OpenCV 2.4 Cheat
Sheet (C++)
The OpenCV C++
reference manual is here: http: // docs. opencv. org .
Use Quick Search to find descriptions of the particular functions and classes
Key
(từ khóa)
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Classes (Lớp)
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Point_
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Template 2D point class - Lớp điểm ảnh 2D
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Point3_
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Template 3D point class - Lớp điểm ảnh 3D
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Size_
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Template size (width, height) class - Lớp kích thước ảnh (rộng, cao)
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Vec
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Template short vector class
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Matx
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Template small matrix class
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Scalar
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4-element vector
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Rect
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Rectangle
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Range
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Integer value range
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Mat
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2D or multi-dimensional dense array (can
be used to store matrices, images, histograms, feature descriptors, voxel volumes
etc.)
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SparseMat
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Multi-dimensional
sparse array
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Ptr
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Template smart pointer class
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Function
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Meaning
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Mat image(240, 320, CV_8UC3);
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image.create(480,
640, CV_8UC3);
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Mat A33(3, 3, CV_32F, Scalar(5));
Mat B33(3, 3, CV_32F); B33 = Scalar(5);
Mat C33 = Mat::ones(3, 3, CV_32F)*5.;
Mat D33 = Mat::zeros(3, 3, CV_32F) + 5.;
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double a = CV_PI/3;
Mat A22 = (Mat_(2, 2) << cos(a),
-sin(a), sin(a), cos(a));
float B22data[] = {cos(a), -sin(a), sin(a), cos(a)};
Mat B22 = Mat(2, 2, CV_32F, B22data).clone();
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randu(image,
Scalar(0), Scalar(256)); // uniform dist
randn(image,
Scalar(128), Scalar(10)); // Gaussian dist
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(without copying the data)
Mat image_alias = image;
float* Idata=new float[480*640*3];
Mat I(480, 640, CV_32FC3, Idata);
Mat iP(iptvec); // iP _ 10x1 CV_32SC2 matrix
IplImage* oldC0 =
cvCreateImage(cvSize(320,240),16,1);
Mat newC = cvarrToMat(oldC0);
IplImage oldC1 = newC; CvMat oldC2 = newC;
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(with copying the data)
Mat newC2 = cvarrToMat(oldC0).clone();
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A33.at(i,j) =
A33.at(j,i)+1;
Mat
dyImage(image.size(), image.type());
for(int y = 1; y
< image.rows-1; y++) {
Vec3b* prevRow =
image.ptr(y-1);
Vec3b* nextRow =
image.ptr(y+1);
for(int x = 0; x < image.cols; x++)
for(int c = 0; c < 3; c++)
dyImage.at(y,x)[c] =
saturate_cast(nextRow[x][c] - prevRow[x][c]);
}
Mat_::iterator it = image.begin(), itEnd
= image.end();
for(; it != itEnd; ++it)
(*it)[1] ^= 255;
Function
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Meaning
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src.copyTo(dst)
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Copy matrix to another one
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src.convertTo(dst,type,scale,shift)
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Scale and convert to another datatype
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m.clone()
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Make deep copy of a matrix
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m.reshape(nch,nrows)
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Change matrix dimensions and/or number of channels without
copying data
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m.row(i), m.col(i)
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Take a matrix row/column
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m.rowRange(Range(i1,i2))
m.colRange(Range(j1,j2))
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Take a matrix row/column span
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m.diag(i)
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Take a matrix diagonal
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m(Range(i1,i2),Range(j1,j2)), m(roi)
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Take a submatrix
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m.repeat(ny,nx)
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Make a bigger matrix from a smaller one
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flip(src,dst,dir)
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Reverse the order of matrix rows and/or columns
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split(...)
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Split multi-channel matrix into separate channels
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merge(...)
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Make a multi-channel matrix out of the separate channels
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mixChannels(...)
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Generalized form of split() and merge()
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randShuffle(...)
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Randomly shuffle matrix elements
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Ví dụ 1. Smooth image ROI in-place
Mat imgroi =
image(Rect(10, 20, 100, 100));
GaussianBlur(imgroi,
imgroi, Size(5, 5), 1.2, 1.2);
Ví dụ 2. Somewhere in a linear algebra algorithm
m.row(i) += m.row(j)*alpha;
Ví dụ 3. Copy image ROI to another image with conversion
Rect r(1, 1, 10, 20);
Mat dstroi = dst(Rect(0,10,r.width,r.height));
src(r).convertTo(dstroi, dstroi.type(), 1, 0);
OpenCV implements most common arithmetical, logical and other
matrix operations, such as
Function
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Meaning
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add(), subtract(), multiply(), divide(), absdiff(),
bitwise_and(), bitwise_or(),
itwise_xor(), max(), min(), compare()
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Correspondingly, addition, subtraction, element-wise
multiplication ... comparison of two matrices or a matrix and a scalar.
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Ví dụ. Alpha compositing function:
void alphaCompose(const Mat&
rgba1, const Mat& rgba2, Mat& rgba_dest)
{
Mat a1(rgba1.size(), rgba1.type()), ra1;
Mat a2(rgba2.size(), rgba2.type());
int mixch[]={3, 0, 3, 1, 3, 2, 3, 3};
mixChannels(&rgba1, 1, &a1, 1, mixch, 4);
mixChannels(&rgba2, 1, &a2, 1, mixch, 4);
subtract(Scalar::all(255), a1, ra1);
bitwise_or(a1, Scalar(0,0,0,255), a1);
bitwise_or(a2, Scalar(0,0,0,255), a2);
multiply(a2, ra1, a2, 1./255);
multiply(a1, rgba1, a1, 1./255);
multiply(a2, rgba2, a2, 1./255);
add(a1, a2, rgba_dest);
}
Function
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Meaning
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sum(), mean(), meanStdDev(), norm(), countNonZero(), minMaxLoc(),
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various statistics of matrix elements.
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exp(), log(), pow(), sqrt(), cartToPolar(), polarToCart()
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the classical math functions.
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scaleAdd(), transpose(), gemm(), invert(), solve(), determinant(),
trace(), eigen(), SVD
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the algebraic functions + SVD class.
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dft(), idft(), dct(), idct(),
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discrete Fourier and cosine transformations
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For some operations a more convenient algebraic notation can be used, for Ví dụ:
Mat delta = (J.t()*J + lambda*Mat::eye(J.cols, J.cols, J.type())).inv(CV_SVD)*(J.t()*err);
implements the core of Levenberg-Marquardt optimization algorithm.
Function
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Meaning
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filter2D()
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Non-separable linear filter
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sepFilter2D()
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Separable linear filter
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boxFilter(),
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Smooth the image with one of the linear or non-linear filters
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GaussianBlur(),medianBlur(),
bilateralFilter()
Sobel(), Scharr()
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Compute the spatial image derivatives
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Laplacian()
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compute Laplacian
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erode(), dilate()
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Morphological operations
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Ví dụ. Filter image in-place with a 3x3 high-pass kernel (preserve
negative responses by shifting the result by 128):
filter2D(image, image, image.depth(), (Mat_(3,3)
<-1 -1="" 128="" 9="" o:p="" point="">
Function
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Meaning
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resize()
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Resize image
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getRectSubPix()
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Extract an image patch
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warpAffine()
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Warp image afinely
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warpPerspective()
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Warp image perspectively
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remap()
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Generic image warping
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convertMaps()
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Optimize maps for a faster remap() execution
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Ví dụ. Decimate image by factor of 
:
Mat dst; resize(src, dst, Size(), 1./sqrt(2), 1./sqrt(2));
Function
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Meaning
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cvtColor()
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Convert image from one color space to another
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threshold(),
adaptivethreshold()
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Convert grayscale image to binary image using a fixed or a
variable threshold
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floodFill()
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Find a connected component using region growing algorithm
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integral()
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Compute integral image
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distanceTransform()
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build distance map or discrete Voronoi diagram for a binary
image.
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watershed(),grabCut()
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marker-based image segmentation algorithms. See the samples
watershed.cpp and grabcut.cpp.
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Function
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Meaning
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calcHist()
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Compute image(s) histogram
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calcBackProject()
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Back-project the histogram
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equalizeHist()
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Normalize image brightness and contrast
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compareHist()
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Compare two histograms
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Ví dụ. Compute Hue-Saturation histogram of an image:
Mat hsv, H;
cvtColor(image, hsv, CV_BGR2HSV);
int planes[]={0, 1}, hsize[] = {32, 32};
calcHist(&hsv, 1, planes, Mat(), H, 2, hsize, 0);
See contours2.cpp and squares.cpp samples
on what are the contours and how to use them.
XML/YAML storages are collections (possibly nested) of scalar values, structures and
heterogeneous lists.
// Type of the file is determined
from the extension
FileStorage fs("test.yml",
FileStorage::WRITE);
fs << "i" << 5 <<
"r" << 3.1 << "str" <<
"ABCDEFGH";
fs
<< "mtx" << Mat::eye(3,3,CV_32F);
fs << "mylist" <<
"[" << CV_PI << "1+1" << "{:" <<
"month" << 12 << "day" << 31 <<
"year" << 1969 << "}" << "]";
fs << "mystruct" <<
"{" << "x" << 1 << "y" <<
2 << "width" << 100 << "height" <<
200 << "lbp" << "[:";
const uchar arr[] = {0, 1, 1, 0, 1, 1,
0, 1};
fs.writeRaw("u", arr,
(int)(sizeof(arr)/sizeof(arr[0])));
fs << "]" <<
"}";
Scalars (integers, floating-point
numbers, text strings), matrices, STL vectors of scalars and some other types
can be written to the file storages using << operator.
// Type of the file is determined from the content
FileStorage fs("test.yml", FileStorage::READ);
int i1 = (int)fs["i"]; double r1 =
(double)fs["r"];
string str1 = (string)fs["str"];
Mat M; fs["mtx"] >> M;
FileNode tl = fs["mylist"];
CV_Assert(tl.type() == FileNode::SEQ && tl.size() == 3);
double tl0 = (double)tl[0]; string tl1 = (string)tl[1];
int m = (int)tl[2]["month"], d =
(int)tl[2]["day"];
int year = (int)tl[2]["year"];
FileNode tm = fs["mystruct"];
Rect r; r.x = (int)tm["x"], r.y =
(int)tm["y"];
r.width = (int)tm["width"], r.height =
(int)tm["height"];
int lbp_val = 0;
FileNodeIterator it = tm["lbp"].begin();
for(int k = 0; k < 8; k++, ++it)
lbp_val |= ((int)*it) << k;
Scalars are read using the corresponding FileNode's cast operators.
Matrices and some other types are read using operator. Lists can be read using
FileNodeIterator's.
imwrite("myimage.jpg", image);
Mat image_color_copy = imread("myimage.jpg", 1);
Mat image_grayscale_copy = imread("myimage.jpg", 0);
The functions can read/write images in the following formats:
BMP (.bmp), JPEG (.jpg, .jpeg), TIFF (.tif, .tiff),
PNG (.png), PBM/PGM/PPM (.p?m), Sun Raster (.sr), JPEG 2000 (.jp2).
Every format supports 8-bit, 1 or 3-channel images. Some formats
(PNG, JPEG 2000) support 16 bits per channel.
VideoCapture cap;
if(argc > 1) cap.open(string(argv[1])); else cap.open(0);
Mat frame; namedWindow("video", 1);
for(;;) {
cap >> frame; if(!frame.data) break;
imshow("video", frame); if(waitKey(30) >= 0)
break;
}
Function
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Meaning
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namedWindow(winname,flags)
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Create named highgui window
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destroyWindow(winname)
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Destroy the specified window
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imshow(winname, mtx)
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Show image in the window
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waitKey(delay)
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Wait for a key press during the specified time interval (or forever).
Process events while waiting. Do not forget
to call this function several times a second in your code.
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createTrackbar(...)
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Add trackbar (slider) to the specified window
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setMouseCallback(...)
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Set the callback on mouse clicks and movements in the specified
window
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See camshiftdemo.cpp and other OpenCV samples on how to use the GUI functions.
Function
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Meaning
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calibrateCamera()
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Calibrate camera from several views of a calibration pattern.
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findChessboardCorners()
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Find feature points on the checker board calibration pattern.
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solvePnP()
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Find the object pose from the known projections of its feature
points.
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stereoCalibrate()
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Calibrate stereo camera.
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stereoRectify()
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Compute the rectification transforms for a calibrated stereo
camera.
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initUndistortRectifyMap()
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Compute rectification map (for remap()) for each stereo camera
head.
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StereoBM, StereoSGBM
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The stereo correspondence engines to be run on rectified stereo
pairs.
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reprojectImageTo3D()
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Convert disparity map to 3D point cloud.
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findHomography()
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Find best-fit perspective transformation between two 2D point
sets.
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