"""

from __future__ import print_function
import os, os.path, sys, argparse, traceback, multiprocessing

# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner


            

Reported by Pylint.

              """

from __future__ import print_function
import os, os.path, sys, argparse, traceback, multiprocessing

# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner


            

Reported by Pylint.

              
# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner

MACOSX_DEPLOYMENT_TARGET='10.12'  # default, can be changed via command line options or environment variable

class OSXTestRunner(TestRunner):


            

Reported by Pylint.

                      return None

    def getCMakeArgs(self):
        args = TestRunner.getCMakeArgs(self)
        args = args + [
            '-DMACOSX_DEPLOYMENT_TARGET=%s' % os.environ['MACOSX_DEPLOYMENT_TARGET']
        ]
        return args


            

Reported by Pylint.

              """

from __future__ import print_function
import os, os.path, sys, argparse, traceback, multiprocessing

# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner


            

Reported by Pylint.

              
# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner

MACOSX_DEPLOYMENT_TARGET='10.12'  # default, can be changed via command line options or environment variable

class OSXTestRunner(TestRunner):


            

Reported by Pylint.

              sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from run_tests import TestRunner

MACOSX_DEPLOYMENT_TARGET='10.12'  # default, can be changed via command line options or environment variable

class OSXTestRunner(TestRunner):

    def getToolchain(self):
        return None

            

Reported by Pylint.

              
MACOSX_DEPLOYMENT_TARGET='10.12'  # default, can be changed via command line options or environment variable

class OSXTestRunner(TestRunner):

    def getToolchain(self):
        return None

    def getCMakeArgs(self):

            

Reported by Pylint.

              
class OSXTestRunner(TestRunner):

    def getToolchain(self):
        return None

    def getCMakeArgs(self):
        args = TestRunner.getCMakeArgs(self)
        args = args + [

            

Reported by Pylint.

              
class OSXTestRunner(TestRunner):

    def getToolchain(self):
        return None

    def getCMakeArgs(self):
        args = TestRunner.getCMakeArgs(self)
        args = args + [

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21

            

Reported by Pylint.

              title_window = 'Morphology Transformations Demo'
morph_op_dic = {0: cv.MORPH_OPEN, 1: cv.MORPH_CLOSE, 2: cv.MORPH_GRADIENT, 3: cv.MORPH_TOPHAT, 4: cv.MORPH_BLACKHAT}

def morphology_operations(val):
    morph_operator = cv.getTrackbarPos(title_trackbar_operator_type, title_window)
    morph_size = cv.getTrackbarPos(title_trackbar_kernel_size, title_window)
    morph_elem = 0
    val_type = cv.getTrackbarPos(title_trackbar_element_type, title_window)
    if val_type == 0:

            

Reported by Pylint.

              
def morphology_operations(val):
    morph_operator = cv.getTrackbarPos(title_trackbar_operator_type, title_window)
    morph_size = cv.getTrackbarPos(title_trackbar_kernel_size, title_window)
    morph_elem = 0
    val_type = cv.getTrackbarPos(title_trackbar_element_type, title_window)
    if val_type == 0:
        morph_elem = cv.MORPH_RECT
    elif val_type == 1:

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21

            

Reported by Pylint.

              import numpy as np
import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21
title_trackbar_operator_type = 'Operator:\n 0: Opening - 1: Closing  \n 2: Gradient - 3: Top Hat \n 4: Black Hat'
title_trackbar_element_type = 'Element:\n 0: Rect - 1: Cross - 2: Ellipse'

            

Reported by Pylint.

              import argparse

morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21
title_trackbar_operator_type = 'Operator:\n 0: Opening - 1: Closing  \n 2: Gradient - 3: Top Hat \n 4: Black Hat'
title_trackbar_element_type = 'Element:\n 0: Rect - 1: Cross - 2: Ellipse'
title_trackbar_kernel_size = 'Kernel size:\n 2n + 1'

            

Reported by Pylint.

              
morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21
title_trackbar_operator_type = 'Operator:\n 0: Opening - 1: Closing  \n 2: Gradient - 3: Top Hat \n 4: Black Hat'
title_trackbar_element_type = 'Element:\n 0: Rect - 1: Cross - 2: Ellipse'
title_trackbar_kernel_size = 'Kernel size:\n 2n + 1'
title_window = 'Morphology Transformations Demo'

            

Reported by Pylint.

              morph_size = 0
max_operator = 4
max_elem = 2
max_kernel_size = 21
title_trackbar_operator_type = 'Operator:\n 0: Opening - 1: Closing  \n 2: Gradient - 3: Top Hat \n 4: Black Hat'
title_trackbar_element_type = 'Element:\n 0: Rect - 1: Cross - 2: Ellipse'
title_trackbar_kernel_size = 'Kernel size:\n 2n + 1'
title_window = 'Morphology Transformations Demo'
morph_op_dic = {0: cv.MORPH_OPEN, 1: cv.MORPH_CLOSE, 2: cv.MORPH_GRADIENT, 3: cv.MORPH_TOPHAT, 4: cv.MORPH_BLACKHAT}

            

Reported by Pylint.

              import org.opencv.core.Point3;
import org.opencv.test.OpenCVTestCase;

public class Point3Test extends OpenCVTestCase {

    private Point3 p1;
    private Point3 p2;

    @Override

            

Reported by PMD.

              
public class Point3Test extends OpenCVTestCase {

    private Point3 p1;
    private Point3 p2;

    @Override
    protected void setUp() throws Exception {
        super.setUp();

            

Reported by PMD.

              public class Point3Test extends OpenCVTestCase {

    private Point3 p1;
    private Point3 p2;

    @Override
    protected void setUp() throws Exception {
        super.setUp();


            

Reported by PMD.

                  private Point3 p1;
    private Point3 p2;

    @Override
    protected void setUp() throws Exception {
        super.setUp();

        p1 = new Point3(2, 2, 2);
        p2 = new Point3(1, 1, 1);

            

Reported by PMD.

                      p2 = new Point3(1, 1, 1);
    }

    public void testClone() {
        Point3 truth = new Point3(1, 1, 1);
        p1 = truth.clone();
        assertEquals(truth, p1);
    }


            

Reported by PMD.

                      assertEquals(truth, p1);
    }

    public void testCross() {
        Point3 dstPoint = p1.cross(p2);
        Point3 truth = new Point3(0, 0, 0);
        assertEquals(truth, dstPoint);
    }


            

Reported by PMD.

                      assertEquals(truth, dstPoint);
    }

    public void testDot() {
        double result = p1.dot(p2);
        assertEquals(6.0, result);
    }

    public void testEqualsObject() {

            

Reported by PMD.

                      assertEquals(6.0, result);
    }

    public void testEqualsObject() {
        boolean flag = p1.equals(p1);
        assertTrue(flag);

        flag = p1.equals(p2);
        assertFalse(flag);

            

Reported by PMD.

                      assertEquals(6.0, result);
    }

    public void testEqualsObject() {
        boolean flag = p1.equals(p1);
        assertTrue(flag);

        flag = p1.equals(p2);
        assertFalse(flag);

            

Reported by PMD.

                      assertFalse(flag);
    }

    public void testHashCode() {
        assertEquals(p1.hashCode(), p1.hashCode());
    }

    public void testPoint3() {
        p1 = new Point3();

            

Reported by PMD.

              # Python 2/3 compatibility
from __future__ import print_function

import cv2 as cv
import numpy as np

from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):

            

Reported by Pylint.

              import cv2 as cv
import numpy as np

from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()

            

Reported by Pylint.

              from __future__ import print_function

import cv2 as cv
import numpy as np

from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):

            

Reported by Pylint.

                          results2 = dict([(t, cv.goodFeaturesToTrack(arr, numPoints, t, 2, useHarrisDetector=True)) for t in threshes])
            for t in threshes:
                self.assertTrue(len(results2[t]) == len(results[t]))
                for i in range(len(results[t])):
                    self.assertTrue(cv.norm(results[t][i][0] - results2[t][i][0]) == 0)

        for t0,t1 in zip(threshes, threshes[1:]):
            r0 = results[t0]
            r1 = results[t1]

            

Reported by Pylint.

              #!/usr/bin/env python

# Python 2/3 compatibility
from __future__ import print_function

import cv2 as cv
import numpy as np

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()
        threshes = [ x / 100. for x in range(1,10) ]
        numPoints = 20000

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()
        threshes = [ x / 100. for x in range(1,10) ]
        numPoints = 20000

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()
        threshes = [ x / 100. for x in range(1,10) ]
        numPoints = 20000

            

Reported by Pylint.

              from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()
        threshes = [ x / 100. for x in range(1,10) ]
        numPoints = 20000


            

Reported by Pylint.

              from tests_common import NewOpenCVTests

class TestGoodFeaturesToTrack_test(NewOpenCVTests):
    def test_goodFeaturesToTrack(self):
        arr = self.get_sample('samples/data/lena.jpg', 0)
        original = arr.copy()
        threshes = [ x / 100. for x in range(1,10) ]
        numPoints = 20000


            

Reported by Pylint.

                      String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";
        matImgSrc = Imgcodecs.imread(imagePath);
        if (matImgSrc.empty()) {
            System.out.println("Empty image: " + imagePath);
            System.exit(0);
        }

        // Create and set up the window.
        frame = new JFrame("Morphology Transformations demo");

            

Reported by PMD.

                          Imgproc.MORPH_GRADIENT, Imgproc.MORPH_TOPHAT, Imgproc.MORPH_BLACKHAT };
    private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;

            

Reported by PMD.

                          Imgproc.MORPH_GRADIENT, Imgproc.MORPH_TOPHAT, Imgproc.MORPH_BLACKHAT };
    private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;

            

Reported by PMD.

                  private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

                  private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

                  private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;


            

Reported by PMD.

                  private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

    public MorphologyDemo2(String[] args) {

            

Reported by PMD.

                  private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

    public MorphologyDemo2(String[] args) {
        String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";

            

Reported by PMD.

                  private Mat matImgDst = new Mat();
    private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

    public MorphologyDemo2(String[] args) {
        String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";

            

Reported by PMD.

                  private int morphOpType = Imgproc.MORPH_OPEN;
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private JFrame frame;
    private JLabel imgLabel;

    public MorphologyDemo2(String[] args) {
        String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";
        matImgSrc = Imgcodecs.imread(imagePath);

            

Reported by PMD.

              
import numpy as np

from .configs.test_config import CommonConfig
from ..utils import create_parser, plot_acc


class ModelTestPipeline:
    def __init__(

            

Reported by Pylint.

              import numpy as np

from .configs.test_config import CommonConfig
from ..utils import create_parser, plot_acc


class ModelTestPipeline:
    def __init__(
            self,

            

Reported by Pylint.

                              self._test_module_config.model = self._net_model.model_path["full_path"]

            if cmd_args.default_img_preprocess:
                self._test_module_config.scale = self._default_input_blob_preproc["scale"]
                self._test_module_config.mean = self._default_input_blob_preproc["mean"]
                self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:

            

Reported by Pylint.

              
            if cmd_args.default_img_preprocess:
                self._test_module_config.scale = self._default_input_blob_preproc["scale"]
                self._test_module_config.mean = self._default_input_blob_preproc["mean"]
                self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]

            

Reported by Pylint.

                          if cmd_args.default_img_preprocess:
                self._test_module_config.scale = self._default_input_blob_preproc["scale"]
                self._test_module_config.mean = self._default_input_blob_preproc["mean"]
                self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]

            

Reported by Pylint.

                              self._test_module_config.scale = self._default_input_blob_preproc["scale"]
                self._test_module_config.mean = self._default_input_blob_preproc["mean"]
                self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]


            

Reported by Pylint.

                              self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]

                self._test_module_param_list = [
                    '--model', self._test_module_config.model,

            

Reported by Pylint.

                              self._test_module_config.std = self._default_input_blob_preproc["std"]
                self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]

                self._test_module_param_list = [
                    '--model', self._test_module_config.model,

            

Reported by Pylint.

                              self._test_module_config.crop = self._default_input_blob_preproc["crop"]

                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]

                self._test_module_param_list = [
                    '--model', self._test_module_config.model,
                    '--input', self._test_module_config.input_img,

            

Reported by Pylint.

              
                if "rsz_height" in self._default_input_blob_preproc and "rsz_width" in self._default_input_blob_preproc:
                    self._test_module_config.rsz_height = self._default_input_blob_preproc["rsz_height"]
                    self._test_module_config.rsz_width = self._default_input_blob_preproc["rsz_width"]

                self._test_module_param_list = [
                    '--model', self._test_module_config.model,
                    '--input', self._test_module_config.input_img,
                    '--width', self._test_module_config.frame_width,

            

Reported by Pylint.

                      String filename = args.length > 0 ? args[0] : "../data/building.jpg";
        Mat src = Imgcodecs.imread(filename);
        if (src.empty()) {
            System.err.println("Cannot read image: " + filename);
            System.exit(0);
        }

        Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);


            

Reported by PMD.

              import org.opencv.imgproc.Imgproc;

class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

              import org.opencv.imgproc.Imgproc;

class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

              
class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;

            

Reported by PMD.

              
class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;

            

Reported by PMD.

              class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;
    private static final int MAX_THRESHOLD = 255;

            

Reported by PMD.

              class CornerHarris {
    private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;
    private static final int MAX_THRESHOLD = 255;

            

Reported by PMD.

                  private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;
    private static final int MAX_THRESHOLD = 255;
    private int threshold = 200;

            

Reported by PMD.

                  private Mat srcGray = new Mat();
    private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;
    private static final int MAX_THRESHOLD = 255;
    private int threshold = 200;

            

Reported by PMD.

                  private Mat dst = new Mat();
    private Mat dstNorm = new Mat();
    private Mat dstNormScaled = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private JLabel cornerLabel;
    private static final int MAX_THRESHOLD = 255;
    private int threshold = 200;


            

Reported by PMD.

                      String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";
        matImgSrc = Imgcodecs.imread(imagePath);
        if (matImgSrc.empty()) {
            System.out.println("Empty image: " + imagePath);
            System.exit(0);
        }

        // Create and set up the window.
        frame = new JFrame("Erosion and dilatation demo");

            

Reported by PMD.

                  private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final String[] MORPH_OP = { "Erosion", "Dilatation" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;

            

Reported by PMD.

                  private static final String[] ELEMENT_TYPE = { "Rectangle", "Cross", "Ellipse" };
    private static final String[] MORPH_OP = { "Erosion", "Dilatation" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;

            

Reported by PMD.

                  private static final String[] MORPH_OP = { "Erosion", "Dilatation" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

                  private static final String[] MORPH_OP = { "Erosion", "Dilatation" };
    private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

            

Reported by PMD.

                  private static final int MAX_KERNEL_SIZE = 21;
    private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;


            

Reported by PMD.

                  private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

    //! [constructor]

            

Reported by PMD.

                  private Mat matImgSrc;
    private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

    //! [constructor]

            

Reported by PMD.

                  private Mat matImgDst = new Mat();
    private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

    //! [constructor]
    public MorphologyDemo1(String[] args) {

            

Reported by PMD.

                  private int elementType = Imgproc.CV_SHAPE_RECT;
    private int kernelSize = 0;
    private boolean doErosion = true;
    private JFrame frame;
    private JLabel imgLabel;

    //! [constructor]
    public MorphologyDemo1(String[] args) {
        String imagePath = args.length > 0 ? args[0] : "../data/LinuxLogo.jpg";

            

Reported by PMD.

              
        Mat src1, src2, dst = new Mat();

        System.out.println(" Simple Linear Blender ");
        System.out.println("-----------------------");
        System.out.println("* Enter alpha [0.0-1.0]: ");
        Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
        input = scan.nextDouble();


            

Reported by PMD.

                      Mat src1, src2, dst = new Mat();

        System.out.println(" Simple Linear Blender ");
        System.out.println("-----------------------");
        System.out.println("* Enter alpha [0.0-1.0]: ");
        Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
        input = scan.nextDouble();

        if( input >= 0.0 && input <= 1.0 )

            

Reported by PMD.

              
        System.out.println(" Simple Linear Blender ");
        System.out.println("-----------------------");
        System.out.println("* Enter alpha [0.0-1.0]: ");
        Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
        input = scan.nextDouble();

        if( input >= 0.0 && input <= 1.0 )
            alpha = input;

            

Reported by PMD.

                      src2 = Imgcodecs.imread("../../images/WindowsLogo.jpg");
        //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);

            

Reported by PMD.

                      //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);
        //! [blend_images]

            

Reported by PMD.

                      System.out.println(" Simple Linear Blender ");
        System.out.println("-----------------------");
        System.out.println("* Enter alpha [0.0-1.0]: ");
        Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
        input = scan.nextDouble();

        if( input >= 0.0 && input <= 1.0 )
            alpha = input;


            

Reported by PMD.

                      src2 = Imgcodecs.imread("../../images/WindowsLogo.jpg");
        //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);

            

Reported by PMD.

                      src2 = Imgcodecs.imread("../../images/WindowsLogo.jpg");
        //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);

            

Reported by PMD.

                      //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);
        //! [blend_images]

            

Reported by PMD.

                      //! [load]

        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}

        //! [blend_images]
        beta = ( 1.0 - alpha );
        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);
        //! [blend_images]

            

Reported by PMD.

              import argparse
import os.path
import numpy as np
import cv2 as cv

backends = (cv.dnn.DNN_BACKEND_DEFAULT,
    cv.dnn.DNN_BACKEND_INFERENCE_ENGINE,
    cv.dnn.DNN_BACKEND_OPENCV,
    cv.dnn.DNN_BACKEND_VKCOM,

            

Reported by Pylint.

                  images = np.array(img_list)
    images = (images / 255.0 - MEAN) / STD

    input = cv.dnn.blobFromImages(images.astype(np.float32), ddepth = cv.CV_32F)
    return input

def extract_feature(img_dir, model_path, batch_size = 32, resize_h = 384, resize_w = 128, backend=cv.dnn.DNN_BACKEND_OPENCV, target=cv.dnn.DNN_TARGET_CPU):
    """
    Extract features from images in a target directory

            

Reported by Pylint.

                  dist = np.matmul(array1, array2.T)
    return dist

def topk(query_feat, gallery_feat, topk = 5):
    """
    Return the index of top K gallery images most similar to the query images
    :param query_feat: array of feature vectors of query images
    :param gallery_feat: array of feature vectors of gallery images
    :param topk: number of gallery images to return

            

Reported by Pylint.

                  dist = np.matmul(array1, array2.T)
    return dist

def topk(query_feat, gallery_feat, topk = 5):
    """
    Return the index of top K gallery images most similar to the query images
    :param query_feat: array of feature vectors of query images
    :param gallery_feat: array of feature vectors of gallery images
    :param topk: number of gallery images to return

            

Reported by Pylint.

                  dist = np.matmul(array1, array2.T)
    return dist

def topk(query_feat, gallery_feat, topk = 5):
    """
    Return the index of top K gallery images most similar to the query images
    :param query_feat: array of feature vectors of query images
    :param gallery_feat: array of feature vectors of gallery images
    :param topk: number of gallery images to return

            

Reported by Pylint.

                  return ret


def visualization(topk_idx, query_names, gallery_names, output_dir = 'vis'):
    """
    Visualize the retrieval results with the person ReID model
    :param topk_idx: the index of ranked gallery images for each query image
    :param query_names: the list of paths of query images
    :param gallery_names: the list of paths of gallery images

            

Reported by Pylint.

                  return ret


def visualization(topk_idx, query_names, gallery_names, output_dir = 'vis'):
    """
    Visualize the retrieval results with the person ReID model
    :param topk_idx: the index of ranked gallery images for each query image
    :param query_names: the list of paths of query images
    :param gallery_names: the list of paths of gallery images

            

Reported by Pylint.

                  return ret


def visualization(topk_idx, query_names, gallery_names, output_dir = 'vis'):
    """
    Visualize the retrieval results with the person ReID model
    :param topk_idx: the index of ranked gallery images for each query image
    :param query_names: the list of paths of query images
    :param gallery_names: the list of paths of gallery images

            

Reported by Pylint.

                  input = cv.dnn.blobFromImages(images.astype(np.float32), ddepth = cv.CV_32F)
    return input

def extract_feature(img_dir, model_path, batch_size = 32, resize_h = 384, resize_w = 128, backend=cv.dnn.DNN_BACKEND_OPENCV, target=cv.dnn.DNN_TARGET_CPU):
    """
    Extract features from images in a target directory
    :param img_dir: the input image directory
    :param model_path: path to ReID model
    :param batch_size: the batch size for each network inference iteration

            

Reported by Pylint.

                  input = cv.dnn.blobFromImages(images.astype(np.float32), ddepth = cv.CV_32F)
    return input

def extract_feature(img_dir, model_path, batch_size = 32, resize_h = 384, resize_w = 128, backend=cv.dnn.DNN_BACKEND_OPENCV, target=cv.dnn.DNN_TARGET_CPU):
    """
    Extract features from images in a target directory
    :param img_dir: the input image directory
    :param model_path: path to ReID model
    :param batch_size: the batch size for each network inference iteration

            

Reported by Pylint.