from __future__ import print_function

import numpy as np
import cv2 as cv

import argparse
import sys

modes = (cv.Stitcher_PANORAMA, cv.Stitcher_SCANS)

            

Reported by Pylint.

              # Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import cv2 as cv

import argparse
import sys


            

Reported by Pylint.

              import numpy as np
import cv2 as cv

import argparse
import sys

modes = (cv.Stitcher_PANORAMA, cv.Stitcher_SCANS)

parser = argparse.ArgumentParser(prog='stitching.py', description='Stitching sample.')

            

Reported by Pylint.

              import cv2 as cv

import argparse
import sys

modes = (cv.Stitcher_PANORAMA, cv.Stitcher_SCANS)

parser = argparse.ArgumentParser(prog='stitching.py', description='Stitching sample.')
parser.add_argument('--mode',

            

Reported by Pylint.

              
__doc__ += '\n' + parser.format_help()

def main():
    args = parser.parse_args()

    # read input images
    imgs = []
    for img_name in args.img:

            

Reported by Pylint.

              from __future__ import print_function

import numpy as np
import cv2 as cv

import video
import sys

def main():

            

Reported by Pylint.

              # Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import cv2 as cv

import video
import sys


            

Reported by Pylint.

              def main():
    try:
        video_src = sys.argv[1]
    except:
        video_src = 0

    cam = video.create_capture(video_src)
    mser = cv.MSER_create()


            

Reported by Pylint.

              import cv2 as cv

import video
import sys

def main():
    try:
        video_src = sys.argv[1]
    except:

            

Reported by Pylint.

              import video
import sys

def main():
    try:
        video_src = sys.argv[1]
    except:
        video_src = 0


            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the camshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the camshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the camshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              # Setup the termination criteria, either 10 iteration or move by atleast 1 pt
term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )

while(1):
    ret, frame = cap.read()

    if ret == True:
        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)

            

Reported by Pylint.

              while(1):
    ret, frame = cap.read()

    if ret == True:
        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)

        # apply camshift to get the new location
        ret, track_window = cv.CamShift(dst, track_window, term_crit)

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the meanshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the meanshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates the meanshift algorithm. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              # Setup the termination criteria, either 10 iteration or move by atleast 1 pt
term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )

while(1):
    ret, frame = cap.read()

    if ret == True:
        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)

            

Reported by Pylint.

              while(1):
    ret, frame = cap.read()

    if ret == True:
        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)

        # apply meanshift to get the new location
        ret, track_window = cv.meanShift(dst, track_window, term_crit)

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates Lucas-Kanade Optical Flow calculation. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates Lucas-Kanade Optical Flow calculation. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates Lucas-Kanade Optical Flow calculation. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()

            

Reported by Pylint.

              import cv2 as cv
import argparse

parser = argparse.ArgumentParser(description='This sample demonstrates Lucas-Kanade Optical Flow calculation. \
                                              The example file can be downloaded from: \
                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
parser.add_argument('image', type=str, help='path to image file')
args = parser.parse_args()


            

Reported by Pylint.

              # Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)

while(1):
    ret,frame = cap.read()
    frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)

    # calculate optical flow
    p1, st, err = cv.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
cap = cv.VideoCapture(cv.samples.findFile("vtest.avi"))
ret, frame1 = cap.read()
prvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()

            

Reported by Pylint.

              hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()
    next = cv.cvtColor(frame2,cv.COLOR_BGR2GRAY)
    flow = cv.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
    mag, ang = cv.cartToPolar(flow[...,0], flow[...,1])
    hsv[...,0] = ang*180/np.pi/2
    hsv[...,2] = cv.normalize(mag,None,0,255,cv.NORM_MINMAX)
    bgr = cv.cvtColor(hsv,cv.COLOR_HSV2BGR)

            

Reported by Pylint.

              import numpy as np
import cv2 as cv
cap = cv.VideoCapture(cv.samples.findFile("vtest.avi"))
ret, frame1 = cap.read()
prvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()

            

Reported by Pylint.

              prvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()
    next = cv.cvtColor(frame2,cv.COLOR_BGR2GRAY)
    flow = cv.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
    mag, ang = cv.cartToPolar(flow[...,0], flow[...,1])
    hsv[...,0] = ang*180/np.pi/2

            

Reported by Pylint.

                  bgr = cv.cvtColor(hsv,cv.COLOR_HSV2BGR)
    cv.imshow('frame2',bgr)
    k = cv.waitKey(30) & 0xff
    if k == 27:
        break
    elif k == ord('s'):
        cv.imwrite('opticalfb.png',frame2)
        cv.imwrite('opticalhsv.png',bgr)
    prvs = next

            

Reported by Pylint.

              from __future__ import print_function

from glob import glob
import cv2 as cv
import re

if __name__ == '__main__':
    cv2_callable = set(['cv.'+name for name in dir(cv) if callable( getattr(cv, name) )])


            

Reported by Pylint.

                  for fn in glob('*.py'):
        print(' --- ', fn)
        code = open(fn).read()
        found |= set(re.findall('cv2?\.\w+', code))

    cv2_used = found & cv2_callable
    cv2_unused = cv2_callable - cv2_used
    with open('unused_api.txt', 'w') as f:
        f.write('\n'.join(sorted(cv2_unused)))

            

Reported by Pylint.

                  for fn in glob('*.py'):
        print(' --- ', fn)
        code = open(fn).read()
        found |= set(re.findall('cv2?\.\w+', code))

    cv2_used = found & cv2_callable
    cv2_unused = cv2_callable - cv2_used
    with open('unused_api.txt', 'w') as f:
        f.write('\n'.join(sorted(cv2_unused)))

            

Reported by Pylint.

              
from glob import glob
import cv2 as cv
import re

if __name__ == '__main__':
    cv2_callable = set(['cv.'+name for name in dir(cv) if callable( getattr(cv, name) )])

    found = set()

            

Reported by Pylint.

              import re

if __name__ == '__main__':
    cv2_callable = set(['cv.'+name for name in dir(cv) if callable( getattr(cv, name) )])

    found = set()
    for fn in glob('*.py'):
        print(' --- ', fn)
        code = open(fn).read()

            

Reported by Pylint.

              IMATH_INTERNAL_NAMESPACE_HEADER_ENTER

// Attempt to normalize null vector
DEFINE_EXC_EXP (IMATH_EXPORT, NullVecExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize a point at infinity
DEFINE_EXC_EXP (IMATH_EXPORT, InfPointExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize null quaternion

            

Reported by Cppcheck.

              IMATH_INTERNAL_NAMESPACE_HEADER_ENTER

// Attempt to normalize null vector
DEFINE_EXC_EXP (IMATH_EXPORT, NullVecExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize a point at infinity
DEFINE_EXC_EXP (IMATH_EXPORT, InfPointExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize null quaternion

            

Reported by Cppcheck.

              IMATH_INTERNAL_NAMESPACE_HEADER_ENTER

// Attempt to normalize null vector
DEFINE_EXC_EXP (IMATH_EXPORT, NullVecExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize a point at infinity
DEFINE_EXC_EXP (IMATH_EXPORT, InfPointExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize null quaternion

            

Reported by Cppcheck.

              IMATH_INTERNAL_NAMESPACE_HEADER_ENTER

// Attempt to normalize null vector
DEFINE_EXC_EXP (IMATH_EXPORT, NullVecExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize a point at infinity
DEFINE_EXC_EXP (IMATH_EXPORT, InfPointExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize null quaternion

            

Reported by Cppcheck.

              IMATH_INTERNAL_NAMESPACE_HEADER_ENTER

// Attempt to normalize null vector
DEFINE_EXC_EXP (IMATH_EXPORT, NullVecExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize a point at infinity
DEFINE_EXC_EXP (IMATH_EXPORT, InfPointExc, ::IEX_NAMESPACE::MathExc)

// Attempt to normalize null quaternion

            

Reported by Cppcheck.

              using cv::gapi::core::GMat3;
using GMat2 = std::tuple<GMat, GMat>;

G_TYPED_KERNEL(TAddSimple, <GMat(GMat, GMat)>, "test.fluid.add_simple") {
    static cv::GMatDesc outMeta(cv::GMatDesc a, cv::GMatDesc) {
        return a;
    }
};


            

Reported by Cppcheck.

              using cv::gapi::core::GMat3;
using GMat2 = std::tuple<GMat, GMat>;

G_TYPED_KERNEL(TAddSimple, <GMat(GMat, GMat)>, "test.fluid.add_simple") {
    static cv::GMatDesc outMeta(cv::GMatDesc a, cv::GMatDesc) {
        return a;
    }
};


            

Reported by Cppcheck.

              using cv::gapi::core::GMat3;
using GMat2 = std::tuple<GMat, GMat>;

G_TYPED_KERNEL(TAddSimple, <GMat(GMat, GMat)>, "test.fluid.add_simple") {
    static cv::GMatDesc outMeta(cv::GMatDesc a, cv::GMatDesc) {
        return a;
    }
};


            

Reported by Cppcheck.

              using cv::gapi::core::GMat3;
using GMat2 = std::tuple<GMat, GMat>;

G_TYPED_KERNEL(TAddSimple, <GMat(GMat, GMat)>, "test.fluid.add_simple") {
    static cv::GMatDesc outMeta(cv::GMatDesc a, cv::GMatDesc) {
        return a;
    }
};


            

Reported by Cppcheck.

              using cv::gapi::core::GMat3;
using GMat2 = std::tuple<GMat, GMat>;

G_TYPED_KERNEL(TAddSimple, <GMat(GMat, GMat)>, "test.fluid.add_simple") {
    static cv::GMatDesc outMeta(cv::GMatDesc a, cv::GMatDesc) {
        return a;
    }
};


            

Reported by Cppcheck.

              #
# Copyright (C) 2017, Intel Corporation, all rights reserved.
# Third party copyrights are property of their respective owners.
import tensorflow as tf
import struct
import argparse
import numpy as np

parser = argparse.ArgumentParser(description='Convert weights of a frozen TensorFlow graph to fp16.')

            

Reported by Pylint.

              # This file is part of OpenCV project.
# It is subject to the license terms in the LICENSE file found in the top-level directory
# of this distribution and at http://opencv.org/license.html.
#
# Copyright (C) 2017, Intel Corporation, all rights reserved.
# Third party copyrights are property of their respective owners.
import tensorflow as tf
import struct
import argparse

            

Reported by Pylint.

              # Copyright (C) 2017, Intel Corporation, all rights reserved.
# Third party copyrights are property of their respective owners.
import tensorflow as tf
import struct
import argparse
import numpy as np

parser = argparse.ArgumentParser(description='Convert weights of a frozen TensorFlow graph to fp16.')
parser.add_argument('--input', required=True, help='Path to frozen graph.')

            

Reported by Pylint.

              # Third party copyrights are property of their respective owners.
import tensorflow as tf
import struct
import argparse
import numpy as np

parser = argparse.ArgumentParser(description='Convert weights of a frozen TensorFlow graph to fp16.')
parser.add_argument('--input', required=True, help='Path to frozen graph.')
parser.add_argument('--output', required=True, help='Path to output graph.')

            

Reported by Pylint.

              import argparse
import numpy as np

parser = argparse.ArgumentParser(description='Convert weights of a frozen TensorFlow graph to fp16.')
parser.add_argument('--input', required=True, help='Path to frozen graph.')
parser.add_argument('--output', required=True, help='Path to output graph.')
parser.add_argument('--ops', default=['Conv2D', 'MatMul'], nargs='+',
                    help='List of ops which weights are converted.')
args = parser.parse_args()

            

Reported by Pylint.