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Merge pull request #27246 from gursimarsingh:bug_fix/mcc_dnn_dependency

Fix hard dependency of dnn for mcc module. #27246

Currently building objdetect module without dnn fails due to mcc module. This PR makes the dependency optional, by checking if DNN is available in mcc module. 

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Gursimar Singh
2025-04-22 10:57:36 +05:30
committed by GitHub
parent 7c17912426
commit bbd36a0ec1
7 changed files with 69 additions and 14 deletions
+10 -5
View File
@@ -44,10 +44,13 @@ Ptr<CCheckerDetector> CCheckerDetector::create()
{
return makePtr<CCheckerDetectorImpl>();
}
#ifdef HAVE_OPENCV_DNN
Ptr<CCheckerDetector> CCheckerDetector::create(const dnn::Net& net)
{
return makePtr<CCheckerDetectorImpl>(net);
}
#endif
CCheckerDetectorImpl::
CCheckerDetectorImpl()
@@ -251,6 +254,7 @@ bool CCheckerDetectorImpl::
{
m_checkers.clear();
#ifdef HAVE_OPENCV_DNN
if (this->net.empty() || !m_useDnn)
{
return _no_net_process(image, nc, regionsOfInterest);
@@ -471,6 +475,9 @@ bool CCheckerDetectorImpl::
m_checkers.resize(min(nc, (int)m_checkers.size()));
return !m_checkers.empty();
#else
return _no_net_process(image, nc, regionsOfInterest);
#endif
}
@@ -491,7 +498,7 @@ void CCheckerDetectorImpl::setColorChartType(ColorChart chartType)
{
this->m_chartType = chartType;
}
#ifdef HAVE_OPENCV_DNN
void CCheckerDetectorImpl::setUseDnnModel(bool useDnn)
{
this->m_useDnn = useDnn;
@@ -501,7 +508,7 @@ bool CCheckerDetectorImpl::getUseDnnModel() const
{
return m_useDnn;
}
#endif
const DetectorParametersMCC& CCheckerDetectorImpl::getDetectionParams() const
{
return m_params;
@@ -1428,8 +1435,6 @@ void CCheckerDetectorImpl::
{
// color chart classic model
CChartModel cccm(m_chartType);
Mat lab;
size_t N;
std::vector<Point2f> fbox = cccm.box;
std::vector<Point2f> cellchart = cccm.cellchart;
@@ -1439,7 +1444,7 @@ void CCheckerDetectorImpl::
Mat mask(im_rgb.size(), CV_8U);
mask.setTo(Scalar::all(0));
std::vector<Point2f> bch(4), bcht(4);
N = cellchart.size() / 4;
size_t N = cellchart.size() / 4;
// Create table charts information
// |p_size|average|stddev|max|min|
@@ -45,9 +45,11 @@ class CCheckerDetectorImpl : public CCheckerDetector
public:
CCheckerDetectorImpl();
#ifdef HAVE_OPENCV_DNN
CCheckerDetectorImpl(const dnn::Net& _net){
net = _net;
}
#endif
virtual ~CCheckerDetectorImpl();
bool process(InputArray image, const std::vector<Rect> &regionsOfInterest,
@@ -72,9 +74,11 @@ public:
virtual void setColorChartType(ColorChart chartType) CV_OVERRIDE;
#ifdef HAVE_OPENCV_DNN
virtual void setUseDnnModel(bool useDnn) CV_OVERRIDE;
virtual bool getUseDnnModel() const CV_OVERRIDE;
#endif
virtual const DetectorParametersMCC& getDetectionParams() const CV_OVERRIDE;
@@ -164,10 +168,14 @@ protected: // methods pipeline
protected:
std::vector<Ptr<CChecker>> m_checkers;
#ifdef HAVE_OPENCV_DNN
dnn::Net net;
bool m_useDnn = true;
#else
bool m_useDnn = false;
#endif
DetectorParametersMCC m_params = DetectorParametersMCC();
ColorChart m_chartType;
bool m_useDnn = true;
private: // methods aux
void get_subbox_chart_physical(
+2
View File
@@ -34,7 +34,9 @@
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/3d.hpp>
#ifdef HAVE_OPENCV_DNN
#include <opencv2/dnn.hpp>
#endif
#include <vector>
#include <string>