// Check if image is loaded fine
        if( src.empty() ) {
            System.out.println("Error opening image!");
            System.out.println("Program Arguments: [image_name -- default ../data/lena.jpg] \n");
            System.exit(-1);
        }
        //! [load]


            

Reported by PMD.

                      // Check if image is loaded fine
        if( src.empty() ) {
            System.out.println("Error opening image!");
            System.out.println("Program Arguments: [image_name -- default ../data/lena.jpg] \n");
            System.exit(-1);
        }
        //! [load]

        //! [init_arguments]

            

Reported by PMD.

                      src = Imgcodecs.imread(imageName, Imgcodecs.IMREAD_COLOR);

        // Check if image is loaded fine
        if( src.empty() ) {
            System.out.println("Error opening image!");
            System.out.println("Program Arguments: [image_name -- default ../data/lena.jpg] \n");
            System.exit(-1);
        }
        //! [load]

            

Reported by PMD.

                      if( src.empty() ) {
            System.out.println("Error opening image!");
            System.out.println("Program Arguments: [image_name -- default ../data/lena.jpg] \n");
            System.exit(-1);
        }
        //! [load]

        //! [init_arguments]
        // Initialize arguments for the filter

            

Reported by PMD.

                          // Update kernel size for a normalized box filter
            kernel_size = 3 + 2*( ind%5 );
            Mat ones = Mat.ones( kernel_size, kernel_size, CvType.CV_32F );
            Core.multiply(ones, new Scalar(1/(double)(kernel_size*kernel_size)), kernel);
            //! [update_kernel]

            //! [apply_filter]
            // Apply filter
            Imgproc.filter2D(src, dst, ddepth , kernel, anchor, delta, Core.BORDER_DEFAULT );

            

Reported by PMD.

              
            int c = HighGui.waitKey(500);
            // Press 'ESC' to exit the program
            if( c == 27 )
            { break; }

            ind++;
        }


            

Reported by PMD.

                          ind++;
        }

        System.exit(0);
    }
}

public class Filter2D_Demo {
    public static void main(String[] args) {

            

Reported by PMD.

                  }
}

public class Filter2D_Demo {
    public static void main(String[] args) {
        // Load the native library.
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
        new Filter2D_DemoRun().run(args);
    }

            

Reported by PMD.

               * @brief Sample code that shows how to implement your own linear filters by using filter2D function
 */

import org.opencv.core.*;
import org.opencv.core.Point;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;


            

Reported by PMD.

              
class Filter2D_DemoRun {

    public void run(String[] args) {
        // Declare variables
        Mat src, dst = new Mat();

        Mat kernel = new Mat();
        Point anchor;

            

Reported by PMD.

              ]


def longTestFilter(data, module=None):
    res = ['*', '-'] + [v for m, v, _time in data if module is None or m == module]
    return '--gtest_filter={}'.format(':'.join(res))


# Parse one xml file, filter out tests which took less than 'timeLimit' seconds

            

Reported by Pylint.

              

def longTestFilter(data, module=None):
    res = ['*', '-'] + [v for m, v, _time in data if module is None or m == module]
    return '--gtest_filter={}'.format(':'.join(res))


# Parse one xml file, filter out tests which took less than 'timeLimit' seconds
# Returns tuple: ( <module_name>, [ (<module_name>, <test_name>, <test_time>), ... ] )

            

Reported by Pylint.

              # Parse one xml file, filter out tests which took less than 'timeLimit' seconds
# Returns tuple: ( <module_name>, [ (<module_name>, <test_name>, <test_time>), ... ] )
def parseOneFile(filename, timeLimit):
    tree = ET.parse(filename)
    root = tree.getroot()

    def guess(s, delims):
        for delim in delims:
            tmp = s.partition(delim)

            

Reported by Bandit.

                          if len(tmp[1]) != 0:
                return tmp[0]
        return None
    module = guess(filename, ['_posix_', '_nt_', '__']) or root.get('cv_module_name')
    if not module:
        return (None, None)
    res = []
    for elem in root.findall('.//testcase'):
        key = '{}.{}'.format(elem.get('classname'), elem.get('name'))

            

Reported by Pylint.

                  module = guess(filename, ['_posix_', '_nt_', '__']) or root.get('cv_module_name')
    if not module:
        return (None, None)
    res = []
    for elem in root.findall('.//testcase'):
        key = '{}.{}'.format(elem.get('classname'), elem.get('name'))
        val = elem.get('time')
        if float(val) >= timeLimit:
            res.append((module, key, float(val)))

            

Reported by Pylint.

              #!/usr/bin/env python
from __future__ import print_function
import xml.etree.ElementTree as ET
from glob import glob
from pprint import PrettyPrinter as PP

LONG_TESTS_DEBUG_VALGRIND = [
    ('calib3d', 'Calib3d_InitUndistortRectifyMap.accuracy', 2017.22),
    ('dnn', 'Reproducibility*', 1000),  # large DNN models

            

Reported by Pylint.

              #!/usr/bin/env python
from __future__ import print_function
import xml.etree.ElementTree as ET
from glob import glob
from pprint import PrettyPrinter as PP

LONG_TESTS_DEBUG_VALGRIND = [
    ('calib3d', 'Calib3d_InitUndistortRectifyMap.accuracy', 2017.22),
    ('dnn', 'Reproducibility*', 1000),  # large DNN models

            

Reported by Bandit.

                  ('dnn', '*eccv16*', 1000),  # very large DNN models
    ('dnn', '*OpenPose*', 1000),  # very large DNN models
    ('dnn', '*SSD/*', 1000),  # very large DNN models
    ('gapi', 'Fluid.MemoryConsumptionDoesNotGrowOnReshape', 1000000),  # test doesn't work properly under valgrind
    ('face', 'CV_Face_FacemarkLBF.test_workflow', 10000.0), # >40min on i7
    ('features2d', 'Features2d/DescriptorImage.no_crash/3', 1000),
    ('features2d', 'Features2d/DescriptorImage.no_crash/4', 1000),
    ('features2d', 'Features2d/DescriptorImage.no_crash/5', 1000),
    ('features2d', 'Features2d/DescriptorImage.no_crash/6', 1000),

            

Reported by Pylint.

                  ('tracking', '*DistanceAndOverlap*/2', 1000.0), # faceocc2
    ('videoio', 'videoio/videoio_ffmpeg.write_big*', 1000),
    ('videoio', 'videoio_ffmpeg.parallel', 1000),
    ('videoio', '*videocapture_acceleration*', 1000), # valgrind can't track HW buffers: Conditional jump or move depends on uninitialised value(s)
    ('videoio', '*videowriter_acceleration*', 1000), # valgrind crash: set_mempolicy: Operation not permitted
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_BoostDesc_LBGM.regression', 1124.51),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG120.regression', 2198.1),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG48.regression', 1958.52),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG64.regression', 2113.12),

            

Reported by Pylint.

                  ('videoio', 'videoio/videoio_ffmpeg.write_big*', 1000),
    ('videoio', 'videoio_ffmpeg.parallel', 1000),
    ('videoio', '*videocapture_acceleration*', 1000), # valgrind can't track HW buffers: Conditional jump or move depends on uninitialised value(s)
    ('videoio', '*videowriter_acceleration*', 1000), # valgrind crash: set_mempolicy: Operation not permitted
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_BoostDesc_LBGM.regression', 1124.51),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG120.regression', 2198.1),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG48.regression', 1958.52),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG64.regression', 2113.12),
    ('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG80.regression', 2167.16),

            

Reported by Pylint.

              from __future__ import print_function

import numpy as np
import cv2 as cv

# local modules
from video import create_capture
from common import clock, draw_str


            

Reported by Pylint.

              # Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import cv2 as cv

# local modules
from video import create_capture
from common import clock, draw_str

            

Reported by Pylint.

                  args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
    try:
        video_src = video_src[0]
    except:
        video_src = 0
    args = dict(args)
    cascade_fn = args.get('--cascade', "data/haarcascades/haarcascade_frontalface_alt.xml")
    nested_fn  = args.get('--nested-cascade', "data/haarcascades/haarcascade_eye.xml")


            

Reported by Pylint.

              from common import clock, draw_str


def detect(img, cascade):
    rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30),
                                     flags=cv.CASCADE_SCALE_IMAGE)
    if len(rects) == 0:
        return []
    rects[:,2:] += rects[:,:2]

            

Reported by Pylint.

                  rects[:,2:] += rects[:,:2]
    return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt

            

Reported by Pylint.

                  return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt


            

Reported by Pylint.

                  return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt


            

Reported by Pylint.

                  return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt


            

Reported by Pylint.

                  return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt


            

Reported by Pylint.

                  for x1, y1, x2, y2 in rects:
        cv.rectangle(img, (x1, y1), (x2, y2), color, 2)

def main():
    import sys, getopt

    args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
    try:
        video_src = video_src[0]

            

Reported by Pylint.

                  xrange = range

import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
    h, w = img.shape[:2]

    for i in xrange(iter_n):

            

Reported by Pylint.

              

def main():
    import sys
    try:
        fn = sys.argv[1]
    except:
        fn = 'baboon.jpg'


            

Reported by Pylint.

              

def main():
    import sys
    try:
        fn = sys.argv[1]
    except:
        fn = 'baboon.jpg'


            

Reported by Pylint.

                  import sys
    try:
        fn = sys.argv[1]
    except:
        fn = 'baboon.jpg'

    src = cv.imread(cv.samples.findFile(fn))

    def nothing(*argv):

            

Reported by Pylint.

              
    src = cv.imread(cv.samples.findFile(fn))

    def nothing(*argv):
        pass

    def update():
        sigma = cv.getTrackbarPos('sigma', 'control')*2+1
        str_sigma = cv.getTrackbarPos('str_sigma', 'control')*2+1

            

Reported by Pylint.

              PY3 = sys.version_info[0] == 3

if PY3:
    xrange = range

import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):

            

Reported by Pylint.

              if PY3:
    xrange = range

import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
    h, w = img.shape[:2]


            

Reported by Pylint.

                  xrange = range

import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
    h, w = img.shape[:2]

    for i in xrange(iter_n):

            

Reported by Pylint.

              import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
    h, w = img.shape[:2]

    for i in xrange(iter_n):
        print(i)


            

Reported by Pylint.

              import numpy as np
import cv2 as cv

def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
    h, w = img.shape[:2]

    for i in xrange(iter_n):
        print(i)


            

Reported by Pylint.

              from __future__ import print_function

import numpy as np
import cv2 as cv
import sys

from tests_common import NewOpenCVTests

class grabcut_test(NewOpenCVTests):

            

Reported by Pylint.

              
import numpy as np
import cv2 as cv
import sys

from tests_common import NewOpenCVTests

class grabcut_test(NewOpenCVTests):


            

Reported by Pylint.

                      exp_mask2 = self.get_sample("cv/grabcut/exp_mask2py.png", 0)

        if img is None:
            self.assertTrue(False, 'Missing test data')

        rect = (24, 126, 459, 168)
        mask = np.zeros(img.shape[:2], dtype = np.uint8)
        bgdModel = np.zeros((1,65),np.float64)
        fgdModel = np.zeros((1,65),np.float64)

            

Reported by Pylint.

              
import numpy as np
import cv2 as cv
import sys

from tests_common import NewOpenCVTests

class grabcut_test(NewOpenCVTests):


            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

class grabcut_test(NewOpenCVTests):

    def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

class grabcut_test(NewOpenCVTests):

    def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)

            

Reported by Pylint.

              
class grabcut_test(NewOpenCVTests):

    def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)
        nonIntersectArea = np.count_nonzero(mask != exp)
        curRatio = float(nonIntersectArea) / expArea

            

Reported by Pylint.

              
class grabcut_test(NewOpenCVTests):

    def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)
        nonIntersectArea = np.count_nonzero(mask != exp)
        curRatio = float(nonIntersectArea) / expArea

            

Reported by Pylint.

              
    def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)
        nonIntersectArea = np.count_nonzero(mask != exp)
        curRatio = float(nonIntersectArea) / expArea
        return curRatio < maxDiffRatio


            

Reported by Pylint.

                  def verify(self, mask, exp):

        maxDiffRatio = 0.02
        expArea = np.count_nonzero(exp)
        nonIntersectArea = np.count_nonzero(mask != exp)
        curRatio = float(nonIntersectArea) / expArea
        return curRatio < maxDiffRatio

    def scaleMask(self, mask):

            

Reported by Pylint.

                      Core.gemm(tmp, cameraMatrix.inv(), 1, new Mat(), 0, H);
        Scalar s = new Scalar(H.get(2, 2)[0]);
        Core.divide(H, s, H);
        System.out.println(H.dump());
        //! [compute-homography]

        //! [stitch]
        Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );

            

Reported by PMD.

              class PanoramaStitchingRotatingCameraRun {
    void basicPanoramaStitching (String[] args) {
        String img1path = args[0], img2path = args[1];
        Mat img1 = new Mat(), img2 = new Mat();
        img1 = Imgcodecs.imread(img1path);
        img2 = Imgcodecs.imread(img2path);

        //! [camera-pose-from-Blender-at-location-1]
        Mat c1Mo = new Mat( 4, 4, CvType.CV_64FC1 );

            

Reported by PMD.

              class PanoramaStitchingRotatingCameraRun {
    void basicPanoramaStitching (String[] args) {
        String img1path = args[0], img2path = args[1];
        Mat img1 = new Mat(), img2 = new Mat();
        img1 = Imgcodecs.imread(img1path);
        img2 = Imgcodecs.imread(img2path);

        //! [camera-pose-from-Blender-at-location-1]
        Mat c1Mo = new Mat( 4, 4, CvType.CV_64FC1 );

            

Reported by PMD.

              
        //! [stitch]
        Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]


            

Reported by PMD.

              
        //! [stitch]
        Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]


            

Reported by PMD.

                      //! [stitch]
        Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]

        Mat img_compare = new Mat();

            

Reported by PMD.

                      Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]

        Mat img_compare = new Mat();
        Mat img_space = Mat.zeros(new Size(50, img1.rows()), CvType.CV_8UC3);

            

Reported by PMD.

                      Mat img_stitch = new Mat();
        Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]

        Mat img_compare = new Mat();
        Mat img_space = Mat.zeros(new Size(50, img1.rows()), CvType.CV_8UC3);

            

Reported by PMD.

                      Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) );
        Mat half = new Mat();
        half =  new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows()));
        img1.copyTo(half);
        //! [stitch]

        Mat img_compare = new Mat();
        Mat img_space = Mat.zeros(new Size(50, img1.rows()), CvType.CV_8UC3);
        List<Mat>list = new ArrayList<>();

            

Reported by PMD.

                      //! [stitch]

        Mat img_compare = new Mat();
        Mat img_space = Mat.zeros(new Size(50, img1.rows()), CvType.CV_8UC3);
        List<Mat>list = new ArrayList<>();
        list.add(img1);
        list.add(img_space);
        list.add(img2);
        Core.hconcat(list, img_compare);

            

Reported by PMD.

                      self.children = [] # ordered titles
        self.prev = None
        self.next = None
        with open(path, "rt") as f:
            self.parse(f)

    def parse(self, f):
        rx_title = re.compile(r"\{#(\w+)\}")
        rx_subpage = re.compile(r"@subpage\s+(\w+)")

            

Reported by Pylint.

                      with open(path, "rt") as f:
            self.parse(f)

    def parse(self, f):
        rx_title = re.compile(r"\{#(\w+)\}")
        rx_subpage = re.compile(r"@subpage\s+(\w+)")
        rx_prev = re.compile(r"@prev_tutorial\{(\w+)\}")
        rx_next = re.compile(r"@next_tutorial\{(\w+)\}")
        for line in f:

            

Reported by Pylint.

                              continue

    def verify_prev_next(self, storage):
        res = True

        if self.title is None:
            print("[W] No title")
            res = False


            

Reported by Pylint.

                              res = False
            prev = c.title

        next = None
        for one in reversed(self.children):
            c = storage[one]
            if c.next is not None and c.next != next:
                print("[W] Wrong next_tutorial: expected {} / actual {}".format(c.next, next))
                res = False

            

Reported by Pylint.

              #!/usr/bin/env python

from pathlib import Path
import re

# Tasks
# 1. Find all tutorials
# 2. Generate tree (@subpage)
# 3. Check prev/next nodes

            

Reported by Pylint.

              # 2. Generate tree (@subpage)
# 3. Check prev/next nodes

class Tutorial(object):
    def __init__(self, path):
        self.path = path
        self.title = None # doxygen title
        self.children = [] # ordered titles
        self.prev = None

            

Reported by Pylint.

              # 2. Generate tree (@subpage)
# 3. Check prev/next nodes

class Tutorial(object):
    def __init__(self, path):
        self.path = path
        self.title = None # doxygen title
        self.children = [] # ordered titles
        self.prev = None

            

Reported by Pylint.

                      self.children = [] # ordered titles
        self.prev = None
        self.next = None
        with open(path, "rt") as f:
            self.parse(f)

    def parse(self, f):
        rx_title = re.compile(r"\{#(\w+)\}")
        rx_subpage = re.compile(r"@subpage\s+(\w+)")

            

Reported by Pylint.

                      with open(path, "rt") as f:
            self.parse(f)

    def parse(self, f):
        rx_title = re.compile(r"\{#(\w+)\}")
        rx_subpage = re.compile(r"@subpage\s+(\w+)")
        rx_prev = re.compile(r"@prev_tutorial\{(\w+)\}")
        rx_next = re.compile(r"@next_tutorial\{(\w+)\}")
        for line in f:

            

Reported by Pylint.

                      with open(path, "rt") as f:
            self.parse(f)

    def parse(self, f):
        rx_title = re.compile(r"\{#(\w+)\}")
        rx_subpage = re.compile(r"@subpage\s+(\w+)")
        rx_prev = re.compile(r"@prev_tutorial\{(\w+)\}")
        rx_next = re.compile(r"@next_tutorial\{(\w+)\}")
        for line in f:

            

Reported by Pylint.

              public class ColorBlobDetectionActivity extends CameraActivity implements OnTouchListener, CvCameraViewListener2 {
    private static final String  TAG              = "OCVSample::Activity";

    private boolean              mIsColorSelected = false;
    private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;

            

Reported by PMD.

              public class ColorBlobDetectionActivity extends CameraActivity implements OnTouchListener, CvCameraViewListener2 {
    private static final String  TAG              = "OCVSample::Activity";

    private boolean              mIsColorSelected = false;
    private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;

            

Reported by PMD.

                  private static final String  TAG              = "OCVSample::Activity";

    private boolean              mIsColorSelected = false;
    private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;

            

Reported by PMD.

              
    private boolean              mIsColorSelected = false;
    private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

            

Reported by PMD.

                  private boolean              mIsColorSelected = false;
    private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;


            

Reported by PMD.

                  private Mat                  mRgba;
    private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

    private CameraBridgeViewBase mOpenCvCameraView;

            

Reported by PMD.

                  private Scalar               mBlobColorRgba;
    private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

    private CameraBridgeViewBase mOpenCvCameraView;


            

Reported by PMD.

                  private Scalar               mBlobColorHsv;
    private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

    private CameraBridgeViewBase mOpenCvCameraView;

    private BaseLoaderCallback  mLoaderCallback = new BaseLoaderCallback(this) {

            

Reported by PMD.

                  private ColorBlobDetector    mDetector;
    private Mat                  mSpectrum;
    private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

    private CameraBridgeViewBase mOpenCvCameraView;

    private BaseLoaderCallback  mLoaderCallback = new BaseLoaderCallback(this) {
        @Override

            

Reported by PMD.

                  private Size                 SPECTRUM_SIZE;
    private Scalar               CONTOUR_COLOR;

    private CameraBridgeViewBase mOpenCvCameraView;

    private BaseLoaderCallback  mLoaderCallback = new BaseLoaderCallback(this) {
        @Override
        public void onManagerConnected(int status) {
            switch (status) {

            

Reported by PMD.

              from __future__ import print_function

import numpy as np
import cv2 as cv
import sys


def randomColor():
    color = np.random.randint(0, 255,(1, 3))

            

Reported by Pylint.

              #!/usr/bin/env python
# -*- coding: utf-8 -*-

# Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import cv2 as cv
import sys

            

Reported by Pylint.

              
import numpy as np
import cv2 as cv
import sys


def randomColor():
    color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

            

Reported by Pylint.

              import sys


def randomColor():
    color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))

            

Reported by Pylint.

              import sys


def randomColor():
    color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))

            

Reported by Pylint.

                  color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))
    img2 = cv.imread(cv.samples.findFile(img2Path))

    # [find-corners]
    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)

            

Reported by Pylint.

                  color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))
    img2 = cv.imread(cv.samples.findFile(img2Path))

    # [find-corners]
    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)

            

Reported by Pylint.

                  color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))
    img2 = cv.imread(cv.samples.findFile(img2Path))

    # [find-corners]
    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)

            

Reported by Pylint.

                  color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))
    img2 = cv.imread(cv.samples.findFile(img2Path))

    # [find-corners]
    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)

            

Reported by Pylint.

                  color = np.random.randint(0, 255,(1, 3))
    return color[0].tolist()

def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
    img1 = cv.imread(cv.samples.findFile(img1Path))
    img2 = cv.imread(cv.samples.findFile(img2Path))

    # [find-corners]
    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)

            

Reported by Pylint.

              #!/usr/bin/env python

import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              import sys
import unittest

from tests_common import NewOpenCVTests


try:

    if sys.version_info[:2] < (3, 0):

            

Reported by Pylint.

                      def setUp(self):
            self.skipTest('Skip tests: ' + message)

        def test_skip():
            pass

    pass



            

Reported by Pylint.

              #!/usr/bin/env python

import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              
import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests


            

Reported by Pylint.

                      def test_skip():
            pass

    pass


if __name__ == '__main__':
    NewOpenCVTests.bootstrap()

            

Reported by Pylint.

              #!/usr/bin/env python

import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              
import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests


            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests



            

Reported by Pylint.

              import cv2 as cv
import os
import sys
import unittest

from tests_common import NewOpenCVTests


try:

            

Reported by Pylint.