidths.push_back(size);
_boxHeights.push_back(size);
}
// rest of priors
for (size_t r = 0; r < _aspectRatios.size(); ++r)
{
float arSqrt = sqrt(_aspectRatios[r]);
_boxWidths.push_back(minSize * arSqrt);
_boxHeights.push_back(minSize / arSqrt);
}
}
}
CV_Assert(_boxWidths.size() == _boxHeights.size());
@ -272,8 +274,9 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
(backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine()) ||
(backendId == DNN_BACKEND_VKCOM && haveVulkan());
(backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() &&
( _explicitSizes || (_minSize.size() == 1 && _maxSize.size() <= 1)))
|| (backendId == DNN_BACKEND_VKCOM && haveVulkan());
}
bool getMemoryShapes(const std::vector<MatShape> &inputs,
@ -523,10 +526,9 @@ public:
InferenceEngine::Builder::PriorBoxLayer ieLayer(name);
CV_Assert(!_explicitSizes);
ieLayer.setMinSize(_minSize);
if (_maxSize > 0)
ieLayer.setMaxSize(_maxSize);
ieLayer.setMinSize(_minSize[0]);
if (!_maxSize.empty())
ieLayer.setMaxSize(_maxSize[0]);
CV_CheckEQ(_offsetsX.size(), (size_t)1, ""); CV_CheckEQ(_offsetsY.size(), (size_t)1, ""); CV_CheckEQ(_offsetsX[0], _offsetsY[0], "");
ieLayer.setOffset(_offsetsX[0]);
@ -573,8 +575,8 @@ public:
}
private:
float _minSize;
float _maxSize;
std::vector<float> _minSize;
std::vector<float> _maxSize;
float _stepX, _stepY;

41
modules/dnn/src/onnx/onnx_importer.cpp
Unescape View File

@ -465,6 +465,20 @@ void ONNXImporter::populateNet(Net dstNet)
}
layerParams.set("begin", DictValue::arrayInt(&begin[0], begin.size()));
layerParams.set("end", DictValue::arrayInt(&end[0], end.size()));
}
else if (layer_type == "Split")
{
DictValue splits = layerParams.get("split");
const int numSplits = splits.size();
CV_Assert(numSplits > 1);
std::vector<int> slicePoints(numSplits - 1, splits.get<int>(0));
for (int i = 1; i < splits.size() - 1; ++i)
{
slicePoints[i] = slicePoints[i - 1] + splits.get<int>(i - 1);
}
layerParams.set("slice_point", DictValue::arrayInt(&slicePoints[0], slicePoints.size()));
layerParams.type = "Slice";
}
else if (layer_type == "Add" || layer_type == "Sum")
{
@ -486,6 +500,11 @@ void ONNXImporter::populateNet(Net dstNet)
layerParams.type = "Eltwise";
}
}
else if (layer_type == "Max")
{
layerParams.type = "Eltwise";
layerParams.set("operation", "max");
}
else if (layer_type == "Sub")
{
Mat blob = getBlob(node_proto, constBlobs, 1);
@ -741,6 +760,16 @@ void ONNXImporter::populateNet(Net dstNet)
{
layerParams.type = "Permute";
replaceLayerParam(layerParams, "perm", "order");
CV_Assert(node_proto.input_size() == 1);
if (constBlobs.find(node_proto.input(0)) != constBlobs.end())
{
std::vector<Mat> inputs(1, getBlob(node_proto, constBlobs, 0)), transposed;
runLayer(layerParams, inputs, transposed);
CV_Assert(transposed.size() == 1);
constBlobs.insert(std::make_pair(layerParams.name, transposed[0]));
continue;
}
}
else if (layer_type == "Unsqueeze")
{
@ -906,8 +935,10 @@ void ONNXImporter::populateNet(Net dstNet)
}
int id = dstNet.addLayer(layerParams.name, layerParams.type, layerParams);
layer_id.insert(std::make_pair(layerParams.name, LayerInfo(id, 0)));
for (int i = 0; i < node_proto.output_size(); ++i)
{
layer_id.insert(std::make_pair(node_proto.output(i), LayerInfo(id, i)));
}
std::vector<MatShape> layerInpShapes, layerOutShapes, layerInternalShapes;
for (int j = 0; j < node_proto.input_size(); j++) {
@ -924,8 +955,10 @@ void ONNXImporter::populateNet(Net dstNet)
// Compute shape of output blob for this layer.
Ptr<Layer> layer = dstNet.getLayer(id);
layer->getMemoryShapes(layerInpShapes, 0, layerOutShapes, layerInternalShapes);
CV_Assert(!layerOutShapes.empty());
outShapes[layerParams.name] = layerOutShapes[0];
for (int i = 0; i < node_proto.output_size() && i < (int)layerOutShapes.size(); ++i)
{
outShapes[node_proto.output(i)] = layerOutShapes[i];
}
}
}

10
modules/dnn/test/test_backends.cpp
Unescape View File

@ -205,10 +205,6 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
if (backend == DNN_BACKEND_HALIDE)
applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
#endif
Mat sample = imread(findDataFile("dnn/street.png"));
Mat inp = blobFromImage(sample, 1.0f, Size(300, 300), Scalar(), false);
@ -248,10 +244,6 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
if (backend == DNN_BACKEND_HALIDE)
applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
#endif
Mat sample = imread(findDataFile("dnn/street.png"));
Mat inp = blobFromImage(sample, 1.0f, Size(300, 300), Scalar(), false);
@ -395,7 +387,7 @@ TEST_P(DNNTestNetwork, DenseNet_121)
float l1 = 0.0, lInf = 0.0;
if (target == DNN_TARGET_OPENCL_FP16)
{
l1 = 9e-3; lInf = 5e-2;
l1 = 2e-2; lInf = 9e-2;
}
else if (target == DNN_TARGET_MYRIAD)
{

4
modules/dnn/test/test_caffe_importer.cpp
Unescape View File

@ -496,7 +496,11 @@ TEST_P(Test_Caffe_nets, DenseNet_121)
float l1 = default_l1, lInf = default_lInf;
if (target == DNN_TARGET_OPENCL_FP16)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
l1 = 0.04; lInf = 0.21;
#else
l1 = 0.017; lInf = 0.0795;
#endif
}
else if (target == DNN_TARGET_MYRIAD)
{

2
modules/dnn/test/test_darknet_importer.cpp
Unescape View File

@ -360,7 +360,7 @@ TEST_P(Test_Darknet_nets, YOLOv3)
1, 2, 0.989633f, 0.450719f, 0.463353f, 0.496305f, 0.522258f, // a car
1, 2, 0.997412f, 0.647584f, 0.459939f, 0.821038f, 0.663947f); // a car
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0047 : 8e-5;
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.006 : 8e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.018 : 3e-4;
std::string config_file = "yolov3.cfg";

23
modules/dnn/test/test_layers.cpp
Unescape View File

@ -233,9 +233,14 @@ TEST_P(Test_Caffe_layers, Dropout)
TEST_P(Test_Caffe_layers, Concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
#if defined(INF_ENGINE_RELEASE)
#if INF_ENGINE_VER_MAJOR_GE(2019010000) && INF_ENGINE_VER_MAJOR_LT(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_2019R1, CV_TEST_TAG_DNN_SKIP_IE_2019R1_1);
#elif INF_ENGINE_VER_MAJOR_EQ(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
#endif
#endif
testLayerUsingCaffeModels("layer_concat");
testLayerUsingCaffeModels("layer_concat_optim", true, false);
@ -742,6 +747,22 @@ TEST_P(Test_Caffe_layers, Average_pooling_kernel_area)
normAssert(out, blobFromImage(ref));
}
TEST_P(Test_Caffe_layers, PriorBox_repeated)
{
Net net = readNet(_tf("prior_box.prototxt"));
int inp_size[] = {1, 3, 10, 10};
int shape_size[] = {1, 2, 3, 4};
Mat inp(4, inp_size, CV_32F);
randu(inp, -1.0f, 1.0f);
Mat shape(4, shape_size, CV_32F);
randu(shape, -1.0f, 1.0f);
net.setInput(inp, "data");
net.setInput(shape, "shape");
Mat out = net.forward();
Mat ref = blobFromNPY(_tf("priorbox_output.npy"));
normAssert(out, ref, "");
}
// Test PriorBoxLayer in case of no aspect ratios (just squared proposals).
TEST_P(Test_Caffe_layers, PriorBox_squares)
{

15
modules/dnn/test/test_onnx_importer.cpp
Unescape View File

@ -348,6 +348,13 @@ TEST_P(Test_ONNX_layers, Softmax)
testONNXModels("log_softmax", npy, 0, 0, false, false);
}
TEST_P(Test_ONNX_layers, Split_EltwiseMax)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE);
testONNXModels("split_max");
}
INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_ONNX_layers, dnnBackendsAndTargets());
class Test_ONNX_nets : public Test_ONNX_layers
@ -426,14 +433,6 @@ TEST_P(Test_ONNX_nets, RCNN_ILSVRC13)
testONNXModels("rcnn_ilsvrc13", pb, 0.0045);
}
TEST_P(Test_ONNX_nets, VGG16)
{
applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb
// output range: [-69; 72], after Softmax [0; 0.96]
testONNXModels("vgg16", pb, default_l1, default_lInf, true);
}
TEST_P(Test_ONNX_nets, VGG16_bn)
{
applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb

12
modules/dnn/test/test_tf_importer.cpp
Unescape View File

@ -436,11 +436,6 @@ TEST_P(Test_TensorFlow_nets, Inception_v2_SSD)
TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
#endif
checkBackend();
std::string proto = findDataFile("dnn/ssd_mobilenet_v1_coco_2017_11_17.pbtxt");
std::string model = findDataFile("dnn/ssd_mobilenet_v1_coco_2017_11_17.pb", false);
@ -456,7 +451,7 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD)
Mat out = net.forward();
Mat ref = blobFromNPY(findDataFile("dnn/tensorflow/ssd_mobilenet_v1_coco_2017_11_17.detection_out.npy"));
float scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 7e-3 : 1.5e-5;
float scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.011 : 1.5e-5;
float iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.012 : 1e-3;
float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.35 : 0.3;
@ -515,11 +510,6 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD_PPN)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
#endif
checkBackend();
std::string proto = findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pbtxt");
std::string model = findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pb", false);

4
modules/imgcodecs/src/exif.cpp
Unescape View File

@ -229,7 +229,7 @@ void ExifReader::parseExif()
uint32_t offset = getStartOffset();
size_t numEntry = getNumDirEntry();
size_t numEntry = getNumDirEntry( offset );
offset += 2; //go to start of tag fields
@ -303,7 +303,7 @@ uint32_t ExifReader::getStartOffset() const
*
* @return The number of directory entries
*/
size_t ExifReader::getNumDirEntry() const
size_t ExifReader::getNumDirEntry(const size_t offsetNumDir) const
{
return getU16( offsetNumDir );
}

5
modules/imgcodecs/src/exif.hpp
Unescape View File

@ -199,7 +199,7 @@ private:
bool checkTagMark() const;
size_t getFieldSize ();
size_t getNumDirEntry() const;
size_t getNumDirEntry( const size_t offsetNumDir ) const;
uint32_t getStartOffset() const;
uint16_t getExifTag( const size_t offset ) const;
uint16_t getU16( const size_t offset ) const;
@ -225,9 +225,6 @@ private:
private:
static const uint16_t tagMarkRequired = 0x2A;
//offset to the _number-of-directory-entry_ field
static const size_t offsetNumDir = 8;
//max size of data in tag.
//'DDDDDDDD' contains the value of that Tag. If its size is over 4bytes,
//'DDDDDDDD' contains the offset to data stored address.

2
modules/imgproc/perf/perf_cvt_color.cpp
Unescape View File

@ -417,7 +417,7 @@ PERF_TEST_P(Size_CvtMode_Bayer, cvtColorBayer8u,
TEST_CYCLE() cvtColor(src, dst, mode, ch.dcn);
SANITY_CHECK(dst, 1);
SANITY_CHECK_NOTHING();
}
typedef tuple<Size, CvtMode2> Size_CvtMode2_t;

4
modules/imgproc/src/box_filter.dispatch.cpp
Unescape View File

@ -389,7 +389,7 @@ Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
}
#endif
#if defined(HAVE_IPP)
#if 0 //defined(HAVE_IPP)
static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool normalize, int borderType)
{
#ifdef HAVE_IPP_IW
@ -476,7 +476,7 @@ void boxFilter(InputArray _src, OutputArray _dst, int ddepth,
CV_OVX_RUN(true,
openvx_boxfilter(src, dst, ddepth, ksize, anchor, normalize, borderType))
CV_IPP_RUN_FAST(ipp_boxfilter(src, dst, ksize, anchor, normalize, borderType));
//CV_IPP_RUN_FAST(ipp_boxfilter(src, dst, ksize, anchor, normalize, borderType));
borderType = (borderType&~BORDER_ISOLATED);

10
modules/imgproc/src/demosaicing.cpp
Unescape View File

@ -1153,14 +1153,14 @@ static void Bayer2RGB_VNG_8u( const Mat& srcmat, Mat& dstmat, int code )
{
Rs += srow[-bstep*2-2] + srow[0];
Gs += brow0[N6-1];
Bs += srow[-bstep+1]*2;
Bs += srow[-bstep-1]*2;
ng++;
}
if( gradSE < T )
{
Rs += srow[bstep*2+2] + srow[0];
Gs += brow2[N6+1];
Bs += srow[-bstep+1]*2;
Bs += srow[bstep+1]*2;
ng++;
}
R = srow[0];
@ -1394,8 +1394,8 @@ static void Bayer2RGB_VNG_8u( const Mat& srcmat, Mat& dstmat, int code )
RGs = _mm_adds_epi16(RGs, _mm_and_si128(_mm_merge_epi16(t1, t0), mask));
// GRs += {brow2[N6+1]; (srow[1]+srow[bstep*2+1])} * (T>gradSE)
GRs = _mm_adds_epi16(GRs, _mm_and_si128(_mm_merge_epi16(_mm_loadu_si128((__m128i*)(brow2+N6+1)), _mm_adds_epi16(x7,x10)), mask));
// Bs += {srow[-bstep+1]*2; (srow[bstep+2]+srow[bstep])} * (T>gradSE)
Bs = _mm_adds_epi16(Bs, _mm_and_si128(_mm_merge_epi16(_mm_slli_epi16(x5, 1), _mm_adds_epi16(x8,x11)), mask));
// Bs += {srow[bstep+1]*2; (srow[bstep+2]+srow[bstep])} * (T>gradSE)
Bs = _mm_adds_epi16(Bs, _mm_and_si128(_mm_merge_epi16(_mm_slli_epi16(x9, 1), _mm_adds_epi16(x8,x11)), mask));
// gradS ***********************************************
mask = _mm_cmpgt_epi16(T, gradS); // mask = T>gradS
@ -1451,7 +1451,7 @@ static void Bayer2RGB_VNG_8u( const Mat& srcmat, Mat& dstmat, int code )
// GRs += {brow0[N6-1]; (srow[-bstep*2-1]+srow[-1])} * (T>gradNW)
GRs = _mm_adds_epi16(GRs, _mm_and_si128(_mm_merge_epi16(_mm_loadu_si128((__m128i*)(brow0+N6-1)), _mm_adds_epi16(x2,x15)), mask));
// Bs += {srow[-bstep-1]*2; (srow[-bstep]+srow[-bstep-2])} * (T>gradNW)
Bs = _mm_adds_epi16(Bs, _mm_and_si128(_mm_merge_epi16(_mm_slli_epi16(x5, 1),_mm_adds_epi16(x3,x16)), mask));
Bs = _mm_adds_epi16(Bs, _mm_and_si128(_mm_merge_epi16(_mm_slli_epi16(x1, 1),_mm_adds_epi16(x3,x16)), mask));
__m128 ngf0 = _mm_div_ps(_0_5, _mm_cvtloepi16_ps(ng));
__m128 ngf1 = _mm_div_ps(_0_5, _mm_cvthiepi16_ps(ng));

6
modules/imgproc/src/filter.dispatch.cpp
Unescape View File

@ -1022,7 +1022,7 @@ static bool replacementFilter2D(int stype, int dtype, int kernel_type,
return success;
}
#ifdef HAVE_IPP
#if 0 //defined HAVE_IPP
static bool ippFilter2D(int stype, int dtype, int kernel_type,
uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
@ -1286,7 +1286,7 @@ void filter2D(int stype, int dtype, int kernel_type,
if (res)
return;
CV_IPP_RUN_FAST(ippFilter2D(stype, dtype, kernel_type,
/*CV_IPP_RUN_FAST(ippFilter2D(stype, dtype, kernel_type,
src_data, src_step,
dst_data, dst_step,
width, height,
@ -1295,7 +1295,7 @@ void filter2D(int stype, int dtype, int kernel_type,
kernel_data, kernel_step,
kernel_width, kernel_height,
anchor_x, anchor_y,
delta, borderType, isSubmatrix))
delta, borderType, isSubmatrix))*/
res = dftFilter2D(stype, dtype, kernel_type,
src_data, src_step,

4
modules/imgproc/src/median_blur.dispatch.cpp
Unescape View File

@ -203,7 +203,7 @@ static bool openvx_medianFilter(InputArray _src, OutputArray _dst, int ksize)
}
#endif
#ifdef HAVE_IPP
#if 0 //defined HAVE_IPP
static bool ipp_medianFilter(Mat &src0, Mat &dst, int ksize)
{
CV_INSTRUMENT_REGION_IPP();
@ -301,7 +301,7 @@ void medianBlur( InputArray _src0, OutputArray _dst, int ksize )
CV_OVX_RUN(true,
openvx_medianFilter(_src0, _dst, ksize))
CV_IPP_RUN_FAST(ipp_medianFilter(src0, dst, ksize));
//CV_IPP_RUN_FAST(ipp_medianFilter(src0, dst, ksize));
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::useTegra() && tegra::medianBlur(src0, dst, ksize))

4
modules/imgproc/src/smooth.dispatch.cpp
Unescape View File

@ -363,7 +363,7 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
#endif
#ifdef HAVE_IPP
#if 0 //defined HAVE_IPP
// IW 2017u2 has bug which doesn't allow use of partial inMem with tiling
#if IPP_DISABLE_GAUSSIANBLUR_PARALLEL
#define IPP_GAUSSIANBLUR_PARALLEL 0
@ -533,7 +533,7 @@ void GaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
CV_OVX_RUN(true,
openvx_gaussianBlur(src, dst, ksize, sigma1, sigma2, borderType))
CV_IPP_RUN_FAST(ipp_GaussianBlur(src, dst, ksize, sigma1, sigma2, borderType));
//CV_IPP_RUN_FAST(ipp_GaussianBlur(src, dst, ksize, sigma1, sigma2, borderType));
if(sdepth == CV_8U && ((borderType & BORDER_ISOLATED) || !_src.getMat().isSubmatrix()))
{

4
modules/videoio/src/cap_v4l.cpp
Unescape View File

@ -262,6 +262,10 @@ typedef uint32_t __u32;
#define V4L2_CID_IRIS_ABSOLUTE (V4L2_CID_CAMERA_CLASS_BASE+17)
#endif
#ifndef V4L2_PIX_FMT_Y10
#define V4L2_PIX_FMT_Y10 v4l2_fourcc('Y', '1', '0', ' ')
#endif
/* Defaults - If your board can do better, set it here. Set for the most common type inputs. */
#define DEFAULT_V4L_WIDTH 640
#define DEFAULT_V4L_HEIGHT 480

4
modules/videoio/test/test_video_io.cpp
Unescape View File

@ -84,6 +84,8 @@ public:
{
if (!videoio_registry::hasBackend(apiPref))
throw SkipTestException(cv::String("Backend is not available/disabled: ") + cv::videoio_registry::getBackendName(apiPref));
if (cvtest::skipUnstableTests && apiPref == CAP_MSMF && (ext == "h264" || ext == "h265"))
throw SkipTestException("Unstable MSMF test");
writeVideo();
VideoCapture cap;
ASSERT_NO_THROW(cap.open(video_file, apiPref));
@ -170,6 +172,8 @@ public:
{
if (!videoio_registry::hasBackend(apiPref))
throw SkipTestException(cv::String("Backend is not available/disabled: ") + cv::videoio_registry::getBackendName(apiPref));
if (cvtest::skipUnstableTests && apiPref == CAP_MSMF && (ext == "h264" || ext == "h265"))
throw SkipTestException("Unstable MSMF test");
VideoCapture cap;
EXPECT_NO_THROW(cap.open(video_file, apiPref));
if (!cap.isOpened())

4
platforms/wince/arm-wince-headless-overrides.cmake
Unescape View File

@ -3,10 +3,10 @@ if(WINCE)
# Try_Compile succeed and therefore also C/C++ ABI Detetection work
# https://gitlab.kitware.com/cmake/cmake/blob/master/Modules/Platform/Windows-
# MSVC.cmake
set(CMAKE_C_STANDARD_LIBRARIES_INIT "coredll.lib")
set(CMAKE_C_STANDARD_LIBRARIES_INIT "coredll.lib oldnames.lib")
set(CMAKE_CXX_STANDARD_LIBRARIES_INIT ${CMAKE_C_STANDARD_LIBRARIES_INIT})
foreach(ID EXE SHARED MODULE)
string(APPEND CMAKE_${ID}_LINKER_FLAGS_INIT
" /NODEFAULTLIB:libc.lib /NODEFAULTLIB:oldnames.lib")
" /NODEFAULTLIB:libc.lib")
endforeach()
endif()

8
platforms/wince/readme.md
Unescape View File

@ -57,6 +57,14 @@ For headless WEC2013, this configuration may not be limited to but is known to w
-DWITH_TIFF=OFF `
```
## Configuring to build as shared
Building OpenCV as shared libraries is as easy as appending
```
-DBUILD_SHARED_LIBS=ON `
-DBUILD_ZLIB=ON
```
to the build configuration.
## Building
You are required to build using Unicode:
`cmake --build . -- /p:CharacterSet=Unicode`

1
samples/dnn/face_detector/deploy.prototxt
Unescape View File

@ -1785,5 +1785,6 @@ layer {
code_type: CENTER_SIZE
keep_top_k: 200
confidence_threshold: 0.01
clip: 1
}
}

10
samples/dnn/face_detector/opencv_face_detector.pbtxt
Unescape View File

@ -1221,7 +1221,7 @@ node {
attr {
key: "padding"
value {
s: "SAME"
s: "VALID"
}
}
attr {
@ -1311,7 +1311,7 @@ node {
attr {
key: "padding"
value {
s: "SAME"
s: "VALID"
}
}
attr {
@ -2337,6 +2337,12 @@ node {
i: 400
}
}
attr {
key: "clip"
value {
b: true
}
}
}
node {
name: "reshape_before_softmax"

5
samples/dnn/face_detector/test.prototxt
Unescape View File

@ -917,7 +917,7 @@ layer {
}
convolution_param {
num_output: 128
pad: 1
pad: 0
kernel_size: 3
stride: 1
weight_filler {
@ -983,7 +983,7 @@ layer {
}
convolution_param {
num_output: 128
pad: 1
pad: 0
kernel_size: 3
stride: 1
weight_filler {
@ -1810,6 +1810,7 @@ layer {
code_type: CENTER_SIZE
keep_top_k: 200
confidence_threshold: 0.01
clip: 1
}
}
layer {

4
samples/dnn/face_detector/train.prototxt
Unescape View File

@ -1086,7 +1086,7 @@ layer {
}
convolution_param {
num_output: 128
pad: 1
pad: 0
kernel_size: 3
stride: 1
weight_filler {
@ -1600,7 +1600,7 @@ layer {
}
convolution_param {
num_output: 16
pad: 1
pad: 0
kernel_size: 3
stride: 1
weight_filler {

10
samples/dnn/tf_text_graph_ssd.py
Unescape View File

@ -67,7 +67,7 @@ def createSSDGraph(modelPath, configPath, outputPath):
'Sub', 'ResizeNearestNeighbor', 'Pad']
# Node with which prefixes should be removed
prefixesToRemove = ('MultipleGridAnchorGenerator/', 'Postprocessor/', 'Preprocessor/map')
prefixesToRemove = ('MultipleGridAnchorGenerator/', 'Concatenate/', 'Postprocessor/', 'Preprocessor/map')
# Load a config file.
config = readTextMessage(configPath)
@ -312,12 +312,16 @@ def createSSDGraph(modelPath, configPath, outputPath):
addConcatNode('PriorBox/concat', priorBoxes, 'concat/axis_flatten')
# Sigmoid for classes predictions and DetectionOutput layer
addReshape('ClassPredictor/concat', 'ClassPredictor/concat3d', [0, -1, num_classes + 1], graph_def)
sigmoid = NodeDef()
sigmoid.name = 'ClassPredictor/concat/sigmoid'
sigmoid.op = 'Sigmoid'
sigmoid.input.append('ClassPredictor/concat')
sigmoid.input.append('ClassPredictor/concat3d')
graph_def.node.extend([sigmoid])
addFlatten(sigmoid.name, sigmoid.name + '/Flatten', graph_def)
detectionOut = NodeDef()
detectionOut.name = 'detection_out'
detectionOut.op = 'DetectionOutput'
@ -326,7 +330,7 @@ def createSSDGraph(modelPath, configPath, outputPath):
detectionOut.input.append('BoxEncodingPredictor/concat')
else:
detectionOut.input.append('BoxPredictor/concat')
detectionOut.input.append(sigmoid.name)
detectionOut.input.append(sigmoid.name + '/Flatten')
detectionOut.input.append('PriorBox/concat')
detectionOut.addAttr('num_classes', num_classes + 1)

Write Preview
Loading…
Cancel
Save