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first parameter of createERFilterNM1/createERFilterNM2 is now mandatory. changed the sample program to use the new prototypes

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lluis
2013-09-13 16:29:21 +02:00
parent 75fdfba281
commit d25309f82e
3 changed files with 10 additions and 18 deletions
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16
modules/objdetect/src/erfilter.cpp
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@@ -1056,8 +1056,8 @@ double ERClassifierNM2::eval(const ERStat& stat)
local minimum is greater than minProbabilityDiff).
\param cb Callback with the classifier.
if omitted tries to load a default classifier from file trained_classifierNM1.xml
default classifier can be implicitly load with function loadClassifierNM1()
from file in samples/cpp/trained_classifierNM1.xml
\param thresholdDelta Threshold step in subsequent thresholds when extracting the component tree
\param minArea The minimum area (% of image size) allowed for retreived ER's
\param minArea The maximum area (% of image size) allowed for retreived ER's
@@ -1077,12 +1077,7 @@ Ptr<ERFilter> createERFilterNM1(const Ptr<ERFilter::Callback>& cb, int threshold
Ptr<ERFilterNM> filter = makePtr<ERFilterNM>();
if (cb == NULL)
filter->setCallback(makePtr<ERClassifierNM1>("trained_classifierNM1.xml"));
else
filter->setCallback(cb);
filter->setCallback(cb);
filter->setThresholdDelta(thresholdDelta);
filter->setMinArea(minArea);
@@ -1103,8 +1098,8 @@ Ptr<ERFilter> createERFilterNM1(const Ptr<ERFilter::Callback>& cb, int threshold
additional features: hole area ratio, convex hull ratio, and number of outer inflexion points.
\param cb Callback with the classifier
if omitted tries to load a default classifier from file trained_classifierNM2.xml
default classifier can be implicitly load with function loadClassifierNM1()
from file in samples/cpp/trained_classifierNM2.xml
\param minProbability The minimum probability P(er|character) allowed for retreived ER's
*/
Ptr<ERFilter> createERFilterNM2(const Ptr<ERFilter::Callback>& cb, float minProbability)
@@ -1114,10 +1109,7 @@ Ptr<ERFilter> createERFilterNM2(const Ptr<ERFilter::Callback>& cb, float minProb
Ptr<ERFilterNM> filter = makePtr<ERFilterNM>();
if (cb == NULL)
filter->setCallback(makePtr<ERClassifierNM2>("trained_classifierNM2.xml"));
else
filter->setCallback(cb);
filter->setCallback(cb);
filter->setMinProbability(minProbability);
return (Ptr<ERFilter>)filter;