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Commit 64f2b1b2 authored by Alexander Alekhin's avatar Alexander Alekhin
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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

parents 0d6518aa eed43a23
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Showing with 137 additions and 97 deletions
doc/py_tutorials/py_imgproc/py_thresholding/py_thresholding.markdown
View file @ 64f2b1b2
......@@ -183,7 +183,7 @@ minimizes the **weighted within-class variance** given by the relation :
where
\f[q_1(t) = \sum_{i=1}^{t} P(i) \quad \& \quad q_1(t) = \sum_{i=t+1}^{I} P(i)\f]\f[\mu_1(t) = \sum_{i=1}^{t} \frac{iP(i)}{q_1(t)} \quad \& \quad \mu_2(t) = \sum_{i=t+1}^{I} \frac{iP(i)}{q_2(t)}\f]\f[\sigma_1^2(t) = \sum_{i=1}^{t} [i-\mu_1(t)]^2 \frac{P(i)}{q_1(t)} \quad \& \quad \sigma_2^2(t) = \sum_{i=t+1}^{I} [i-\mu_1(t)]^2 \frac{P(i)}{q_2(t)}\f]
\f[q_1(t) = \sum_{i=1}^{t} P(i) \quad \& \quad q_2(t) = \sum_{i=t+1}^{I} P(i)\f]\f[\mu_1(t) = \sum_{i=1}^{t} \frac{iP(i)}{q_1(t)} \quad \& \quad \mu_2(t) = \sum_{i=t+1}^{I} \frac{iP(i)}{q_2(t)}\f]\f[\sigma_1^2(t) = \sum_{i=1}^{t} [i-\mu_1(t)]^2 \frac{P(i)}{q_1(t)} \quad \& \quad \sigma_2^2(t) = \sum_{i=t+1}^{I} [i-\mu_2(t)]^2 \frac{P(i)}{q_2(t)}\f]
It actually finds a value of t which lies in between two peaks such that variances to both classes
are minimum. It can be simply implemented in Python as follows:
......
modules/dnn/src/darknet/darknet_io.cpp
View file @ 64f2b1b2
......@@ -212,6 +212,44 @@ namespace cv {
fused_layer_names.push_back(last_layer);
}
void setAvgpool()
{
cv::dnn::LayerParams avgpool_param;
avgpool_param.set<cv::String>("pool", "ave");
avgpool_param.set<bool>("global_pooling", true);
avgpool_param.name = "Pooling-name";
avgpool_param.type = "Pooling";
darknet::LayerParameter lp;
std::string layer_name = cv::format("avgpool_%d", layer_id);
lp.layer_name = layer_name;
lp.layer_type = avgpool_param.type;
lp.layerParams = avgpool_param;
lp.bottom_indexes.push_back(last_layer);
last_layer = layer_name;
net->layers.push_back(lp);
layer_id++;
fused_layer_names.push_back(last_layer);
}
void setSoftmax()
{
cv::dnn::LayerParams softmax_param;
softmax_param.name = "Softmax-name";
softmax_param.type = "Softmax";
darknet::LayerParameter lp;
std::string layer_name = cv::format("softmax_%d", layer_id);
lp.layer_name = layer_name;
lp.layer_type = softmax_param.type;
lp.layerParams = softmax_param;
lp.bottom_indexes.push_back(last_layer);
last_layer = layer_name;
net->layers.push_back(lp);
layer_id++;
fused_layer_names.push_back(last_layer);
}
void setConcat(int number_of_inputs, int *input_indexes)
{
cv::dnn::LayerParams concat_param;
......@@ -541,6 +579,17 @@ namespace cv {
int pad = getParam<int>(layer_params, "pad", 0);
setParams.setMaxpool(kernel_size, pad, stride);
}
else if (layer_type == "avgpool")
{
setParams.setAvgpool();
}
else if (layer_type == "softmax")
{
int groups = getParam<int>(layer_params, "groups", 1);
if (groups != 1)
CV_Error(Error::StsNotImplemented, "Softmax from Darknet with groups != 1");
setParams.setSoftmax();
}
else if (layer_type == "route")
{
std::string bottom_layers = getParam<std::string>(layer_params, "layers", "");
......
modules/dnn/src/dnn.cpp
View file @ 64f2b1b2
......@@ -66,6 +66,15 @@ static bool DNN_DISABLE_MEMORY_OPTIMIZATIONS = utils::getConfigurationParameterB
static bool DNN_OPENCL_ALLOW_ALL_DEVICES = utils::getConfigurationParameterBool("OPENCV_DNN_OPENCL_ALLOW_ALL_DEVICES", false);
#endif
static int PARAM_DNN_BACKEND_DEFAULT = (int)utils::getConfigurationParameterSizeT("OPENCV_DNN_BACKEND_DEFAULT",
#ifdef HAVE_INF_ENGINE
(size_t)DNN_BACKEND_INFERENCE_ENGINE
#else
(size_t)DNN_BACKEND_OPENCV
#endif
);
using std::vector;
using std::map;
using std::make_pair;
......@@ -851,11 +860,8 @@ struct Net::Impl
CV_TRACE_FUNCTION();
if (preferableBackend == DNN_BACKEND_DEFAULT)
#ifdef HAVE_INF_ENGINE
preferableBackend = DNN_BACKEND_INFERENCE_ENGINE;
#else
preferableBackend = DNN_BACKEND_OPENCV;
#endif
preferableBackend = (Backend)PARAM_DNN_BACKEND_DEFAULT;
CV_Assert(preferableBackend != DNN_BACKEND_OPENCV ||
preferableTarget == DNN_TARGET_CPU ||
preferableTarget == DNN_TARGET_OPENCL ||
......
modules/dnn/src/tensorflow/tf_importer.cpp
View file @ 64f2b1b2
......@@ -1641,6 +1641,27 @@ void TFImporter::populateNet(Net dstNet)
connect(layer_id, dstNet, Pin(name), flattenId, 0);
}
}
else if (type == "ClipByValue")
{
// op: "ClipByValue"
// input: "input"
// input: "mix"
// input: "max"
CV_Assert(layer.input_size() == 3);
Mat minValue = getTensorContent(getConstBlob(layer, value_id, 1));
Mat maxValue = getTensorContent(getConstBlob(layer, value_id, 2));
CV_Assert(minValue.total() == 1, minValue.type() == CV_32F,
maxValue.total() == 1, maxValue.type() == CV_32F);
layerParams.set("min_value", minValue.at<float>(0));
layerParams.set("max_value", maxValue.at<float>(0));
int id = dstNet.addLayer(name, "ReLU6", layerParams);
layer_id[name] = id;
connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
}
else if (type == "Abs" || type == "Tanh" || type == "Sigmoid" ||
type == "Relu" || type == "Elu" ||
type == "Identity" || type == "Relu6")
......
modules/dnn/test/test_darknet_importer.cpp
View file @ 64f2b1b2
......@@ -228,4 +228,9 @@ TEST(Test_Darknet, upsample)
testDarknetLayer("upsample");
}
TEST(Test_Darknet, avgpool_softmax)
{
testDarknetLayer("avgpool_softmax");
}
}} // namespace
modules/dnn/test/test_tf_importer.cpp
View file @ 64f2b1b2
......@@ -415,6 +415,7 @@ TEST(Test_TensorFlow, softmax)
TEST(Test_TensorFlow, relu6)
{
runTensorFlowNet("keras_relu6");
runTensorFlowNet("keras_relu6", DNN_TARGET_CPU, /*hasText*/ true);
}
TEST(Test_TensorFlow, keras_mobilenet_head)
......
modules/photo/src/seamless_cloning.cpp
View file @ 64f2b1b2
......@@ -88,10 +88,6 @@ void cv::seamlessClone(InputArray _src, InputArray _dst, InputArray _mask, Point
int minxd = p.x - lenx/2;
int minyd = p.y - leny/2;
int maxxd = minxd + lenx;
int maxyd = minyd + leny;
CV_Assert(minxd >= 0 && minyd >= 0 && maxxd <= dest.rows && maxyd <= dest.cols);
Rect roi_d(minxd,minyd,lenx,leny);
Rect roi_s(minx,miny,lenx,leny);
......
modules/videoio/src/cap_dshow.cpp
View file @ 64f2b1b2
......@@ -3220,6 +3220,11 @@ double VideoCapture_DShow::getProperty(int propIdx) const
return g_VI.getFourcc(m_index);
case CV_CAP_PROP_FPS:
return g_VI.getFPS(m_index);
case CV_CAP_PROP_AUTOFOCUS:
// Flags indicate whether or not autofocus is enabled
if (g_VI.getVideoSettingCamera(m_index, CameraControl_Focus, min_value, max_value, stepping_delta, current_value, flags, defaultValue))
return (double)flags;
return -1;
// video filter properties
case CV_CAP_PROP_BRIGHTNESS:
......@@ -3284,6 +3289,7 @@ bool VideoCapture_DShow::setProperty(int propIdx, double propVal)
break;
case CV_CAP_PROP_FPS:
{
int fps = cvRound(propVal);
if (fps != g_VI.getFPS(m_index))
{
......@@ -3297,6 +3303,19 @@ bool VideoCapture_DShow::setProperty(int propIdx, double propVal)
return g_VI.isDeviceSetup(m_index);
}
case CV_CAP_PROP_AUTOFOCUS:
{
// Flags are required to toggle autofocus or not, but the setProperty interface does not support multiple parameters
bool enabled = cvRound(propVal) == 1;
long minFocus, maxFocus, delta, currentFocus, flags, defaultValue;
if (!g_VI.getVideoSettingCamera(m_index, CameraControl_Focus, minFocus, maxFocus, delta, currentFocus, flags, defaultValue))
{
return false;
}
return g_VI.setVideoSettingCamera(m_index, CameraControl_Focus, currentFocus, enabled ? CameraControl_Flags_Auto | CameraControl_Flags_Manual : CameraControl_Flags_Manual, enabled ? true : false);
}
}
if (handled)
{
// a stream setting
......
modules/videoio/src/cap_msmf.cpp
View file @ 64f2b1b2
......@@ -122,89 +122,36 @@ public:
T** operator&()
{
assert(p == NULL);
CV_Assert(p == NULL);
return p.operator&();
}
T* operator->() const
{
assert(p != NULL);
CV_Assert(p != NULL);
return p.operator->();
}
bool operator!() const
{
return p.operator==(NULL);
}
bool operator==(_In_opt_ T* pT) const
{
return p.operator==(pT);
}
bool operator!=(_In_opt_ T* pT) const
{
return p.operator!=(pT);
}
operator bool()
{
return p.operator!=(NULL);
}
T* const* GetAddressOf() const
{
return &p;
}
T** GetAddressOf()
{
return &p;
}
T** ReleaseAndGetAddressOf()
{
p.Release();
return &p;
}
T* Get() const
{
return p;
}
// Attach to an existing interface (does not AddRef)
void Attach(_In_opt_ T* p2)
{
p.Attach(p2);
}
// Detach the interface (does not Release)
T* Detach()
void Release()
{
return p.Detach();
}
_Check_return_ HRESULT CopyTo(_Deref_out_opt_ T** ppT)
{
assert(ppT != NULL);
if (ppT == NULL)
return E_POINTER;
*ppT = p;
if (p != NULL)
p->AddRef();
return S_OK;
if (p)
p.Release();
}
void Reset()
{
p.Release();
}
// query for U interface
template<typename U>
HRESULT As(_Inout_ U** lp) const
{
return p->QueryInterface(__uuidof(U), reinterpret_cast<void**>(lp));
}
// query for U interface
template<typename U>
HRESULT As(_Out_ ComPtr<U>* lp) const
HRESULT As(_Out_ ComPtr<U>& lp) const
{
return p->QueryInterface(__uuidof(U), reinterpret_cast<void**>(lp->ReleaseAndGetAddressOf()));
lp.Release();
return p->QueryInterface(__uuidof(U), reinterpret_cast<void**>((T**)&lp));
}
private:
_COM_SMARTPTR_TYPEDEF(T, __uuidof(T));
......@@ -734,12 +681,10 @@ void CvCapture_MSMF::close()
if (isOpen)
{
isOpen = false;
if (videoSample)
videoSample.Reset();
if (videoFileSource)
videoFileSource.Reset();
videoSample.Release();
videoFileSource.Release();
camid = -1;
filename = "";
filename.clear();
}
}
......@@ -759,7 +704,7 @@ bool CvCapture_MSMF::configureHW(bool enable)
D3D_FEATURE_LEVEL_10_1, D3D_FEATURE_LEVEL_10_0,
D3D_FEATURE_LEVEL_9_3, D3D_FEATURE_LEVEL_9_2, D3D_FEATURE_LEVEL_9_1 };
if (SUCCEEDED(D3D11CreateDevice(NULL, D3D_DRIVER_TYPE_HARDWARE, NULL, D3D11_CREATE_DEVICE_BGRA_SUPPORT | D3D11_CREATE_DEVICE_VIDEO_SUPPORT,
levels, sizeof(levels) / sizeof(*levels), D3D11_SDK_VERSION, D3DDev.GetAddressOf(), NULL, NULL)))
levels, sizeof(levels) / sizeof(*levels), D3D11_SDK_VERSION, &D3DDev, NULL, NULL)))
{
// NOTE: Getting ready for multi-threaded operation
_ComPtr<ID3D11Multithread> D3DDevMT;
......@@ -767,29 +712,29 @@ bool CvCapture_MSMF::configureHW(bool enable)
if (SUCCEEDED(D3DDev->QueryInterface(IID_PPV_ARGS(&D3DDevMT))))
{
D3DDevMT->SetMultithreadProtected(TRUE);
D3DDevMT.Reset();
if (SUCCEEDED(MFCreateDXGIDeviceManager(&mgrRToken, D3DMgr.GetAddressOf())))
D3DDevMT.Release();
if (SUCCEEDED(MFCreateDXGIDeviceManager(&mgrRToken, &D3DMgr)))
{
if (SUCCEEDED(D3DMgr->ResetDevice(D3DDev.Get(), mgrRToken)))
{
captureMode = MODE_HW;
return reopen ? camid >= 0 ? open(prevcam) : open(prevfile.c_str()) : true;
return reopen ? (prevcam >= 0 ? open(prevcam) : open(prevfile.c_str())) : true;
}
D3DMgr.Reset();
D3DMgr.Release();
}
}
D3DDev.Reset();
D3DDev.Release();
}
return false;
}
else
{
if (D3DMgr)
D3DMgr.Reset();
D3DMgr.Release();
if (D3DDev)
D3DDev.Reset();
D3DDev.Release();
captureMode = MODE_SW;
return reopen ? camid >= 0 ? open(prevcam) : open(prevfile.c_str()) : true;
return reopen ? (prevcam >= 0 ? open(prevcam) : open(prevfile.c_str())) : true;
}
#else
return !enable;
......@@ -911,7 +856,7 @@ bool CvCapture_MSMF::open(int _index)
close();
_ComPtr<IMFAttributes> msAttr = NULL;
if (SUCCEEDED(MFCreateAttributes(msAttr.GetAddressOf(), 1)) &&
if (SUCCEEDED(MFCreateAttributes(&msAttr, 1)) &&
SUCCEEDED(msAttr->SetGUID(
MF_DEVSOURCE_ATTRIBUTE_SOURCE_TYPE,
MF_DEVSOURCE_ATTRIBUTE_SOURCE_TYPE_VIDCAP_GUID
......@@ -933,10 +878,10 @@ bool CvCapture_MSMF::open(int _index)
_ComPtr<IMFAttributes> srAttr;
if (SUCCEEDED(ppDevices[ind]->ActivateObject(__uuidof(IMFMediaSource), (void**)&mSrc)) && mSrc &&
SUCCEEDED(MFCreateAttributes(&srAttr, 10)) &&
SUCCEEDED(srAttr->SetUINT32(MF_READWRITE_ENABLE_HARDWARE_TRANSFORMS, true)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_DISABLE_DXVA, false)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_ENABLE_VIDEO_PROCESSING, false)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_ENABLE_ADVANCED_VIDEO_PROCESSING, true)))
SUCCEEDED(srAttr->SetUINT32(MF_READWRITE_ENABLE_HARDWARE_TRANSFORMS, TRUE)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_DISABLE_DXVA, FALSE)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_ENABLE_VIDEO_PROCESSING, FALSE)) &&
SUCCEEDED(srAttr->SetUINT32(MF_SOURCE_READER_ENABLE_ADVANCED_VIDEO_PROCESSING, TRUE)))
{
#ifdef HAVE_DXVA
if (D3DMgr)
......@@ -1019,8 +964,7 @@ bool CvCapture_MSMF::grabFrame()
if (isOpen)
{
DWORD streamIndex, flags;
if (videoSample)
videoSample.Reset();
videoSample.Release();
HRESULT hr;
for(;;)
{
......@@ -1123,7 +1067,7 @@ bool CvCapture_MSMF::retrieveFrame(int, cv::OutputArray frame)
_ComPtr<IMF2DBuffer> buffer2d;
if (convertFormat)
{
if (SUCCEEDED(buf.As<IMF2DBuffer>(&buffer2d)))
if (SUCCEEDED(buf.As<IMF2DBuffer>(buffer2d)))
{
CV_TRACE_REGION_NEXT("lock2d");
if (SUCCEEDED(buffer2d->Lock2D(&ptr, &pitch)))
......@@ -1204,8 +1148,7 @@ bool CvCapture_MSMF::setTime(double time, bool rough)
if (SUCCEEDED(videoFileSource->GetPresentationAttribute((DWORD)MF_SOURCE_READER_MEDIASOURCE, MF_SOURCE_READER_MEDIASOURCE_CHARACTERISTICS, &var)) &&
var.vt == VT_UI4 && var.ulVal & MFMEDIASOURCE_CAN_SEEK)
{
if (videoSample)
videoSample.Reset();
videoSample.Release();
bool useGrabbing = time > 0 && !rough && !(var.ulVal & MFMEDIASOURCE_HAS_SLOW_SEEK);
PropVariantClear(&var);
sampleTime = (useGrabbing && time >= frameStep) ? (LONGLONG)floor(time + 0.5) - frameStep : (LONGLONG)floor(time + 0.5);
......@@ -1216,7 +1159,7 @@ bool CvCapture_MSMF::setTime(double time, bool rough)
if (resOK && useGrabbing)
{
LONGLONG timeborder = (LONGLONG)floor(time + 0.5) - frameStep / 2;
do { resOK = grabFrame(); videoSample.Reset(); } while (resOK && sampleTime < timeborder);
do { resOK = grabFrame(); videoSample.Release(); } while (resOK && sampleTime < timeborder);
}
return resOK;
}
......@@ -1958,7 +1901,7 @@ void CvVideoWriter_MSMF::close()
{
initiated = false;
sinkWriter->Finalize();
sinkWriter.Reset();
sinkWriter.Release();
}
}
......
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