HighGui.moveWindow( rook_window, W, 200 );

        HighGui.waitKey( 0 );
        System.exit(0);
    }

    /// Function Declaration

    /**

            

Reported by PMD.

                  //! [my_line]
}

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

            

Reported by PMD.

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

import java.util.*;
import java.util.List;

class GeometricDrawingRun{

            

Reported by PMD.

                      int shift = 0;

        /** Create some points */
        Point[] rook_points = new Point[20];
        rook_points[0]  = new Point(     W/4, 7*W/8   );
        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );

            

Reported by PMD.

              
        /** Create some points */
        Point[] rook_points = new Point[20];
        rook_points[0]  = new Point(     W/4, 7*W/8   );
        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );

            

Reported by PMD.

                      /** Create some points */
        Point[] rook_points = new Point[20];
        rook_points[0]  = new Point(     W/4, 7*W/8   );
        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
        rook_points[6]  = new Point(   3*W/4, W/8     );

            

Reported by PMD.

                      Point[] rook_points = new Point[20];
        rook_points[0]  = new Point(     W/4, 7*W/8   );
        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
        rook_points[6]  = new Point(   3*W/4, W/8     );
        rook_points[7]  = new Point( 26*W/40, W/8     );

            

Reported by PMD.

                      rook_points[0]  = new Point(     W/4, 7*W/8   );
        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
        rook_points[6]  = new Point(   3*W/4, W/8     );
        rook_points[7]  = new Point( 26*W/40, W/8     );
        rook_points[8]  = new Point( 26*W/40, W/4     );

            

Reported by PMD.

                      rook_points[1]  = new Point(   3*W/4, 7*W/8   );
        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
        rook_points[6]  = new Point(   3*W/4, W/8     );
        rook_points[7]  = new Point( 26*W/40, W/8     );
        rook_points[8]  = new Point( 26*W/40, W/4     );
        rook_points[9]  = new Point( 22*W/40, W/4     );

            

Reported by PMD.

                      rook_points[2]  = new Point(   3*W/4, 13*W/16 );
        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
        rook_points[6]  = new Point(   3*W/4, W/8     );
        rook_points[7]  = new Point( 26*W/40, W/8     );
        rook_points[8]  = new Point( 26*W/40, W/4     );
        rook_points[9]  = new Point( 22*W/40, W/4     );
        rook_points[10] = new Point( 22*W/40, W/8     );

            

Reported by PMD.

                  xrange = range

import numpy as np
import cv2 as cv

from numpy import random

def make_gaussians(cluster_n, img_size):
    points = []

            

Reported by Pylint.

              #!/usr/bin/env python

# Python 2/3 compatibility
from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3

if PY3:
    xrange = range

            

Reported by Pylint.

              PY3 = sys.version_info[0] == 3

if PY3:
    xrange = range

import numpy as np
import cv2 as cv

from numpy import random

            

Reported by Pylint.

              if PY3:
    xrange = range

import numpy as np
import cv2 as cv

from numpy import random

def make_gaussians(cluster_n, img_size):

            

Reported by Pylint.

                  xrange = range

import numpy as np
import cv2 as cv

from numpy import random

def make_gaussians(cluster_n, img_size):
    points = []

            

Reported by Pylint.

              import numpy as np
import cv2 as cv

from numpy import random

def make_gaussians(cluster_n, img_size):
    points = []
    ref_distrs = []
    for _i in xrange(cluster_n):

            

Reported by Pylint.

              
from numpy import random

def make_gaussians(cluster_n, img_size):
    points = []
    ref_distrs = []
    for _i in xrange(cluster_n):
        mean = (0.1 + 0.8*random.rand(2)) * img_size
        a = (random.rand(2, 2)-0.5)*img_size*0.1

            

Reported by Pylint.

                  ref_distrs = []
    for _i in xrange(cluster_n):
        mean = (0.1 + 0.8*random.rand(2)) * img_size
        a = (random.rand(2, 2)-0.5)*img_size*0.1
        cov = np.dot(a.T, a) + img_size*0.05*np.eye(2)
        n = 100 + random.randint(900)
        pts = random.multivariate_normal(mean, cov, n)
        points.append( pts )
        ref_distrs.append( (mean, cov) )

            

Reported by Pylint.

                      mean = (0.1 + 0.8*random.rand(2)) * img_size
        a = (random.rand(2, 2)-0.5)*img_size*0.1
        cov = np.dot(a.T, a) + img_size*0.05*np.eye(2)
        n = 100 + random.randint(900)
        pts = random.multivariate_normal(mean, cov, n)
        points.append( pts )
        ref_distrs.append( (mean, cov) )
    points = np.float32( np.vstack(points) )
    return points, ref_distrs

            

Reported by Pylint.

                  points = np.float32( np.vstack(points) )
    return points, ref_distrs

def draw_gaussain(img, mean, cov, color):
    x, y = mean
    w, u, _vt = cv.SVDecomp(cov)
    ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi)
    s1, s2 = np.sqrt(w)*3.0
    cv.ellipse(img, (int(x), int(y)), (int(s1), int(s2)), ang, 0, 360, color, 1, cv.LINE_AA)

            

Reported by Pylint.

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

public class ScalarTest extends OpenCVTestCase {

    private Scalar dstScalar;
    private Scalar s1;
    private Scalar s2;


            

Reported by PMD.

              
public class ScalarTest extends OpenCVTestCase {

    private Scalar dstScalar;
    private Scalar s1;
    private Scalar s2;

    @Override
    protected void setUp() throws Exception {

            

Reported by PMD.

              public class ScalarTest extends OpenCVTestCase {

    private Scalar dstScalar;
    private Scalar s1;
    private Scalar s2;

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

            

Reported by PMD.

              
    private Scalar dstScalar;
    private Scalar s1;
    private Scalar s2;

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


            

Reported by PMD.

                  private Scalar s1;
    private Scalar s2;

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

        s1 = new Scalar(1.0);
        s2 = Scalar.all(1.0);

            

Reported by PMD.

              
        s1 = new Scalar(1.0);
        s2 = Scalar.all(1.0);
        dstScalar = null;
    }

    public void testAll() {
        dstScalar = Scalar.all(2.0);
        Scalar truth = new Scalar(2.0, 2.0, 2.0, 2.0);

            

Reported by PMD.

                      dstScalar = null;
    }

    public void testAll() {
        dstScalar = Scalar.all(2.0);
        Scalar truth = new Scalar(2.0, 2.0, 2.0, 2.0);
        assertEquals(truth, dstScalar);
    }


            

Reported by PMD.

                      assertEquals(truth, dstScalar);
    }

    public void testClone() {
        dstScalar = s2.clone();
        assertEquals(s2, dstScalar);
    }

    public void testConj() {

            

Reported by PMD.

                      assertEquals(s2, dstScalar);
    }

    public void testConj() {
        dstScalar = s2.conj();
        Scalar truth = new Scalar(1, -1, -1, -1);
        assertEquals(truth, dstScalar);
    }


            

Reported by PMD.

                      assertEquals(truth, dstScalar);
    }

    public void testEqualsObject() {
        dstScalar = s2.clone();
        assertTrue(s2.equals(dstScalar));

        assertFalse(s2.equals(s1));
    }

            

Reported by PMD.

                      CascadeClassifier eyesCascade = new CascadeClassifier();

        if (!faceCascade.load(filenameFaceCascade)) {
            System.err.println("--(!)Error loading face cascade: " + filenameFaceCascade);
            System.exit(0);
        }
        if (!eyesCascade.load(filenameEyesCascade)) {
            System.err.println("--(!)Error loading eyes cascade: " + filenameEyesCascade);
            System.exit(0);

            

Reported by PMD.

                          System.exit(0);
        }
        if (!eyesCascade.load(filenameEyesCascade)) {
            System.err.println("--(!)Error loading eyes cascade: " + filenameEyesCascade);
            System.exit(0);
        }

        VideoCapture capture = new VideoCapture(cameraDevice);
        if (!capture.isOpened()) {

            

Reported by PMD.

              
        VideoCapture capture = new VideoCapture(cameraDevice);
        if (!capture.isOpened()) {
            System.err.println("--(!)Error opening video capture");
            System.exit(0);
        }

        Mat frame = new Mat();
        while (capture.read(frame)) {

            

Reported by PMD.

                      Mat frame = new Mat();
        while (capture.read(frame)) {
            if (frame.empty()) {
                System.err.println("--(!) No captured frame -- Break!");
                break;
            }

            //-- 3. Apply the classifier to the frame
            detectAndDisplay(frame, faceCascade, eyesCascade);

            

Reported by PMD.

              import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;

class ObjectDetection {
    public void detectAndDisplay(Mat frame, CascadeClassifier faceCascade, CascadeClassifier eyesCascade) {
        Mat frameGray = new Mat();
        Imgproc.cvtColor(frame, frameGray, Imgproc.COLOR_BGR2GRAY);
        Imgproc.equalizeHist(frameGray, frameGray);


            

Reported by PMD.

              import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;

class ObjectDetection {
    public void detectAndDisplay(Mat frame, CascadeClassifier faceCascade, CascadeClassifier eyesCascade) {
        Mat frameGray = new Mat();
        Imgproc.cvtColor(frame, frameGray, Imgproc.COLOR_BGR2GRAY);
        Imgproc.equalizeHist(frameGray, frameGray);


            

Reported by PMD.

              
        List<Rect> listOfFaces = faces.toList();
        for (Rect face : listOfFaces) {
            Point center = new Point(face.x + face.width / 2, face.y + face.height / 2);
            Imgproc.ellipse(frame, center, new Size(face.width / 2, face.height / 2), 0, 0, 360,
                    new Scalar(255, 0, 255));

            Mat faceROI = frameGray.submat(face);


            

Reported by PMD.

                      List<Rect> listOfFaces = faces.toList();
        for (Rect face : listOfFaces) {
            Point center = new Point(face.x + face.width / 2, face.y + face.height / 2);
            Imgproc.ellipse(frame, center, new Size(face.width / 2, face.height / 2), 0, 0, 360,
                    new Scalar(255, 0, 255));

            Mat faceROI = frameGray.submat(face);

            // -- In each face, detect eyes

            

Reported by PMD.

                      for (Rect face : listOfFaces) {
            Point center = new Point(face.x + face.width / 2, face.y + face.height / 2);
            Imgproc.ellipse(frame, center, new Size(face.width / 2, face.height / 2), 0, 0, 360,
                    new Scalar(255, 0, 255));

            Mat faceROI = frameGray.submat(face);

            // -- In each face, detect eyes
            MatOfRect eyes = new MatOfRect();

            

Reported by PMD.

                          Mat faceROI = frameGray.submat(face);

            // -- In each face, detect eyes
            MatOfRect eyes = new MatOfRect();
            eyesCascade.detectMultiScale(faceROI, eyes);

            List<Rect> listOfEyes = eyes.toList();
            for (Rect eye : listOfEyes) {
                Point eyeCenter = new Point(face.x + eye.x + eye.width / 2, face.y + eye.y + eye.height / 2);

            

Reported by PMD.

              from __future__ import print_function

import numpy as np
import cv2 as cv

# Drawing Lines
def lines():
    for i in range(NUMBER*2):
        pt1, pt2 = [], []

            

Reported by Pylint.

              #!/usr/bin/env python
'''
    This program demonstrates OpenCV drawing and text output functions by drawing different shapes and text strings
    Usage :
        python3 drawing.py
    Press any button to exit
    '''

# Python 2/3 compatibility

            

Reported by Pylint.

              import cv2 as cv

# Drawing Lines
def lines():
    for i in range(NUMBER*2):
        pt1, pt2 = [], []
        pt1.append(np.random.randint(x1, x2))
        pt1.append(np.random.randint(y1, y2))
        pt2.append(np.random.randint(x1, x2))

            

Reported by Pylint.

                      color = "%06x" % np.random.randint(0, 0xFFFFFF)
        color = tuple(int(color[i:i+2], 16) for i in (0, 2 ,4))
        arrowed =  np.random.randint(0, 6)
        if (arrowed<3):
            cv.line(image, tuple(pt1), tuple(pt2), color, np.random.randint(1, 10), lineType)
        else:
            cv.arrowedLine(image, tuple(pt1), tuple(pt2), color, np.random.randint(1, 10), lineType)
        cv.imshow(wndname, image)
        if cv.waitKey(DELAY)>=0:

            

Reported by Pylint.

                          return

# Drawing Rectangle
def rectangle():
    for i in range(NUMBER*2):
        pt1, pt2 = [], []
        pt1.append(np.random.randint(x1, x2))
        pt1.append(np.random.randint(y1, y2))
        pt2.append(np.random.randint(x1, x2))

            

Reported by Pylint.

                      marker = np.random.randint(0, 10)
        marker_size = np.random.randint(30, 80)

        if (marker > 5):
            cv.rectangle(image, tuple(pt1), tuple(pt2), color, max(thickness, -1), lineType)
        else:
            cv.drawMarker(image, tuple(pt1), color, marker, marker_size)
        cv.imshow(wndname, image)
        if cv.waitKey(DELAY)>=0:

            

Reported by Pylint.

                          return

# Drawing ellipse
def ellipse():
    for i in range(NUMBER*2):
        center = []
        center.append(np.random.randint(x1, x2))
        center.append(np.random.randint(x1, x2))
        axes = []

            

Reported by Pylint.

                      color = "%06x" % np.random.randint(0, 0xFFFFFF)
        color = tuple(int(color[i:i+2], 16) for i in (0, 2 ,4))
        thickness = np.random.randint(-1, 9)
        cv.ellipse(image, tuple(center), tuple(axes), angle, angle-100, angle + 200, color, thickness, lineType)
        cv.imshow(wndname, image)
        if cv.waitKey(DELAY)>=0:
            return

# Drawing Polygonal Curves

            

Reported by Pylint.

                          return

# Drawing Polygonal Curves
def polygonal():
    for i in range(NUMBER):
        pt = [(0, 0)]*6
        pt = np.resize(pt, (2, 3, 2))
        pt[0][0][0] = np.random.randint(x1, x2)
        pt[0][0][1] = np.random.randint(y1, y2)

            

Reported by Pylint.

              # Drawing Polygonal Curves
def polygonal():
    for i in range(NUMBER):
        pt = [(0, 0)]*6
        pt = np.resize(pt, (2, 3, 2))
        pt[0][0][0] = np.random.randint(x1, x2)
        pt[0][0][1] = np.random.randint(y1, y2)
        pt[0][1][0] = np.random.randint(x1, x2)
        pt[0][1][1] = np.random.randint(y1, y2)

            

Reported by Pylint.

              
        String envTestDataPath = System.getenv(ENV_OPENCV_TEST_DATA_PATH);

        if(envTestDataPath == null) throw new Exception(ENV_OPENCV_TEST_DATA_PATH + " has to be defined!");

        File testDataPath = new File(envTestDataPath);

        File f = new File(testDataPath, "dnn/grace_hopper_227.png");
        sourceImageFile = f.toString();

            

Reported by PMD.

              
        File f = new File(testDataPath, "dnn/grace_hopper_227.png");
        sourceImageFile = f.toString();
        if(!f.exists()) throw new Exception("Test image is missing: " + sourceImageFile);

        net = Dnn.readNetFromTensorflow(modelFileName);
    }

    public void testGetLayerTypes() {

            

Reported by PMD.

                      byte[] modelBuffer = new byte[ (int)modelFile.length() ];

        try {
            FileInputStream fis = new FileInputStream(modelFile);
            fis.read(modelBuffer);
            fis.close();
        } catch (IOException e) {
            fail("Failed to read a model: " + e.getMessage());
        }

            

Reported by PMD.

              
    private final static String ENV_OPENCV_TEST_DATA_PATH = "OPENCV_TEST_DATA_PATH";

    String modelFileName = "";
    String sourceImageFile = "";

    Net net;

    private static void normAssert(Mat ref, Mat test) {

            

Reported by PMD.

                  private final static String ENV_OPENCV_TEST_DATA_PATH = "OPENCV_TEST_DATA_PATH";

    String modelFileName = "";
    String sourceImageFile = "";

    Net net;

    private static void normAssert(Mat ref, Mat test) {
        final double l1 = 1e-5;

            

Reported by PMD.

                  String modelFileName = "";
    String sourceImageFile = "";

    Net net;

    private static void normAssert(Mat ref, Mat test) {
        final double l1 = 1e-5;
        final double lInf = 1e-4;
        double normL1 = Core.norm(ref, test, Core.NORM_L1) / ref.total();

            

Reported by PMD.

                      assertTrue(normLInf < lInf);
    }

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

        String envDnnTestDataPath = System.getenv(ENV_OPENCV_DNN_TEST_DATA_PATH);


            

Reported by PMD.

                      net = Dnn.readNetFromTensorflow(modelFileName);
    }

    public void testGetLayerTypes() {
        List<String> layertypes = new ArrayList();
        net.getLayerTypes(layertypes);

        assertFalse("No layer types returned!", layertypes.isEmpty());
    }

            

Reported by PMD.

                      assertFalse("No layer types returned!", layertypes.isEmpty());
    }

    public void testGetLayer() {
        List<String> layernames = net.getLayerNames();

        assertFalse("Test net returned no layers!", layernames.isEmpty());

        String testLayerName = layernames.get(0);

            

Reported by PMD.

                      assertFalse("No layer types returned!", layertypes.isEmpty());
    }

    public void testGetLayer() {
        List<String> layernames = net.getLayerNames();

        assertFalse("Test net returned no layers!", layernames.isEmpty());

        String testLayerName = layernames.get(0);

            

Reported by PMD.

              from __future__ import print_function
import sys

import cv2 as cv
import numpy as np


def print_help():
    print('''

            

Reported by Pylint.

                  cv.log(magI, magI)
    ## [log]
    ## [crop_rearrange]
    magI_rows, magI_cols = magI.shape
    # crop the spectrum, if it has an odd number of rows or columns
    magI = magI[0:(magI_rows & -2), 0:(magI_cols & -2)]
    cx = int(magI_rows/2)
    cy = int(magI_cols/2)


            

Reported by Pylint.

                  ## [crop_rearrange]
    magI_rows, magI_cols = magI.shape
    # crop the spectrum, if it has an odd number of rows or columns
    magI = magI[0:(magI_rows & -2), 0:(magI_cols & -2)]
    cx = int(magI_rows/2)
    cy = int(magI_cols/2)

    q0 = magI[0:cx, 0:cy]         # Top-Left - Create a ROI per quadrant
    q1 = magI[cx:cx+cx, 0:cy]     # Top-Right

            

Reported by Pylint.

              from __future__ import print_function
import sys

import cv2 as cv
import numpy as np


def print_help():
    print('''

            

Reported by Pylint.

              import numpy as np


def print_help():
    print('''
    This program demonstrated the use of the discrete Fourier transform (DFT).
    The dft of an image is taken and it's power spectrum is displayed.
    Usage:
    discrete_fourier_transform.py [image_name -- default lena.jpg]''')

            

Reported by Pylint.

                  discrete_fourier_transform.py [image_name -- default lena.jpg]''')


def main(argv):

    print_help()

    filename = argv[0] if len(argv) > 0 else 'lena.jpg'


            

Reported by Pylint.

                  discrete_fourier_transform.py [image_name -- default lena.jpg]''')


def main(argv):

    print_help()

    filename = argv[0] if len(argv) > 0 else 'lena.jpg'


            

Reported by Pylint.

                  discrete_fourier_transform.py [image_name -- default lena.jpg]''')


def main(argv):

    print_help()

    filename = argv[0] if len(argv) > 0 else 'lena.jpg'


            

Reported by Pylint.

              
    filename = argv[0] if len(argv) > 0 else 'lena.jpg'

    I = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
    if I is None:
        print('Error opening image')
        return -1
    ## [expand]
    rows, cols = I.shape

            

Reported by Pylint.

                      return -1
    ## [expand]
    rows, cols = I.shape
    m = cv.getOptimalDFTSize( rows )
    n = cv.getOptimalDFTSize( cols )
    padded = cv.copyMakeBorder(I, 0, m - rows, 0, n - cols, cv.BORDER_CONSTANT, value=[0, 0, 0])
    ## [expand]
    ## [complex_and_real]
    planes = [np.float32(padded), np.zeros(padded.shape, np.float32)]

            

Reported by Pylint.

              import os
from abc import ABCMeta, abstractmethod

import cv2
import numpy as np

from ...img_utils import read_rgb_img, get_pytorch_preprocess
from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


            

Reported by Pylint.

              import cv2
import numpy as np

from ...img_utils import read_rgb_img, get_pytorch_preprocess
from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


class DataFetch(object):
    imgs_dir = ''

            

Reported by Pylint.

              import numpy as np

from ...img_utils import read_rgb_img, get_pytorch_preprocess
from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


class DataFetch(object):
    imgs_dir = ''
    frame_size = 0

            

Reported by Pylint.

                      img = cv2.resize(img, (PYTORCH_RSZ_WIDTH, PYTORCH_RSZ_HEIGHT))
        img = self.center_crop(img)
        if self.preprocess_input:
            return self.presprocess_input(img)
        return get_pytorch_preprocess(img)


class TFPreprocessedFetch(DataFetch):
    def __init__(self, tf_cls_config, preprocess_input):

            

Reported by Pylint.

              import os
from abc import ABCMeta, abstractmethod

import cv2
import numpy as np

from ...img_utils import read_rgb_img, get_pytorch_preprocess
from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


            

Reported by Pylint.

              from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


class DataFetch(object):
    imgs_dir = ''
    frame_size = 0
    bgr_to_rgb = False

    __metaclass__ = ABCMeta

            

Reported by Pylint.

              from ...test.configs.default_preprocess_config import PYTORCH_RSZ_HEIGHT, PYTORCH_RSZ_WIDTH


class DataFetch(object):
    imgs_dir = ''
    frame_size = 0
    bgr_to_rgb = False

    __metaclass__ = ABCMeta

            

Reported by Pylint.

                  __metaclass__ = ABCMeta

    @abstractmethod
    def preprocess(self, img):
        pass

    @staticmethod
    def reshape_img(img):
        img = img[:, :, 0:3].transpose(2, 0, 1)

            

Reported by Pylint.

                      pass

    @staticmethod
    def reshape_img(img):
        img = img[:, :, 0:3].transpose(2, 0, 1)
        return np.expand_dims(img, 0)

    def center_crop(self, img):
        cols = img.shape[1]

            

Reported by Pylint.

                      img = img[:, :, 0:3].transpose(2, 0, 1)
        return np.expand_dims(img, 0)

    def center_crop(self, img):
        cols = img.shape[1]
        rows = img.shape[0]

        y1 = round((rows - self.frame_size) / 2)
        y2 = round(y1 + self.frame_size)

            

Reported by Pylint.

              """

from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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

            

Reported by Pylint.

              """

from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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

            

Reported by Pylint.

              
from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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


            

Reported by Pylint.

              
from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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


            

Reported by Pylint.

              
from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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


            

Reported by Pylint.

              
from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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


            

Reported by Pylint.

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

class OSXDocBuilder(DocBuilder):

    def getToolchain(self):
        return None

            

Reported by Pylint.

              """

from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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

            

Reported by Pylint.

              
from __future__ import print_function
import os, sys, multiprocessing, argparse, traceback
from subprocess import check_call, check_output, CalledProcessError, Popen

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


            

Reported by Bandit.

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

class OSXDocBuilder(DocBuilder):

    def getToolchain(self):
        return None

            

Reported by Pylint.

              # Python 2/3 compatibility
from __future__ import print_function

import cv2 as cv
import numpy as np
import sys
from numpy import pi, sin, cos

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              
import cv2 as cv
import numpy as np
import sys
from numpy import pi, sin, cos

from tests_common import NewOpenCVTests

def circleApproximation(circle):

            

Reported by Pylint.

              
import cv2 as cv
import numpy as np
import sys
from numpy import pi, sin, cos

from tests_common import NewOpenCVTests

def circleApproximation(circle):

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

def circleApproximation(circle):

    nPoints = 30
    dPhi = 2*pi / nPoints
    contour = []
    for i in range(nPoints):

            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

def circleApproximation(circle):

    nPoints = 30
    dPhi = 2*pi / nPoints
    contour = []
    for i in range(nPoints):

            

Reported by Pylint.

              
def circleApproximation(circle):

    nPoints = 30
    dPhi = 2*pi / nPoints
    contour = []
    for i in range(nPoints):
        contour.append(([circle[0] + circle[2]*cos(i*dPhi),
            circle[1] + circle[2]*sin(i*dPhi)]))

            

Reported by Pylint.

              def circleApproximation(circle):

    nPoints = 30
    dPhi = 2*pi / nPoints
    contour = []
    for i in range(nPoints):
        contour.append(([circle[0] + circle[2]*cos(i*dPhi),
            circle[1] + circle[2]*sin(i*dPhi)]))


            

Reported by Pylint.

              
    return np.array(contour).astype(int)

def convContoursIntersectiponRate(c1, c2):

    s1 = cv.contourArea(c1)
    s2 = cv.contourArea(c2)

    s, _ = cv.intersectConvexConvex(c1, c2)

            

Reported by Pylint.

              
    return np.array(contour).astype(int)

def convContoursIntersectiponRate(c1, c2):

    s1 = cv.contourArea(c1)
    s2 = cv.contourArea(c2)

    s, _ = cv.intersectConvexConvex(c1, c2)

            

Reported by Pylint.

              
    return np.array(contour).astype(int)

def convContoursIntersectiponRate(c1, c2):

    s1 = cv.contourArea(c1)
    s2 = cv.contourArea(c2)

    s, _ = cv.intersectConvexConvex(c1, c2)

            

Reported by Pylint.