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JavaScript bindings for dnn module

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This commit is contained in:
Dmitry Kurtaev
2017-12-02 23:52:35 +03:00
parent 6185f7209e
commit f503515082
14 changed files with 326 additions and 57 deletions
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modules/js/src/core_bindings.cpp
+5 -3
View File
@@ -73,11 +73,13 @@
#include "opencv2/video/tracking.hpp"
#include "opencv2/video/background_segm.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/dnn.hpp"
#include <emscripten/bind.h>
using namespace emscripten;
using namespace cv;
using namespace dnn;
namespace binding_utils
{
@@ -339,12 +341,12 @@ EMSCRIPTEN_BINDINGS(binding_utils)
.constructor<int, int, int, const Scalar&>()
.constructor(&binding_utils::createMat, allow_raw_pointers())
.class_function("eye", select_overload<Mat(int, int, int)>(&binding_utils::matEye))
.class_function("eye", select_overload<Mat(Size, int)>(&binding_utils::matEye))
.class_function("ones", select_overload<Mat(int, int, int)>(&binding_utils::matOnes))
.class_function("eye", select_overload<Mat(int, int, int)>(&binding_utils::matEye))
.class_function("ones", select_overload<Mat(Size, int)>(&binding_utils::matOnes))
.class_function("zeros", select_overload<Mat(int, int, int)>(&binding_utils::matZeros))
.class_function("ones", select_overload<Mat(int, int, int)>(&binding_utils::matOnes))
.class_function("zeros", select_overload<Mat(Size, int)>(&binding_utils::matZeros))
.class_function("zeros", select_overload<Mat(int, int, int)>(&binding_utils::matZeros))
.property("rows", &cv::Mat::rows)
.property("cols", &cv::Mat::cols)
modules/js/src/embindgen.py
+4 -1
View File
@@ -125,6 +125,9 @@ video = {'': ['CamShift', 'calcOpticalFlowFarneback', 'calcOpticalFlowPyrLK', 'c
'BackgroundSubtractorMOG2': ['BackgroundSubtractorMOG2', 'apply'],
'BackgroundSubtractor': ['apply', 'getBackgroundImage']}
dnn = {'dnn_Net': ['setInput', 'forward'],
'': ['readNetFromCaffe', 'readNetFromTensorflow', 'readNetFromTorch', 'readNetFromDarknet', 'blobFromImage']}
def makeWhiteList(module_list):
wl = {}
for m in module_list:
@@ -135,7 +138,7 @@ def makeWhiteList(module_list):
wl[k] = m[k]
return wl
white_list = makeWhiteList([core, imgproc, objdetect, video])
white_list = makeWhiteList([core, imgproc, objdetect, video, dnn])
# Features to be exported
export_enums = False