avoid `Ptr<> == NULL` checks

modules/bioinspired/src/retina.cpp

@@ -562,7 +562,7 @@ bool RetinaImpl::ocl_run(InputArray inputMatToConvert)
 
 void RetinaImpl::run(InputArray inputMatToConvert)
 {
-    CV_OCL_RUN((_ocl_retina != 0 && inputMatToConvert.isUMat()), ocl_run(inputMatToConvert));
+    CV_OCL_RUN((_ocl_retina && inputMatToConvert.isUMat()), ocl_run(inputMatToConvert));
 
     _wasOCLRunCalled = false;
     // first convert input image to the compatible format : std::valarray<float>
@@ -830,7 +830,7 @@ bool RetinaImpl::_convertCvMat2ValarrayBuffer(InputArray inputMat, std::valarray
 void RetinaImpl::clearBuffers()
 {
 #ifdef HAVE_OPENCL
-    if (_ocl_retina != 0)
+    if (_ocl_retina)
         _ocl_retina->clearBuffers();
 #endif
 

modules/rgbd/src/odometry.cpp

@@ -1055,8 +1055,8 @@ bool Odometry::compute(Ptr<OdometryFrame>& srcFrame, Ptr<OdometryFrame>& dstFram
 
 Size Odometry::prepareFrameCache(Ptr<OdometryFrame> &frame, int /*cacheType*/) const
 {
-    if(frame == 0)
-        CV_Error(Error::StsBadArg, "Null frame pointer.\n");
+    if (!frame)
+        CV_Error(Error::StsBadArg, "Null frame pointer.");
 
     return Size();
 }

modules/text/src/erfilter.cpp

@@ -665,12 +665,12 @@ void ERFilterNM::er_merge(ERStat *parent, ERStat *child)
     child->level = child->level*thresholdDelta;
 
     // before saving calculate P(child|character) and filter if possible
-    if (classifier != NULL)
+    if (classifier)
     {
         child->probability = classifier->eval(*child);
     }
 
-    if ( (((classifier!=NULL)?(child->probability >= minProbability):true)||(nonMaxSuppression)) &&
+    if ( (((classifier)?(child->probability >= minProbability):true)||(nonMaxSuppression)) &&
          ((child->area >= (minArea*region_mask.rows*region_mask.cols)) &&
           (child->area <= (maxArea*region_mask.rows*region_mask.cols)) &&
           (child->rect.width > 2) && (child->rect.height > 2)) )
@@ -858,12 +858,12 @@ ERStat* ERFilterNM::er_tree_filter ( InputArray image, ERStat * stat, ERStat *pa
 
 
     // calculate P(child|character) and filter if possible
-    if ( (classifier != NULL) && (stat->parent != NULL) )
+    if (classifier && (stat->parent != NULL))
     {
         stat->probability = classifier->eval(*stat);
     }
 
-    if ( ( ((classifier != NULL)?(stat->probability >= minProbability):true) &&
+    if ( ( ((classifier)?(stat->probability >= minProbability):true) &&
           ((stat->area >= minArea*region_mask.rows*region_mask.cols) &&
            (stat->area <= maxArea*region_mask.rows*region_mask.cols)) ) ||
         (stat->parent == NULL) )

modules/tracking/samples/tracker.cpp

@@ -93,7 +93,7 @@ int main( int argc, char** argv ){
 
   //instantiates the specific Tracker
   Ptr<Tracker> tracker = createTrackerByName(tracker_algorithm);
-  if( tracker == NULL )
+  if (!tracker)
   {
     cout << "***Error in the instantiation of the tracker...***\n";
     return -1;

modules/tracking/samples/tracker_dataset.cpp

@@ -145,7 +145,7 @@ int main(int argc, char *argv[])
 
 	//Create Tracker
     Ptr<Tracker> tracker = createTrackerByName(tracker_algorithm);
-	if (tracker == NULL)
+	if (!tracker)
 	{
 		cout << "***Error in the instantiation of the tracker...***\n";
 		getchar();

modules/tracking/src/multiTracker.cpp

@@ -47,7 +47,7 @@ namespace cv
     bool MultiTracker_Alt::addTarget(InputArray image, const Rect2d& boundingBox, Ptr<Tracker> tracker_algorithm)
 	{
         Ptr<Tracker> tracker = tracker_algorithm;
-		if (tracker == NULL)
+		if (!tracker)
 			return false;
 
 		if (!tracker->init(image, boundingBox))

modules/tracking/src/tracker.cpp

@@ -70,7 +70,7 @@ bool Tracker::init( InputArray image, const Rect2d& boundingBox )
   bool initTracker = initImpl( image.getMat(), boundingBox );
 
   //check if the model component is initialized
-  if( model == 0 )
+  if (!model)
   {
     CV_Error( -1, "The model is not initialized" );
   }

modules/tracking/src/trackerFeatureSet.cpp

@@ -101,7 +101,7 @@ bool TrackerFeatureSet::addTrackerFeature( String trackerFeatureType )
   }
   Ptr<TrackerFeature> feature = TrackerFeature::create( trackerFeatureType );
 
-  if( feature == 0 )
+  if (!feature)
   {
     return false;
   }

modules/tracking/src/trackerModel.cpp

@@ -61,7 +61,7 @@ TrackerModel::~TrackerModel()
 
 bool TrackerModel::setTrackerStateEstimator( Ptr<TrackerStateEstimator> trackerStateEstimator )
 {
-  if( stateEstimator != 0 )
+  if (stateEstimator.get())
   {
     return false;
   }
@@ -109,12 +109,12 @@ void TrackerModel::modelUpdate()
 
 bool TrackerModel::runStateEstimator()
 {
-  if( stateEstimator == 0 )
+  if (!stateEstimator)
   {
     CV_Error( -1, "Tracker state estimator is not setted" );
   }
   Ptr<TrackerTargetState> targetState = stateEstimator->estimate( confidenceMaps );
-  if( targetState == 0 )
+  if (!targetState)
     return false;
 
   setLastTargetState( targetState );

modules/tracking/src/trackerSampler.cpp

@@ -96,7 +96,7 @@ bool TrackerSampler::addTrackerSamplerAlgorithm( String trackerSamplerAlgorithmT
   }
   Ptr<TrackerSamplerAlgorithm> sampler = TrackerSamplerAlgorithm::create( trackerSamplerAlgorithmType );
 
-  if( sampler == 0 )
+  if (!sampler)
   {
     return false;
   }
@@ -113,7 +113,7 @@ bool TrackerSampler::addTrackerSamplerAlgorithm( Ptr<TrackerSamplerAlgorithm>& s
     return false;
   }
 
-  if( sampler == 0 )
+  if (!sampler)
   {
     return false;
   }

modules/xfeatures2d/test/test_features2d.cpp

@@ -262,14 +262,14 @@ TEST(Features2d_BruteForceDescriptorMatcher_knnMatch, regression)
     const int k = 3;
 
     Ptr<DescriptorExtractor> ext = SURF::create();
-    ASSERT_TRUE(ext != NULL);
+    ASSERT_TRUE(ext);
 
     Ptr<FeatureDetector> det = SURF::create();
     //"%YAML:1.0\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n"
-    ASSERT_TRUE(det != NULL);
+    ASSERT_TRUE(det);
 
     Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce");
-    ASSERT_TRUE(matcher != NULL);
+    ASSERT_TRUE(matcher);
 
     Mat imgT(256, 256, CV_8U, Scalar(255));
     line(imgT, Point(20, sz/2), Point(sz-21, sz/2), Scalar(100), 2);