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api.txt
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Help on module cv2:
NAME
cv2
FILE
/usr/local/lib/python2.7/dist-packages/cv2.so
SUBMODULES
Error
bgsegm
datasets
detail
face
fisheye
flann
line_descriptor
ml
motempl
ocl
ogl
optflow
ppf_match_3d
rgbd
text
videostab
xfeatures2d
ximgproc
xphoto
CLASSES
exceptions.Exception(exceptions.BaseException)
error
class error(exceptions.Exception)
| Method resolution order:
| error
| exceptions.Exception
| exceptions.BaseException
| __builtin__.object
|
| Data descriptors defined here:
|
| __weakref__
| list of weak references to the object (if defined)
|
| ----------------------------------------------------------------------
| Methods inherited from exceptions.Exception:
|
| __init__(...)
| x.__init__(...) initializes x; see help(type(x)) for signature
|
| ----------------------------------------------------------------------
| Data and other attributes inherited from exceptions.Exception:
|
| __new__ = <built-in method __new__ of type object>
| T.__new__(S, ...) -> a new object with type S, a subtype of T
|
| ----------------------------------------------------------------------
| Methods inherited from exceptions.BaseException:
|
| __delattr__(...)
| x.__delattr__('name') <==> del x.name
|
| __getattribute__(...)
| x.__getattribute__('name') <==> x.name
|
| __getitem__(...)
| x.__getitem__(y) <==> x[y]
|
| __getslice__(...)
| x.__getslice__(i, j) <==> x[i:j]
|
| Use of negative indices is not supported.
|
| __reduce__(...)
|
| __repr__(...)
| x.__repr__() <==> repr(x)
|
| __setattr__(...)
| x.__setattr__('name', value) <==> x.name = value
|
| __setstate__(...)
|
| __str__(...)
| x.__str__() <==> str(x)
|
| __unicode__(...)
|
| ----------------------------------------------------------------------
| Data descriptors inherited from exceptions.BaseException:
|
| __dict__
|
| args
|
| message
FUNCTIONS
AKAZE_create(...)
AKAZE_create([, descriptor_type[, descriptor_size[, descriptor_channels[, threshold[, nOctaves[, nOctaveLayers[, diffusivity]]]]]]]) -> retval
AgastFeatureDetector_create(...)
AgastFeatureDetector_create([, threshold[, nonmaxSuppression[, type]]]) -> retval
BFMatcher(...)
BFMatcher([, normType[, crossCheck]]) -> <BFMatcher object>
BOWImgDescriptorExtractor(...)
BOWImgDescriptorExtractor(dextractor, dmatcher) -> <BOWImgDescriptorExtractor object>
BOWKMeansTrainer(...)
BOWKMeansTrainer(clusterCount[, termcrit[, attempts[, flags]]]) -> <BOWKMeansTrainer object>
BRISK_create(...)
BRISK_create([, thresh[, octaves[, patternScale]]]) -> retval or BRISK_create(radiusList, numberList[, dMax[, dMin[, indexChange]]]) -> retval
CamShift(...)
CamShift(probImage, window, criteria) -> retval, window
Canny(...)
Canny(image, threshold1, threshold2[, edges[, apertureSize[, L2gradient]]]) -> edges
CascadeClassifier(...)
CascadeClassifier([filename]) -> <CascadeClassifier object>
CascadeClassifier_convert(...)
CascadeClassifier_convert(oldcascade, newcascade) -> retval
DMatch(...)
DMatch() -> <DMatch object> or DMatch(_queryIdx, _trainIdx, _distance) -> <DMatch object> or DMatch(_queryIdx, _trainIdx, _imgIdx, _distance) -> <DMatch object>
DescriptorMatcher_create(...)
DescriptorMatcher_create(descriptorMatcherType) -> retval
FastFeatureDetector_create(...)
FastFeatureDetector_create([, threshold[, nonmaxSuppression[, type]]]) -> retval
FileNode(...)
FileNode() -> <FileNode object>
FileStorage(...)
FileStorage([source, flags[, encoding]]) -> <FileStorage object>
FlannBasedMatcher(...)
FlannBasedMatcher([, indexParams[, searchParams]]) -> <FlannBasedMatcher object>
GFTTDetector_create(...)
GFTTDetector_create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval
GaussianBlur(...)
GaussianBlur(src, ksize, sigmaX[, dst[, sigmaY[, borderType]]]) -> dst
HOGDescriptor(...)
HOGDescriptor() -> <HOGDescriptor object> or HOGDescriptor(_winSize, _blockSize, _blockStride, _cellSize, _nbins[, _derivAperture[, _winSigma[, _histogramNormType[, _L2HysThreshold[, _gammaCorrection[, _nlevels[, _signedGradient]]]]]]]) -> <HOGDescriptor object> or HOGDescriptor(filename) -> <HOGDescriptor object>
HOGDescriptor_getDaimlerPeopleDetector(...)
HOGDescriptor_getDaimlerPeopleDetector() -> retval
HOGDescriptor_getDefaultPeopleDetector(...)
HOGDescriptor_getDefaultPeopleDetector() -> retval
HoughCircles(...)
HoughCircles(image, method, dp, minDist[, circles[, param1[, param2[, minRadius[, maxRadius]]]]]) -> circles
HoughLines(...)
HoughLines(image, rho, theta, threshold[, lines[, srn[, stn[, min_theta[, max_theta]]]]]) -> lines
HoughLinesP(...)
HoughLinesP(image, rho, theta, threshold[, lines[, minLineLength[, maxLineGap]]]) -> lines
HuMoments(...)
HuMoments(m[, hu]) -> hu
KAZE_create(...)
KAZE_create([, extended[, upright[, threshold[, nOctaves[, nOctaveLayers[, diffusivity]]]]]]) -> retval
KalmanFilter(...)
KalmanFilter([dynamParams, measureParams[, controlParams[, type]]]) -> <KalmanFilter object>
KeyPoint(...)
KeyPoint([x, y, _size[, _angle[, _response[, _octave[, _class_id]]]]]) -> <KeyPoint object>
KeyPoint_convert(...)
KeyPoint_convert(keypoints[, keypointIndexes]) -> points2f or KeyPoint_convert(points2f[, size[, response[, octave[, class_id]]]]) -> keypoints
KeyPoint_overlap(...)
KeyPoint_overlap(kp1, kp2) -> retval
LUT(...)
LUT(src, lut[, dst]) -> dst
Laplacian(...)
Laplacian(src, ddepth[, dst[, ksize[, scale[, delta[, borderType]]]]]) -> dst
MSER_create(...)
MSER_create([, _delta[, _min_area[, _max_area[, _max_variation[, _min_diversity[, _max_evolution[, _area_threshold[, _min_margin[, _edge_blur_size]]]]]]]]]) -> retval
Mahalanobis(...)
Mahalanobis(v1, v2, icovar) -> retval
ORB_create(...)
ORB_create([, nfeatures[, scaleFactor[, nlevels[, edgeThreshold[, firstLevel[, WTA_K[, scoreType[, patchSize[, fastThreshold]]]]]]]]]) -> retval
PCABackProject(...)
PCABackProject(data, mean, eigenvectors[, result]) -> result
PCACompute(...)
PCACompute(data, mean[, eigenvectors[, maxComponents]]) -> mean, eigenvectors or PCACompute(data, mean, retainedVariance[, eigenvectors]) -> mean, eigenvectors
PCAProject(...)
PCAProject(data, mean, eigenvectors[, result]) -> result
PSNR(...)
PSNR(src1, src2) -> retval
RQDecomp3x3(...)
RQDecomp3x3(src[, mtxR[, mtxQ[, Qx[, Qy[, Qz]]]]]) -> retval, mtxR, mtxQ, Qx, Qy, Qz
Rodrigues(...)
Rodrigues(src[, dst[, jacobian]]) -> dst, jacobian
SVBackSubst(...)
SVBackSubst(w, u, vt, rhs[, dst]) -> dst
SVDecomp(...)
SVDecomp(src[, w[, u[, vt[, flags]]]]) -> w, u, vt
Scharr(...)
Scharr(src, ddepth, dx, dy[, dst[, scale[, delta[, borderType]]]]) -> dst
SimpleBlobDetector_Params(...)
SimpleBlobDetector_Params() -> <SimpleBlobDetector_Params object>
SimpleBlobDetector_create(...)
SimpleBlobDetector_create([, parameters]) -> retval
Sobel(...)
Sobel(src, ddepth, dx, dy[, dst[, ksize[, scale[, delta[, borderType]]]]]) -> dst
StereoBM_create(...)
StereoBM_create([, numDisparities[, blockSize]]) -> retval
StereoSGBM_create(...)
StereoSGBM_create(minDisparity, numDisparities, blockSize[, P1[, P2[, disp12MaxDiff[, preFilterCap[, uniquenessRatio[, speckleWindowSize[, speckleRange[, mode]]]]]]]]) -> retval
Subdiv2D(...)
Subdiv2D([rect]) -> <Subdiv2D object>
VideoCapture(...)
VideoCapture() -> <VideoCapture object> or VideoCapture(filename) -> <VideoCapture object> or VideoCapture(device) -> <VideoCapture object>
VideoWriter(...)
VideoWriter([filename, fourcc, fps, frameSize[, isColor]]) -> <VideoWriter object>
VideoWriter_fourcc(...)
VideoWriter_fourcc(c1, c2, c3, c4) -> retval
absdiff(...)
absdiff(src1, src2[, dst]) -> dst
accumulate(...)
accumulate(src, dst[, mask]) -> dst
accumulateProduct(...)
accumulateProduct(src1, src2, dst[, mask]) -> dst
accumulateSquare(...)
accumulateSquare(src, dst[, mask]) -> dst
accumulateWeighted(...)
accumulateWeighted(src, dst, alpha[, mask]) -> dst
adaptiveThreshold(...)
adaptiveThreshold(src, maxValue, adaptiveMethod, thresholdType, blockSize, C[, dst]) -> dst
add(...)
add(src1, src2[, dst[, mask[, dtype]]]) -> dst
addWeighted(...)
addWeighted(src1, alpha, src2, beta, gamma[, dst[, dtype]]) -> dst
applyColorMap(...)
applyColorMap(src, colormap[, dst]) -> dst
approxPolyDP(...)
approxPolyDP(curve, epsilon, closed[, approxCurve]) -> approxCurve
arcLength(...)
arcLength(curve, closed) -> retval
arrowedLine(...)
arrowedLine(img, pt1, pt2, color[, thickness[, line_type[, shift[, tipLength]]]]) -> img
batchDistance(...)
batchDistance(src1, src2, dtype[, dist[, nidx[, normType[, K[, mask[, update[, crosscheck]]]]]]]) -> dist, nidx
bilateralFilter(...)
bilateralFilter(src, d, sigmaColor, sigmaSpace[, dst[, borderType]]) -> dst
bitwise_and(...)
bitwise_and(src1, src2[, dst[, mask]]) -> dst
bitwise_not(...)
bitwise_not(src[, dst[, mask]]) -> dst
bitwise_or(...)
bitwise_or(src1, src2[, dst[, mask]]) -> dst
bitwise_xor(...)
bitwise_xor(src1, src2[, dst[, mask]]) -> dst
blur(...)
blur(src, ksize[, dst[, anchor[, borderType]]]) -> dst
borderInterpolate(...)
borderInterpolate(p, len, borderType) -> retval
boundingRect(...)
boundingRect(points) -> retval
boxFilter(...)
boxFilter(src, ddepth, ksize[, dst[, anchor[, normalize[, borderType]]]]) -> dst
boxPoints(...)
boxPoints(box[, points]) -> points
buildOpticalFlowPyramid(...)
buildOpticalFlowPyramid(img, winSize, maxLevel[, pyramid[, withDerivatives[, pyrBorder[, derivBorder[, tryReuseInputImage]]]]]) -> retval, pyramid
calcBackProject(...)
calcBackProject(images, channels, hist, ranges, scale[, dst]) -> dst
calcCovarMatrix(...)
calcCovarMatrix(samples, mean, flags[, covar[, ctype]]) -> covar, mean
calcHist(...)
calcHist(images, channels, mask, histSize, ranges[, hist[, accumulate]]) -> hist
calcOpticalFlowFarneback(...)
calcOpticalFlowFarneback(prev, next, flow, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags) -> flow
calcOpticalFlowPyrLK(...)
calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts[, status[, err[, winSize[, maxLevel[, criteria[, flags[, minEigThreshold]]]]]]]) -> nextPts, status, err
calibrateCamera(...)
calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix, distCoeffs[, rvecs[, tvecs[, flags[, criteria]]]]) -> retval, cameraMatrix, distCoeffs, rvecs, tvecs
calibrationMatrixValues(...)
calibrationMatrixValues(cameraMatrix, imageSize, apertureWidth, apertureHeight) -> fovx, fovy, focalLength, principalPoint, aspectRatio
cartToPolar(...)
cartToPolar(x, y[, magnitude[, angle[, angleInDegrees]]]) -> magnitude, angle
checkHardwareSupport(...)
checkHardwareSupport(feature) -> retval
checkRange(...)
checkRange(a[, quiet[, minVal[, maxVal]]]) -> retval, pos
circle(...)
circle(img, center, radius, color[, thickness[, lineType[, shift]]]) -> img
clipLine(...)
clipLine(imgRect, pt1, pt2) -> retval, pt1, pt2
colorChange(...)
colorChange(src, mask[, dst[, red_mul[, green_mul[, blue_mul]]]]) -> dst
compare(...)
compare(src1, src2, cmpop[, dst]) -> dst
compareHist(...)
compareHist(H1, H2, method) -> retval
completeSymm(...)
completeSymm(mtx[, lowerToUpper]) -> mtx
composeRT(...)
composeRT(rvec1, tvec1, rvec2, tvec2[, rvec3[, tvec3[, dr3dr1[, dr3dt1[, dr3dr2[, dr3dt2[, dt3dr1[, dt3dt1[, dt3dr2[, dt3dt2]]]]]]]]]]) -> rvec3, tvec3, dr3dr1, dr3dt1, dr3dr2, dr3dt2, dt3dr1, dt3dt1, dt3dr2, dt3dt2
computeCorrespondEpilines(...)
computeCorrespondEpilines(points, whichImage, F[, lines]) -> lines
connectedComponents(...)
connectedComponents(image[, labels[, connectivity[, ltype]]]) -> retval, labels
connectedComponentsWithStats(...)
connectedComponentsWithStats(image[, labels[, stats[, centroids[, connectivity[, ltype]]]]]) -> retval, labels, stats, centroids
contourArea(...)
contourArea(contour[, oriented]) -> retval
convertMaps(...)
convertMaps(map1, map2, dstmap1type[, dstmap1[, dstmap2[, nninterpolation]]]) -> dstmap1, dstmap2
convertPointsFromHomogeneous(...)
convertPointsFromHomogeneous(src[, dst]) -> dst
convertPointsToHomogeneous(...)
convertPointsToHomogeneous(src[, dst]) -> dst
convertScaleAbs(...)
convertScaleAbs(src[, dst[, alpha[, beta]]]) -> dst
convexHull(...)
convexHull(points[, hull[, clockwise[, returnPoints]]]) -> hull
convexityDefects(...)
convexityDefects(contour, convexhull[, convexityDefects]) -> convexityDefects
copyMakeBorder(...)
copyMakeBorder(src, top, bottom, left, right, borderType[, dst[, value]]) -> dst
cornerEigenValsAndVecs(...)
cornerEigenValsAndVecs(src, blockSize, ksize[, dst[, borderType]]) -> dst
cornerHarris(...)
cornerHarris(src, blockSize, ksize, k[, dst[, borderType]]) -> dst
cornerMinEigenVal(...)
cornerMinEigenVal(src, blockSize[, dst[, ksize[, borderType]]]) -> dst
cornerSubPix(...)
cornerSubPix(image, corners, winSize, zeroZone, criteria) -> corners
correctMatches(...)
correctMatches(F, points1, points2[, newPoints1[, newPoints2]]) -> newPoints1, newPoints2
countNonZero(...)
countNonZero(src) -> retval
createAffineTransformer(...)
createAffineTransformer(fullAffine) -> retval
createAlignMTB(...)
createAlignMTB([, max_bits[, exclude_range[, cut]]]) -> retval
createBackgroundSubtractorKNN(...)
createBackgroundSubtractorKNN([, history[, dist2Threshold[, detectShadows]]]) -> retval
createBackgroundSubtractorMOG2(...)
createBackgroundSubtractorMOG2([, history[, varThreshold[, detectShadows]]]) -> retval
createCLAHE(...)
createCLAHE([, clipLimit[, tileGridSize]]) -> retval
createCalibrateDebevec(...)
createCalibrateDebevec([, samples[, lambda[, random]]]) -> retval
createCalibrateRobertson(...)
createCalibrateRobertson([, max_iter[, threshold]]) -> retval
createChiHistogramCostExtractor(...)
createChiHistogramCostExtractor([, nDummies[, defaultCost]]) -> retval
createEMDHistogramCostExtractor(...)
createEMDHistogramCostExtractor([, flag[, nDummies[, defaultCost]]]) -> retval
createEMDL1HistogramCostExtractor(...)
createEMDL1HistogramCostExtractor([, nDummies[, defaultCost]]) -> retval
createHanningWindow(...)
createHanningWindow(winSize, type[, dst]) -> dst
createHausdorffDistanceExtractor(...)
createHausdorffDistanceExtractor([, distanceFlag[, rankProp]]) -> retval
createLineSegmentDetector(...)
createLineSegmentDetector([, _refine[, _scale[, _sigma_scale[, _quant[, _ang_th[, _log_eps[, _density_th[, _n_bins]]]]]]]]) -> retval
createMergeDebevec(...)
createMergeDebevec() -> retval
createMergeMertens(...)
createMergeMertens([, contrast_weight[, saturation_weight[, exposure_weight]]]) -> retval
createMergeRobertson(...)
createMergeRobertson() -> retval
createNormHistogramCostExtractor(...)
createNormHistogramCostExtractor([, flag[, nDummies[, defaultCost]]]) -> retval
createOptFlow_DualTVL1(...)
createOptFlow_DualTVL1() -> retval
createShapeContextDistanceExtractor(...)
createShapeContextDistanceExtractor([, nAngularBins[, nRadialBins[, innerRadius[, outerRadius[, iterations[, comparer[, transformer]]]]]]]) -> retval
createStitcher(...)
createStitcher([, try_use_gpu]) -> retval
createThinPlateSplineShapeTransformer(...)
createThinPlateSplineShapeTransformer([, regularizationParameter]) -> retval
createTonemap(...)
createTonemap([, gamma]) -> retval
createTonemapDrago(...)
createTonemapDrago([, gamma[, saturation[, bias]]]) -> retval
createTonemapDurand(...)
createTonemapDurand([, gamma[, contrast[, saturation[, sigma_space[, sigma_color]]]]]) -> retval
createTonemapMantiuk(...)
createTonemapMantiuk([, gamma[, scale[, saturation]]]) -> retval
createTonemapReinhard(...)
createTonemapReinhard([, gamma[, intensity[, light_adapt[, color_adapt]]]]) -> retval
createTrackbar(...)
createTrackbar(trackbarName, windowName, value, count, onChange) -> None
cubeRoot(...)
cubeRoot(val) -> retval
cvtColor(...)
cvtColor(src, code[, dst[, dstCn]]) -> dst
dct(...)
dct(src[, dst[, flags]]) -> dst
decolor(...)
decolor(src[, grayscale[, color_boost]]) -> grayscale, color_boost
decomposeEssentialMat(...)
decomposeEssentialMat(E[, R1[, R2[, t]]]) -> R1, R2, t
decomposeHomographyMat(...)
decomposeHomographyMat(H, K[, rotations[, translations[, normals]]]) -> retval, rotations, translations, normals
decomposeProjectionMatrix(...)
decomposeProjectionMatrix(projMatrix[, cameraMatrix[, rotMatrix[, transVect[, rotMatrixX[, rotMatrixY[, rotMatrixZ[, eulerAngles]]]]]]]) -> cameraMatrix, rotMatrix, transVect, rotMatrixX, rotMatrixY, rotMatrixZ, eulerAngles
demosaicing(...)
demosaicing(_src, code[, _dst[, dcn]]) -> _dst
denoise_TVL1(...)
denoise_TVL1(observations, result[, lambda[, niters]]) -> None
destroyAllWindows(...)
destroyAllWindows() -> None
destroyWindow(...)
destroyWindow(winname) -> None
detailEnhance(...)
detailEnhance(src[, dst[, sigma_s[, sigma_r]]]) -> dst
determinant(...)
determinant(mtx) -> retval
dft(...)
dft(src[, dst[, flags[, nonzeroRows]]]) -> dst
dilate(...)
dilate(src, kernel[, dst[, anchor[, iterations[, borderType[, borderValue]]]]]) -> dst
distanceTransform(...)
distanceTransform(src, distanceType, maskSize[, dst[, dstType]]) -> dst
distanceTransformWithLabels(...)
distanceTransformWithLabels(src, distanceType, maskSize[, dst[, labels[, labelType]]]) -> dst, labels
divide(...)
divide(src1, src2[, dst[, scale[, dtype]]]) -> dst or divide(scale, src2[, dst[, dtype]]) -> dst
drawChessboardCorners(...)
drawChessboardCorners(image, patternSize, corners, patternWasFound) -> image
drawContours(...)
drawContours(image, contours, contourIdx, color[, thickness[, lineType[, hierarchy[, maxLevel[, offset]]]]]) -> image
drawKeypoints(...)
drawKeypoints(image, keypoints, outImage[, color[, flags]]) -> outImage
drawMatches(...)
drawMatches(img1, keypoints1, img2, keypoints2, matches1to2, outImg[, matchColor[, singlePointColor[, matchesMask[, flags]]]]) -> outImg
drawMatchesKnn(...)
drawMatchesKnn(img1, keypoints1, img2, keypoints2, matches1to2, outImg[, matchColor[, singlePointColor[, matchesMask[, flags]]]]) -> outImg
edgePreservingFilter(...)
edgePreservingFilter(src[, dst[, flags[, sigma_s[, sigma_r]]]]) -> dst
eigen(...)
eigen(src[, eigenvalues[, eigenvectors]]) -> retval, eigenvalues, eigenvectors
ellipse(...)
ellipse(img, center, axes, angle, startAngle, endAngle, color[, thickness[, lineType[, shift]]]) -> img or ellipse(img, box, color[, thickness[, lineType]]) -> img
ellipse2Poly(...)
ellipse2Poly(center, axes, angle, arcStart, arcEnd, delta) -> pts
equalizeHist(...)
equalizeHist(src[, dst]) -> dst
erode(...)
erode(src, kernel[, dst[, anchor[, iterations[, borderType[, borderValue]]]]]) -> dst
estimateAffine3D(...)
estimateAffine3D(src, dst[, out[, inliers[, ransacThreshold[, confidence]]]]) -> retval, out, inliers
estimateRigidTransform(...)
estimateRigidTransform(src, dst, fullAffine) -> retval
exp(...)
exp(src[, dst]) -> dst
extractChannel(...)
extractChannel(src, coi[, dst]) -> dst
fastAtan2(...)
fastAtan2(y, x) -> retval
fastNlMeansDenoising(...)
fastNlMeansDenoising(src[, dst[, h[, templateWindowSize[, searchWindowSize]]]]) -> dst or fastNlMeansDenoising(src, h[, dst[, templateWindowSize[, searchWindowSize[, normType]]]]) -> dst
fastNlMeansDenoisingColored(...)
fastNlMeansDenoisingColored(src[, dst[, h[, hColor[, templateWindowSize[, searchWindowSize]]]]]) -> dst
fastNlMeansDenoisingColoredMulti(...)
fastNlMeansDenoisingColoredMulti(srcImgs, imgToDenoiseIndex, temporalWindowSize[, dst[, h[, hColor[, templateWindowSize[, searchWindowSize]]]]]) -> dst
fastNlMeansDenoisingMulti(...)
fastNlMeansDenoisingMulti(srcImgs, imgToDenoiseIndex, temporalWindowSize[, dst[, h[, templateWindowSize[, searchWindowSize]]]]) -> dst or fastNlMeansDenoisingMulti(srcImgs, imgToDenoiseIndex, temporalWindowSize, h[, dst[, templateWindowSize[, searchWindowSize[, normType]]]]) -> dst
fillConvexPoly(...)
fillConvexPoly(img, points, color[, lineType[, shift]]) -> img
fillPoly(...)
fillPoly(img, pts, color[, lineType[, shift[, offset]]]) -> img
filter2D(...)
filter2D(src, ddepth, kernel[, dst[, anchor[, delta[, borderType]]]]) -> dst
filterSpeckles(...)
filterSpeckles(img, newVal, maxSpeckleSize, maxDiff[, buf]) -> img, buf
findChessboardCorners(...)
findChessboardCorners(image, patternSize[, corners[, flags]]) -> retval, corners
findCirclesGrid(...)
findCirclesGrid(image, patternSize[, centers[, flags[, blobDetector]]]) -> retval, centers
findContours(...)
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> image, contours, hierarchy
findEssentialMat(...)
findEssentialMat(points1, points2[, focal[, pp[, method[, prob[, threshold[, mask]]]]]]) -> retval, mask
findFundamentalMat(...)
findFundamentalMat(points1, points2[, method[, param1[, param2[, mask]]]]) -> retval, mask
findHomography(...)
findHomography(srcPoints, dstPoints[, method[, ransacReprojThreshold[, mask[, maxIters[, confidence]]]]]) -> retval, mask
findNonZero(...)
findNonZero(src[, idx]) -> idx
findTransformECC(...)
findTransformECC(templateImage, inputImage, warpMatrix[, motionType[, criteria]]) -> retval, warpMatrix
fitEllipse(...)
fitEllipse(points) -> retval
fitLine(...)
fitLine(points, distType, param, reps, aeps[, line]) -> line
flip(...)
flip(src, flipCode[, dst]) -> dst
floodFill(...)
floodFill(image, mask, seedPoint, newVal[, loDiff[, upDiff[, flags]]]) -> retval, image, mask, rect
gemm(...)
gemm(src1, src2, alpha, src3, beta[, dst[, flags]]) -> dst
getAffineTransform(...)
getAffineTransform(src, dst) -> retval
getBuildInformation(...)
getBuildInformation() -> retval
getCPUTickCount(...)
getCPUTickCount() -> retval
getDefaultNewCameraMatrix(...)
getDefaultNewCameraMatrix(cameraMatrix[, imgsize[, centerPrincipalPoint]]) -> retval
getDerivKernels(...)
getDerivKernels(dx, dy, ksize[, kx[, ky[, normalize[, ktype]]]]) -> kx, ky
getGaborKernel(...)
getGaborKernel(ksize, sigma, theta, lambd, gamma[, psi[, ktype]]) -> retval
getGaussianKernel(...)
getGaussianKernel(ksize, sigma[, ktype]) -> retval
getNumberOfCPUs(...)
getNumberOfCPUs() -> retval
getOptimalDFTSize(...)
getOptimalDFTSize(vecsize) -> retval
getOptimalNewCameraMatrix(...)
getOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imageSize, alpha[, newImgSize[, centerPrincipalPoint]]) -> retval, validPixROI
getPerspectiveTransform(...)
getPerspectiveTransform(src, dst) -> retval
getRectSubPix(...)
getRectSubPix(image, patchSize, center[, patch[, patchType]]) -> patch
getRotationMatrix2D(...)
getRotationMatrix2D(center, angle, scale) -> retval
getStructuringElement(...)
getStructuringElement(shape, ksize[, anchor]) -> retval
getTextSize(...)
getTextSize(text, fontFace, fontScale, thickness) -> retval, baseLine
getTickCount(...)
getTickCount() -> retval
getTickFrequency(...)
getTickFrequency() -> retval
getTrackbarPos(...)
getTrackbarPos(trackbarname, winname) -> retval
getValidDisparityROI(...)
getValidDisparityROI(roi1, roi2, minDisparity, numberOfDisparities, SADWindowSize) -> retval
getWindowProperty(...)
getWindowProperty(winname, prop_id) -> retval
goodFeaturesToTrack(...)
goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]]) -> corners
grabCut(...)
grabCut(img, mask, rect, bgdModel, fgdModel, iterCount[, mode]) -> mask, bgdModel, fgdModel
groupRectangles(...)
groupRectangles(rectList, groupThreshold[, eps]) -> rectList, weights
hconcat(...)
hconcat(src[, dst]) -> dst
idct(...)
idct(src[, dst[, flags]]) -> dst
idft(...)
idft(src[, dst[, flags[, nonzeroRows]]]) -> dst
illuminationChange(...)
illuminationChange(src, mask[, dst[, alpha[, beta]]]) -> dst
imdecode(...)
imdecode(buf, flags) -> retval
imencode(...)
imencode(ext, img[, params]) -> retval, buf
imread(...)
imread(filename[, flags]) -> retval
imreadmulti(...)
imreadmulti(filename, mats[, flags]) -> retval
imshow(...)
imshow(winname, mat) -> None
imwrite(...)
imwrite(filename, img[, params]) -> retval
inRange(...)
inRange(src, lowerb, upperb[, dst]) -> dst
initCameraMatrix2D(...)
initCameraMatrix2D(objectPoints, imagePoints, imageSize[, aspectRatio]) -> retval
initUndistortRectifyMap(...)
initUndistortRectifyMap(cameraMatrix, distCoeffs, R, newCameraMatrix, size, m1type[, map1[, map2]]) -> map1, map2
initWideAngleProjMap(...)
initWideAngleProjMap(cameraMatrix, distCoeffs, imageSize, destImageWidth, m1type[, map1[, map2[, projType[, alpha]]]]) -> retval, map1, map2
inpaint(...)
inpaint(src, inpaintMask, inpaintRadius, flags[, dst]) -> dst
insertChannel(...)
insertChannel(src, dst, coi) -> dst
integral(...)
integral(src[, sum[, sdepth]]) -> sum
integral2(...)
integral2(src[, sum[, sqsum[, sdepth[, sqdepth]]]]) -> sum, sqsum
integral3(...)
integral3(src[, sum[, sqsum[, tilted[, sdepth[, sqdepth]]]]]) -> sum, sqsum, tilted
intersectConvexConvex(...)
intersectConvexConvex(_p1, _p2[, _p12[, handleNested]]) -> retval, _p12
invert(...)
invert(src[, dst[, flags]]) -> retval, dst
invertAffineTransform(...)
invertAffineTransform(M[, iM]) -> iM
isContourConvex(...)
isContourConvex(contour) -> retval
kmeans(...)
kmeans(data, K, bestLabels, criteria, attempts, flags[, centers]) -> retval, bestLabels, centers
line(...)
line(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> img
linearPolar(...)
linearPolar(src, center, maxRadius, flags[, dst]) -> dst
log(...)
log(src[, dst]) -> dst
logPolar(...)
logPolar(src, center, M, flags[, dst]) -> dst
magnitude(...)
magnitude(x, y[, magnitude]) -> magnitude
matMulDeriv(...)
matMulDeriv(A, B[, dABdA[, dABdB]]) -> dABdA, dABdB
matchShapes(...)
matchShapes(contour1, contour2, method, parameter) -> retval
matchTemplate(...)
matchTemplate(image, templ, method[, result[, mask]]) -> result
max(...)
max(src1, src2[, dst]) -> dst
mean(...)
mean(src[, mask]) -> retval
meanShift(...)
meanShift(probImage, window, criteria) -> retval, window
meanStdDev(...)
meanStdDev(src[, mean[, stddev[, mask]]]) -> mean, stddev
medianBlur(...)
medianBlur(src, ksize[, dst]) -> dst
merge(...)
merge(mv[, dst]) -> dst
min(...)
min(src1, src2[, dst]) -> dst
minAreaRect(...)
minAreaRect(points) -> retval
minEnclosingCircle(...)
minEnclosingCircle(points) -> center, radius
minEnclosingTriangle(...)
minEnclosingTriangle(points[, triangle]) -> retval, triangle
minMaxLoc(...)
minMaxLoc(src[, mask]) -> minVal, maxVal, minLoc, maxLoc
mixChannels(...)
mixChannels(src, dst, fromTo) -> dst
moments(...)
moments(array[, binaryImage]) -> retval
morphologyEx(...)
morphologyEx(src, op, kernel[, dst[, anchor[, iterations[, borderType[, borderValue]]]]]) -> dst
moveWindow(...)
moveWindow(winname, x, y) -> None
mulSpectrums(...)
mulSpectrums(a, b, flags[, c[, conjB]]) -> c
mulTransposed(...)
mulTransposed(src, aTa[, dst[, delta[, scale[, dtype]]]]) -> dst
multiply(...)
multiply(src1, src2[, dst[, scale[, dtype]]]) -> dst
namedWindow(...)
namedWindow(winname[, flags]) -> None
norm(...)
norm(src1[, normType[, mask]]) -> retval or norm(src1, src2[, normType[, mask]]) -> retval
normalize(...)
normalize(src, dst[, alpha[, beta[, norm_type[, dtype[, mask]]]]]) -> dst
patchNaNs(...)
patchNaNs(a[, val]) -> a
pencilSketch(...)
pencilSketch(src[, dst1[, dst2[, sigma_s[, sigma_r[, shade_factor]]]]]) -> dst1, dst2
perspectiveTransform(...)
perspectiveTransform(src, m[, dst]) -> dst
phase(...)
phase(x, y[, angle[, angleInDegrees]]) -> angle
phaseCorrelate(...)
phaseCorrelate(src1, src2[, window]) -> retval, response
pointPolygonTest(...)
pointPolygonTest(contour, pt, measureDist) -> retval
polarToCart(...)
polarToCart(magnitude, angle[, x[, y[, angleInDegrees]]]) -> x, y
polylines(...)
polylines(img, pts, isClosed, color[, thickness[, lineType[, shift]]]) -> img
pow(...)
pow(src, power[, dst]) -> dst
preCornerDetect(...)
preCornerDetect(src, ksize[, dst[, borderType]]) -> dst
projectPoints(...)
projectPoints(objectPoints, rvec, tvec, cameraMatrix, distCoeffs[, imagePoints[, jacobian[, aspectRatio]]]) -> imagePoints, jacobian
putText(...)
putText(img, text, org, fontFace, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]]) -> img
pyrDown(...)
pyrDown(src[, dst[, dstsize[, borderType]]]) -> dst
pyrMeanShiftFiltering(...)
pyrMeanShiftFiltering(src, sp, sr[, dst[, maxLevel[, termcrit]]]) -> dst
pyrUp(...)
pyrUp(src[, dst[, dstsize[, borderType]]]) -> dst
randShuffle(...)
randShuffle(dst[, iterFactor]) -> dst
randn(...)
randn(dst, mean, stddev) -> dst
randu(...)
randu(dst, low, high) -> dst
recoverPose(...)
recoverPose(E, points1, points2[, R[, t[, focal[, pp[, mask]]]]]) -> retval, R, t, mask
rectangle(...)
rectangle(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> img
rectify3Collinear(...)
rectify3Collinear(cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, cameraMatrix3, distCoeffs3, imgpt1, imgpt3, imageSize, R12, T12, R13, T13, alpha, newImgSize, flags[, R1[, R2[, R3[, P1[, P2[, P3[, Q]]]]]]]) -> retval, R1, R2, R3, P1, P2, P3, Q, roi1, roi2
reduce(...)
reduce(src, dim, rtype[, dst[, dtype]]) -> dst
remap(...)
remap(src, map1, map2, interpolation[, dst[, borderMode[, borderValue]]]) -> dst
repeat(...)
repeat(src, ny, nx[, dst]) -> dst
reprojectImageTo3D(...)
reprojectImageTo3D(disparity, Q[, _3dImage[, handleMissingValues[, ddepth]]]) -> _3dImage
resize(...)
resize(src, dsize[, dst[, fx[, fy[, interpolation]]]]) -> dst
resizeWindow(...)
resizeWindow(winname, width, height) -> None
rotatedRectangleIntersection(...)
rotatedRectangleIntersection(rect1, rect2[, intersectingRegion]) -> retval, intersectingRegion
scaleAdd(...)
scaleAdd(src1, alpha, src2[, dst]) -> dst
seamlessClone(...)
seamlessClone(src, dst, mask, p, flags[, blend]) -> blend
sepFilter2D(...)
sepFilter2D(src, ddepth, kernelX, kernelY[, dst[, anchor[, delta[, borderType]]]]) -> dst