Commit e967557e authored by David Geldreich's avatar David Geldreich
Browse files

Allows structured_light pipeline to be run from Python 

SinusoidalPattern::unwrapPhaseMap now takes an InputArray instead of InputArrayOfArrays to correct a Python binding problem
present a scriptable HistogramPhaseUnwrapping::create

replicate C++ structured_light test in Python

PhaseUnwrapping now init unwrappedPhase so pixel outside the mask area are set to 0

python binding for HistogramPhaseUnwrapping::Params to use HistogramPhaseUnwrapping::create
parent 9c0ae273

modules/phase_unwrapping/include/opencv2/phase_unwrapping/histogramphaseunwrapping.hpp

+8 −7
Original line number Diff line number Diff line
@@ -75,20 +75,21 @@ public: 
     * @param nbrOfSmallBins Number of bins between 0 and "histThresh". Default value is 10.

     * @param nbrOfLargeBins Number of bins between "histThresh" and 32*pi*pi (highest edge reliability value). Default value is 5.

     */

    struct CV_EXPORTS Params

    struct CV_EXPORTS_W_SIMPLE Params

    {

        Params();

        int width;

        int height;

        float histThresh;

        int nbrOfSmallBins;

        int nbrOfLargeBins;

        CV_WRAP Params();

        CV_PROP_RW int width;

        CV_PROP_RW int height;

        CV_PROP_RW float histThresh;

        CV_PROP_RW int nbrOfSmallBins;

        CV_PROP_RW int nbrOfLargeBins;

    };

    /**

     * @brief Constructor



     * @param parameters HistogramPhaseUnwrapping parameters HistogramPhaseUnwrapping::Params: width,height of the phase map and histogram characteristics.

     */

    CV_WRAP

    static Ptr<HistogramPhaseUnwrapping> create( const HistogramPhaseUnwrapping::Params &parameters =

                                                 HistogramPhaseUnwrapping::Params() );

modules/phase_unwrapping/misc/python/pyopencv_phase_unwrapping.hpp

0 → 100644
+3 −0
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#ifdef HAVE_OPENCV_PHASE_UNWRAPPING

typedef cv::phase_unwrapping::HistogramPhaseUnwrapping::Params HistogramPhaseUnwrapping_Params;

#endif

modules/phase_unwrapping/src/histogramphaseunwrapping.cpp

+3 −0
Original line number Diff line number Diff line
@@ -712,7 +712,10 @@ void HistogramPhaseUnwrapping_Impl::addIncrement( OutputArray unwrappedPhaseMap 
    int rows = params.height;

    int cols = params.width;

    if( uPhaseMap.empty() )

    {

        uPhaseMap.create(rows, cols, CV_32FC1);

        uPhaseMap = Scalar::all(0);

    }

    int nbrOfPixels = static_cast<int>(pixels.size());

    for( int i = 0; i < nbrOfPixels; ++i )

    {

modules/structured_light/include/opencv2/structured_light/sinusoidalpattern.hpp

+1 −1
Original line number Diff line number Diff line
@@ -119,7 +119,7 @@ public: 
     * @param shadowMask Mask used to discard shadow regions.

     */

    CV_WRAP

    virtual void unwrapPhaseMap( InputArrayOfArrays wrappedPhaseMap,

    virtual void unwrapPhaseMap( InputArray wrappedPhaseMap,

                                 OutputArray unwrappedPhaseMap,

                                 cv::Size camSize,

                                 InputArray shadowMask = noArray() ) = 0;

modules/structured_light/misc/python/test/test_structured_light.py

0 → 100644
+94 −0
Original line number Diff line number Diff line 
#!/usr/bin/env python



# Python 2/3 compatibility

from __future__ import print_function



import os, numpy



import cv2 as cv



from tests_common import NewOpenCVTests



class structured_light_test(NewOpenCVTests):



    def test_unwrap(self):

        paramsPsp = cv.structured_light_SinusoidalPattern_Params();

        paramsFtp = cv.structured_light_SinusoidalPattern_Params();

        paramsFaps = cv.structured_light_SinusoidalPattern_Params();

        paramsPsp.methodId = cv.structured_light.PSP;

        paramsFtp.methodId = cv.structured_light.FTP;

        paramsFaps.methodId = cv.structured_light.FAPS;



        sinusPsp = cv.structured_light.SinusoidalPattern_create(paramsPsp)

        sinusFtp = cv.structured_light.SinusoidalPattern_create(paramsFtp)

        sinusFaps = cv.structured_light.SinusoidalPattern_create(paramsFaps)



        captures = []

        for i in range(0,3):

            capture = self.get_sample('/cv/structured_light/data/capture_sin_%d.jpg'%i, cv.IMREAD_GRAYSCALE)

            if capture is None:

                raise unittest.SkipTest("Missing files with test data")

            captures.append(capture)



        rows,cols = captures[0].shape



        unwrappedPhaseMapPspRef = self.get_sample('/cv/structured_light/data/unwrappedPspTest.jpg',

                                                  cv.IMREAD_GRAYSCALE)

        unwrappedPhaseMapFtpRef = self.get_sample('/cv/structured_light/data/unwrappedFtpTest.jpg',

                                                  cv.IMREAD_GRAYSCALE)

        unwrappedPhaseMapFapsRef = self.get_sample('/cv/structured_light/data/unwrappedFapsTest.jpg',

                                                  cv.IMREAD_GRAYSCALE)



        wrappedPhaseMap,shadowMask = sinusPsp.computePhaseMap(captures);

        unwrappedPhaseMap = sinusPsp.unwrapPhaseMap(wrappedPhaseMap, (cols, rows), shadowMask=shadowMask)

        unwrappedPhaseMap8 = unwrappedPhaseMap*1 + 128

        unwrappedPhaseMap8 = numpy.uint8(unwrappedPhaseMap8)



        sumOfDiff = 0

        count = 0

        for i in range(rows):

            for j in range(cols):

                ref = int(unwrappedPhaseMapPspRef[i, j])

                comp = int(unwrappedPhaseMap8[i, j])

                sumOfDiff += (ref - comp)

                count += 1



        ratio = sumOfDiff/float(count)

        self.assertLessEqual(ratio, 0.2)



        wrappedPhaseMap,shadowMask = sinusFtp.computePhaseMap(captures);

        unwrappedPhaseMap = sinusFtp.unwrapPhaseMap(wrappedPhaseMap, (cols, rows), shadowMask=shadowMask)

        unwrappedPhaseMap8 = unwrappedPhaseMap*1 + 128

        unwrappedPhaseMap8 = numpy.uint8(unwrappedPhaseMap8)



        sumOfDiff = 0

        count = 0

        for i in range(rows):

            for j in range(cols):

                ref = int(unwrappedPhaseMapFtpRef[i, j])

                comp = int(unwrappedPhaseMap8[i, j])

                sumOfDiff += (ref - comp)

                count += 1



        ratio = sumOfDiff/float(count)

        self.assertLessEqual(ratio, 0.2)



        wrappedPhaseMap,shadowMask2 = sinusFaps.computePhaseMap(captures);

        unwrappedPhaseMap = sinusFaps.unwrapPhaseMap(wrappedPhaseMap, (cols, rows), shadowMask=shadowMask)

        unwrappedPhaseMap8 = unwrappedPhaseMap*1 + 128

        unwrappedPhaseMap8 = numpy.uint8(unwrappedPhaseMap8)



        sumOfDiff = 0

        count = 0

        for i in range(rows):

            for j in range(cols):

                ref = int(unwrappedPhaseMapFapsRef[i, j])

                comp = int(unwrappedPhaseMap8[i, j])

                sumOfDiff += (ref - comp)

                count += 1



        ratio = sumOfDiff/float(count)

        self.assertLessEqual(ratio, 0.2)



if __name__ == '__main__':

    NewOpenCVTests.bootstrap()