# Python 2/3 compatibility
from __future__ import print_function

import cv2 as cv
import numpy as np
import sys
import math

from tests_common import NewOpenCVTests

            

Reported by Pylint.

              
import cv2 as cv
import numpy as np
import sys
import math

from tests_common import NewOpenCVTests

def linesDiff(line1, line2):

            

Reported by Pylint.

              
import cv2 as cv
import numpy as np
import sys
import math

from tests_common import NewOpenCVTests

def linesDiff(line1, line2):

            

Reported by Pylint.

              import cv2 as cv
import numpy as np
import sys
import math

from tests_common import NewOpenCVTests

def linesDiff(line1, line2):


            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

def linesDiff(line1, line2):

    norm1 = cv.norm(line1 - line2, cv.NORM_L2)
    line3 = line1[2:4] + line1[0:2]
    norm2 = cv.norm(line3 - line2, cv.NORM_L2)


            

Reported by Pylint.

              
from tests_common import NewOpenCVTests

def linesDiff(line1, line2):

    norm1 = cv.norm(line1 - line2, cv.NORM_L2)
    line3 = line1[2:4] + line1[0:2]
    norm2 = cv.norm(line3 - line2, cv.NORM_L2)


            

Reported by Pylint.

              
    return min(norm1, norm2)

class houghlines_test(NewOpenCVTests):

    def test_houghlines(self):

        fn = "/samples/data/pic1.png"


            

Reported by Pylint.

              
    return min(norm1, norm2)

class houghlines_test(NewOpenCVTests):

    def test_houghlines(self):

        fn = "/samples/data/pic1.png"


            

Reported by Pylint.

              
class houghlines_test(NewOpenCVTests):

    def test_houghlines(self):

        fn = "/samples/data/pic1.png"

        src = self.get_sample(fn)
        dst = cv.Canny(src, 50, 200)

            

Reported by Pylint.

              
    def test_houghlines(self):

        fn = "/samples/data/pic1.png"

        src = self.get_sample(fn)
        dst = cv.Canny(src, 50, 200)

        lines = cv.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)[:,0,:]

            

Reported by Pylint.

              
        // Check if image is loaded successfully
        if (src.empty()) {
            System.err.println("Cannot read image: " + filename);
            System.exit(0);
        }

        Mat srcOriginal = src.clone();
        HighGui.imshow("src", srcOriginal);

            

Reported by PMD.

                      List<Point> pts = ptsMat.toList();
        //! [pca]
        // Construct a buffer used by the pca analysis
        int sz = pts.size();
        Mat dataPts = new Mat(sz, 2, CvType.CV_64F);
        double[] dataPtsData = new double[(int) (dataPts.total() * dataPts.channels())];
        for (int i = 0; i < dataPts.rows(); i++) {
            dataPtsData[i * dataPts.cols()] = pts.get(i).x;
            dataPtsData[i * dataPts.cols() + 1] = pts.get(i).y;

            

Reported by PMD.

                      Mat dataPts = new Mat(sz, 2, CvType.CV_64F);
        double[] dataPtsData = new double[(int) (dataPts.total() * dataPts.channels())];
        for (int i = 0; i < dataPts.rows(); i++) {
            dataPtsData[i * dataPts.cols()] = pts.get(i).x;
            dataPtsData[i * dataPts.cols() + 1] = pts.get(i).y;
        }
        dataPts.put(0, 0, dataPtsData);

        // Perform PCA analysis

            

Reported by PMD.

                      double[] dataPtsData = new double[(int) (dataPts.total() * dataPts.channels())];
        for (int i = 0; i < dataPts.rows(); i++) {
            dataPtsData[i * dataPts.cols()] = pts.get(i).x;
            dataPtsData[i * dataPts.cols() + 1] = pts.get(i).y;
        }
        dataPts.put(0, 0, dataPtsData);

        // Perform PCA analysis
        Mat mean = new Mat();

            

Reported by PMD.

                      Mat src = Imgcodecs.imread(filename);

        // Check if image is loaded successfully
        if (src.empty()) {
            System.err.println("Cannot read image: " + filename);
            System.exit(0);
        }

        Mat srcOriginal = src.clone();

            

Reported by PMD.

                      // Check if image is loaded successfully
        if (src.empty()) {
            System.err.println("Cannot read image: " + filename);
            System.exit(0);
        }

        Mat srcOriginal = src.clone();
        HighGui.imshow("src", srcOriginal);


            

Reported by PMD.

                          System.exit(0);
        }

        Mat srcOriginal = src.clone();
        HighGui.imshow("src", srcOriginal);

        // Convert image to grayscale
        Mat gray = new Mat();
        Imgproc.cvtColor(src, gray, Imgproc.COLOR_BGR2GRAY);

            

Reported by PMD.

                              continue;

            // Draw each contour only for visualisation purposes
            Imgproc.drawContours(src, contours, i, new Scalar(0, 0, 255), 2);
            // Find the orientation of each shape
            getOrientation(contours.get(i), src);
        }
        //! [contours]


            

Reported by PMD.

                      HighGui.imshow("output", src);

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

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

            

Reported by PMD.

                  }
}

public class IntroductionToPCADemo {
    public static void main(String[] args) {
        // Load the native OpenCV library
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        new IntroductionToPCA().run(args);

            

Reported by PMD.

              from __future__ import print_function
import cv2 as cv
import argparse

max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'

            

Reported by Pylint.

              window_name = 'Threshold Demo'

## [Threshold_Demo]
def Threshold_Demo(val):
    #0: Binary
    #1: Binary Inverted
    #2: Threshold Truncated
    #3: Threshold to Zero
    #4: Threshold to Zero Inverted

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import argparse

max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'

            

Reported by Pylint.

              from __future__ import print_function
import cv2 as cv
import argparse

max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'

            

Reported by Pylint.

              import cv2 as cv
import argparse

max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'

            

Reported by Pylint.

              import argparse

max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'


            

Reported by Pylint.

              
max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'

## [Threshold_Demo]

            

Reported by Pylint.

              max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'

## [Threshold_Demo]
def Threshold_Demo(val):

            

Reported by Pylint.

              max_value = 255
max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'

## [Threshold_Demo]
def Threshold_Demo(val):

            

Reported by Pylint.

              max_type = 4
max_binary_value = 255
trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
trackbar_value = 'Value'
window_name = 'Threshold Demo'

## [Threshold_Demo]
def Threshold_Demo(val):
    #0: Binary

            

Reported by Pylint.

              from tensorflow.keras.applications import (
    VGG16, vgg16,
    VGG19, vgg19,

    ResNet50, resnet,
    ResNet101,
    ResNet152,

    DenseNet121, densenet,

            

Reported by Pylint.

                  Xception, xception
)

from ..tf_model import TFModelPreparer
from ..tf_model import (
    TFModelProcessor,
    TFDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import TFPreprocessedFetch

            

Reported by Pylint.

              )

from ..tf_model import TFModelPreparer
from ..tf_model import (
    TFModelProcessor,
    TFDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import TFPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline

            

Reported by Pylint.

                  TFModelProcessor,
    TFDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import TFPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import (
    tf_input_blob,
    pytorch_input_blob,
    tf_model_blob_caffe_mode

            

Reported by Pylint.

                  TFDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import TFPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import (
    tf_input_blob,
    pytorch_input_blob,
    tf_model_blob_caffe_mode
)

            

Reported by Pylint.

              )
from ...common.evaluation.classification.cls_data_fetcher import TFPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import (
    tf_input_blob,
    pytorch_input_blob,
    tf_model_blob_caffe_mode
)
from ...common.utils import set_tf_env, create_extended_parser

            

Reported by Pylint.

                  pytorch_input_blob,
    tf_model_blob_caffe_mode
)
from ...common.utils import set_tf_env, create_extended_parser

model_dict = {
    "vgg16": [VGG16, vgg16, tf_model_blob_caffe_mode],
    "vgg19": [VGG19, vgg19, tf_model_blob_caffe_mode],


            

Reported by Pylint.

              

class TFClsModel(TFModelPreparer):
    def __init__(self, model_name, original_model):
        super(TFClsModel, self).__init__(model_name, original_model)


def main():
    set_tf_env()

            

Reported by Pylint.

              from tensorflow.keras.applications import (
    VGG16, vgg16,
    VGG19, vgg19,

    ResNet50, resnet,
    ResNet101,
    ResNet152,

    DenseNet121, densenet,

            

Reported by Pylint.

              DEFAULT_BLOB_PARAMS_ID = 2


class TFClsModel(TFModelPreparer):
    def __init__(self, model_name, original_model):
        super(TFClsModel, self).__init__(model_name, original_model)


def main():

            

Reported by Pylint.

              from torchvision import models

from ..pytorch_model import (
    PyTorchModelPreparer,
    PyTorchModelProcessor,
    PyTorchDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline

            

Reported by Pylint.

              from torchvision import models

from ..pytorch_model import (
    PyTorchModelPreparer,
    PyTorchModelProcessor,
    PyTorchDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline

            

Reported by Pylint.

                  PyTorchModelProcessor,
    PyTorchDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import pytorch_resize_input_blob
from ...common.test.configs.test_config import TestClsConfig
from ...common.utils import set_pytorch_env, create_extended_parser


            

Reported by Pylint.

                  PyTorchDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import pytorch_resize_input_blob
from ...common.test.configs.test_config import TestClsConfig
from ...common.utils import set_pytorch_env, create_extended_parser

model_dict = {

            

Reported by Pylint.

              )
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import pytorch_resize_input_blob
from ...common.test.configs.test_config import TestClsConfig
from ...common.utils import set_pytorch_env, create_extended_parser

model_dict = {
    "alexnet": models.alexnet,

            

Reported by Pylint.

              from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import pytorch_resize_input_blob
from ...common.test.configs.test_config import TestClsConfig
from ...common.utils import set_pytorch_env, create_extended_parser

model_dict = {
    "alexnet": models.alexnet,


            

Reported by Pylint.

              from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline
from ...common.test.configs.default_preprocess_config import pytorch_resize_input_blob
from ...common.test.configs.test_config import TestClsConfig
from ...common.utils import set_pytorch_env, create_extended_parser

model_dict = {
    "alexnet": models.alexnet,

    "vgg11": models.vgg11,

            

Reported by Pylint.

              

class PyTorchClsModel(PyTorchModelPreparer):
    def __init__(self, height, width, model_name, original_model):
        super(PyTorchClsModel, self).__init__(height, width, model_name, original_model)


def main():
    set_pytorch_env()

            

Reported by Pylint.

              from torchvision import models

from ..pytorch_model import (
    PyTorchModelPreparer,
    PyTorchModelProcessor,
    PyTorchDnnModelProcessor
)
from ...common.evaluation.classification.cls_data_fetcher import PyTorchPreprocessedFetch
from ...common.test.cls_model_test_pipeline import ClsModelTestPipeline

            

Reported by Pylint.

              }


class PyTorchClsModel(PyTorchModelPreparer):
    def __init__(self, height, width, model_name, original_model):
        super(PyTorchClsModel, self).__init__(height, width, model_name, original_model)


def main():

            

Reported by Pylint.

              import os

import cv2
import numpy as np
import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models


            

Reported by Pylint.

              
import cv2
import numpy as np
import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models



            

Reported by Pylint.

              import cv2
import numpy as np
import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models


def get_pytorch_onnx_model(original_model):

            

Reported by Pylint.

              import numpy as np
import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models


def get_pytorch_onnx_model(original_model):
    # define the directory for further converted model save

            

Reported by Pylint.

              import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models


def get_pytorch_onnx_model(original_model):
    # define the directory for further converted model save
    onnx_model_path = "models"

            

Reported by Pylint.

              import os

import cv2
import numpy as np
import torch
import torch.onnx
from torch.autograd import Variable
from torchvision import models


            

Reported by Pylint.

              from torchvision import models


def get_pytorch_onnx_model(original_model):
    # define the directory for further converted model save
    onnx_model_path = "models"
    # define the name of further converted model
    onnx_model_name = "resnet50.onnx"


            

Reported by Pylint.

                  return full_model_path


def get_preprocessed_img(img_path):
    # read the image
    input_img = cv2.imread(img_path, cv2.IMREAD_COLOR)
    input_img = input_img.astype(np.float32)

    input_img = cv2.resize(input_img, (256, 256))

            

Reported by Pylint.

                  return input_blob


def get_imagenet_labels(labels_path):
    with open(labels_path) as f:
        imagenet_labels = [line.strip() for line in f.readlines()]
    return imagenet_labels



            

Reported by Pylint.

              

def get_imagenet_labels(labels_path):
    with open(labels_path) as f:
        imagenet_labels = [line.strip() for line in f.readlines()]
    return imagenet_labels


def get_opencv_dnn_prediction(opencv_net, preproc_img, imagenet_labels):

            

Reported by Pylint.

              
public class SURFDescriptorExtractorTest extends OpenCVTestCase {

    Feature2D extractor;
    int matSize;

    private Mat getTestImg() {
        Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
        Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);

            

Reported by PMD.

              public class SURFDescriptorExtractorTest extends OpenCVTestCase {

    Feature2D extractor;
    int matSize;

    private Mat getTestImg() {
        Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
        Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);
        Imgproc.line(cross, new Point(matSize / 2, 20), new Point(matSize / 2, matSize - 21), new Scalar(100), 2);

            

Reported by PMD.

                      return cross;
    }

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

        Class[] cParams = {double.class, int.class, int.class, boolean.class, boolean.class};
        Object[] oValues = {100, 2, 4, true, false};

            

Reported by PMD.

                      matSize = 100;
    }

    public void testComputeListOfMatListOfListOfKeyPointListOfMat() {
        fail("Not yet implemented");
    }

    public void testComputeMatListOfKeyPointMat() {
        KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);

            

Reported by PMD.

                      fail("Not yet implemented");
    }

    public void testComputeMatListOfKeyPointMat() {
        KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
        MatOfKeyPoint keypoints = new MatOfKeyPoint(point);
        Mat img = getTestImg();
        Mat descriptors = new Mat();


            

Reported by PMD.

                      extractor.compute(img, keypoints, descriptors);

        Mat truth = new Mat(1, 128, CvType.CV_32FC1) {
            {
                put(0, 0,
                          0, 0, 0, 0, 0, 0, 0, 0, 0.058821894, 0.058821894, -0.045962855, 0.046261817, 0.0085156476,
                          0.0085754395, -0.0064509804, 0.0064509804, 0.00044069235, 0.00044069235, 0, 0, 0.00025723741,
                          0.00025723741, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.00025723741, 0.00025723741, -0.00044069235,
                          0.00044069235, 0, 0, 0.36278215, 0.36278215, -0.24688604, 0.26173124, 0.052068226, 0.052662034,

            

Reported by PMD.

                      assertMatEqual(truth, descriptors, EPS);
    }

    public void testCreate() {
        assertNotNull(extractor);
    }

    public void testDescriptorSize() {
        assertEquals(128, extractor.descriptorSize());

            

Reported by PMD.

                      assertNotNull(extractor);
    }

    public void testDescriptorSize() {
        assertEquals(128, extractor.descriptorSize());
    }

    public void testDescriptorType() {
        assertEquals(CvType.CV_32F, extractor.descriptorType());

            

Reported by PMD.

                      assertEquals(128, extractor.descriptorSize());
    }

    public void testDescriptorType() {
        assertEquals(CvType.CV_32F, extractor.descriptorType());
    }

    public void testEmpty() {
//        assertFalse(extractor.empty());

            

Reported by PMD.

                      assertEquals(CvType.CV_32F, extractor.descriptorType());
    }

    public void testEmpty() {
//        assertFalse(extractor.empty());
        fail("Not yet implemented");
    }

    public void testRead() {

            

Reported by PMD.

              
    @Override
    public Mat render(CvCameraViewFrame inputFrame) {
        Mat renderedFrame = new Mat(inputFrame.rgba().size(), inputFrame.rgba().type());
        Calib3d.undistort(inputFrame.rgba(), renderedFrame,
                mCalibrator.getCameraMatrix(), mCalibrator.getDistortionCoefficients());

        return renderedFrame;
    }

            

Reported by PMD.

              
    @Override
    public Mat render(CvCameraViewFrame inputFrame) {
        Mat renderedFrame = new Mat(inputFrame.rgba().size(), inputFrame.rgba().type());
        Calib3d.undistort(inputFrame.rgba(), renderedFrame,
                mCalibrator.getCameraMatrix(), mCalibrator.getDistortionCoefficients());

        return renderedFrame;
    }

            

Reported by PMD.

              }

class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;

            

Reported by PMD.

              }

class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;

            

Reported by PMD.

              
class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;
        mHeight = height;

            

Reported by PMD.

              
class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;
        mHeight = height;

            

Reported by PMD.

              class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;
        mHeight = height;
        mResources = resources;

            

Reported by PMD.

              class ComparisonFrameRender extends FrameRender {
    private int mWidth;
    private int mHeight;
    private Resources mResources;
    public ComparisonFrameRender(CameraCalibrator calibrator, int width, int height, Resources resources) {
        mCalibrator = calibrator;
        mWidth = width;
        mHeight = height;
        mResources = resources;

            

Reported by PMD.

              
    @Override
    public Mat render(CvCameraViewFrame inputFrame) {
        Mat undistortedFrame = new Mat(inputFrame.rgba().size(), inputFrame.rgba().type());
        Calib3d.undistort(inputFrame.rgba(), undistortedFrame,
                mCalibrator.getCameraMatrix(), mCalibrator.getDistortionCoefficients());

        Mat comparisonFrame = inputFrame.rgba();
        undistortedFrame.colRange(new Range(0, mWidth / 2)).copyTo(comparisonFrame.colRange(new Range(mWidth / 2, mWidth)));

            

Reported by PMD.

              
    @Override
    public Mat render(CvCameraViewFrame inputFrame) {
        Mat undistortedFrame = new Mat(inputFrame.rgba().size(), inputFrame.rgba().type());
        Calib3d.undistort(inputFrame.rgba(), undistortedFrame,
                mCalibrator.getCameraMatrix(), mCalibrator.getDistortionCoefficients());

        Mat comparisonFrame = inputFrame.rgba();
        undistortedFrame.colRange(new Range(0, mWidth / 2)).copyTo(comparisonFrame.colRange(new Range(mWidth / 2, mWidth)));

            

Reported by PMD.

              
public class BRIEFDescriptorExtractorTest extends OpenCVTestCase {

    Feature2D extractor;
    int matSize;

    private Mat getTestImg() {
        Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
        Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);

            

Reported by PMD.

              public class BRIEFDescriptorExtractorTest extends OpenCVTestCase {

    Feature2D extractor;
    int matSize;

    private Mat getTestImg() {
        Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
        Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);
        Imgproc.line(cross, new Point(matSize / 2, 20), new Point(matSize / 2, matSize - 21), new Scalar(100), 2);

            

Reported by PMD.

                      return cross;
    }

    @Override
    protected void setUp() throws Exception {
        super.setUp();
        extractor = createClassInstance(XFEATURES2D+"BriefDescriptorExtractor", DEFAULT_FACTORY, null, null);
        matSize = 100;
    }

            

Reported by PMD.

                      matSize = 100;
    }

    public void testComputeListOfMatListOfListOfKeyPointListOfMat() {
        fail("Not yet implemented");
    }

    public void testComputeMatListOfKeyPointMat() {
        KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);

            

Reported by PMD.

                      fail("Not yet implemented");
    }

    public void testComputeMatListOfKeyPointMat() {
        KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
        MatOfKeyPoint keypoints = new MatOfKeyPoint(point);
        Mat img = getTestImg();
        Mat descriptors = new Mat();


            

Reported by PMD.

                      extractor.compute(img, keypoints, descriptors);

        Mat truth = new Mat(1, 32, CvType.CV_8UC1) {
            {
                put(0, 0, 96, 0, 76, 24, 47, 182, 68, 137,
                          149, 195, 67, 16, 187, 224, 74, 8,
                          82, 169, 87, 70, 44, 4, 192, 56,
                          13, 128, 44, 106, 146, 72, 194, 245);
            }

            

Reported by PMD.

                      assertMatEqual(truth, descriptors);
    }

    public void testCreate() {
        assertNotNull(extractor);
    }

    public void testDescriptorSize() {
        assertEquals(32, extractor.descriptorSize());

            

Reported by PMD.

                      assertNotNull(extractor);
    }

    public void testDescriptorSize() {
        assertEquals(32, extractor.descriptorSize());
    }

    public void testDescriptorType() {
        assertEquals(CvType.CV_8U, extractor.descriptorType());

            

Reported by PMD.

                      assertEquals(32, extractor.descriptorSize());
    }

    public void testDescriptorType() {
        assertEquals(CvType.CV_8U, extractor.descriptorType());
    }

    public void testEmpty() {
//        assertFalse(extractor.empty());

            

Reported by PMD.

                      assertEquals(CvType.CV_8U, extractor.descriptorType());
    }

    public void testEmpty() {
//        assertFalse(extractor.empty());
        fail("Not yet implemented"); // BRIEF does not override empty() method
    }

    public void testRead() {

            

Reported by PMD.

                  protected BundleContext bundleContext;

    @Inject
    private LogService logService;

    /*
    This service is required to ensure that the native library has been loaded
    before any test is carried out.
    */

            

Reported by PMD.

                  before any test is carried out.
    */
    @Inject
    private OpenCVInterface openCVInterface;

    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")

            

Reported by PMD.

                  private OpenCVInterface openCVInterface;

    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")
                .artifactId("apache-karaf")
                .version(KARAF_VERSION)
                .type("tar.gz");

            

Reported by PMD.

              
    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")
                .artifactId("apache-karaf")
                .version(KARAF_VERSION)
                .type("tar.gz");
        return new Option[]{

            

Reported by PMD.

              
    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")
                .artifactId("apache-karaf")
                .version(KARAF_VERSION)
                .type("tar.gz");
        return new Option[]{

            

Reported by PMD.

              
    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")
                .artifactId("apache-karaf")
                .version(KARAF_VERSION)
                .type("tar.gz");
        return new Option[]{

            

Reported by PMD.

              
    @Configuration
    public static Option[] configuration() throws Exception {
        MavenArtifactUrlReference karafUrl = maven()
                .groupId("org.apache.karaf")
                .artifactId("apache-karaf")
                .version(KARAF_VERSION)
                .type("tar.gz");
        return new Option[]{

            

Reported by PMD.

                          .unpackDirectory(new File("../../../build/target/exam"))
            .useDeployFolder(false),
            keepRuntimeFolder(),
            mavenBundle()
            .groupId("org.opencv")
            .artifactId("opencv")
            .versionAsInProject(),
            logLevel(LogLevelOption.LogLevel.INFO)
        };

            

Reported by PMD.

                          .unpackDirectory(new File("../../../build/target/exam"))
            .useDeployFolder(false),
            keepRuntimeFolder(),
            mavenBundle()
            .groupId("org.opencv")
            .artifactId("opencv")
            .versionAsInProject(),
            logLevel(LogLevelOption.LogLevel.INFO)
        };

            

Reported by PMD.

                          .unpackDirectory(new File("../../../build/target/exam"))
            .useDeployFolder(false),
            keepRuntimeFolder(),
            mavenBundle()
            .groupId("org.opencv")
            .artifactId("opencv")
            .versionAsInProject(),
            logLevel(LogLevelOption.LogLevel.INFO)
        };

            

Reported by PMD.