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Doxygen documentation for: highgui, video, imgcodecs and videoio

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476
modules/highgui/include/opencv2/highgui.hpp
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@ -47,11 +47,92 @@
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
/**
@defgroup highgui High-level GUI
While OpenCV was designed for use in full-scale applications and can be used within functionally
rich UI frameworks (such as Qt\*, WinForms\*, or Cocoa\*) or without any UI at all, sometimes there
it is required to try functionality quickly and visualize the results. This is what the HighGUI
module has been designed for.
It provides easy interface to:
- Create and manipulate windows that can display images and "remember" their content (no need to
handle repaint events from OS).
- Add trackbars to the windows, handle simple mouse events as well as keyboard commands.
@{
@defgroup highgui_opengl OpenGL support
@defgroup highgui_qt Qt New Functions
![image](pics/qtgui.png)
This figure explains new functionality implemented with Qt\* GUI. The new GUI provides a statusbar,
a toolbar, and a control panel. The control panel can have trackbars and buttonbars attached to it.
If you cannot see the control panel, press Ctrl+P or right-click any Qt window and select **Display
properties window**.
- To attach a trackbar, the window name parameter must be NULL.
- To attach a buttonbar, a button must be created. If the last bar attached to the control panel
is a buttonbar, the new button is added to the right of the last button. If the last bar
attached to the control panel is a trackbar, or the control panel is empty, a new buttonbar is
created. Then, a new button is attached to it.
See below the example used to generate the figure: :
@code
int main(int argc, char *argv[])
int value = 50;
int value2 = 0;
cvNamedWindow("main1",CV_WINDOW_NORMAL);
cvNamedWindow("main2",CV_WINDOW_AUTOSIZE | CV_GUI_NORMAL);
cvCreateTrackbar( "track1", "main1", &value, 255, NULL);//OK tested
char* nameb1 = "button1";
char* nameb2 = "button2";
cvCreateButton(nameb1,callbackButton,nameb1,CV_CHECKBOX,1);
cvCreateButton(nameb2,callbackButton,nameb2,CV_CHECKBOX,0);
cvCreateTrackbar( "track2", NULL, &value2, 255, NULL);
cvCreateButton("button5",callbackButton1,NULL,CV_RADIOBOX,0);
cvCreateButton("button6",callbackButton2,NULL,CV_RADIOBOX,1);
cvSetMouseCallback( "main2",on_mouse,NULL );
IplImage* img1 = cvLoadImage("files/flower.jpg");
IplImage* img2 = cvCreateImage(cvGetSize(img1),8,3);
CvCapture* video = cvCaptureFromFile("files/hockey.avi");
IplImage* img3 = cvCreateImage(cvGetSize(cvQueryFrame(video)),8,3);
while(cvWaitKey(33) != 27)
{
cvAddS(img1,cvScalarAll(value),img2);
cvAddS(cvQueryFrame(video),cvScalarAll(value2),img3);
cvShowImage("main1",img2);
cvShowImage("main2",img3);
}
cvDestroyAllWindows();
cvReleaseImage(&img1);
cvReleaseImage(&img2);
cvReleaseImage(&img3);
cvReleaseCapture(&video);
return 0;
}
@endcode
@defgroup highgui_c C API
@}
*/
///////////////////////// graphical user interface //////////////////////////
namespace cv
{
//! @addtogroup highgui
//! @{
// Flags for namedWindow
enum { WINDOW_NORMAL = 0x00000000, // the user can resize the window (no constraint) / also use to switch a fullscreen window to a normal size
WINDOW_AUTOSIZE = 0x00000001, // the user cannot resize the window, the size is constrainted by the image displayed
@ -117,54 +198,334 @@ typedef void (*TrackbarCallback)(int pos, void* userdata);
typedef void (*OpenGlDrawCallback)(void* userdata);
typedef void (*ButtonCallback)(int state, void* userdata);
/** @brief Creates a window.
@param winname Name of the window in the window caption that may be used as a window identifier.
@param flags Flags of the window. The supported flags are:
> - **WINDOW\_NORMAL** If this is set, the user can resize the window (no constraint).
> - **WINDOW\_AUTOSIZE** If this is set, the window size is automatically adjusted to fit the
> displayed image (see imshow ), and you cannot change the window size manually.
> - **WINDOW\_OPENGL** If this is set, the window will be created with OpenGL support.
The function namedWindow creates a window that can be used as a placeholder for images and
trackbars. Created windows are referred to by their names.
If a window with the same name already exists, the function does nothing.
You can call destroyWindow or destroyAllWindows to close the window and de-allocate any associated
memory usage. For a simple program, you do not really have to call these functions because all the
resources and windows of the application are closed automatically by the operating system upon exit.
@note
Qt backend supports additional flags:
- **CV\_WINDOW\_NORMAL or CV\_WINDOW\_AUTOSIZE:** CV\_WINDOW\_NORMAL enables you to resize the
window, whereas CV\_WINDOW\_AUTOSIZE adjusts automatically the window size to fit the
displayed image (see imshow ), and you cannot change the window size manually.
- **CV\_WINDOW\_FREERATIO or CV\_WINDOW\_KEEPRATIO:** CV\_WINDOW\_FREERATIO adjusts the image
with no respect to its ratio, whereas CV\_WINDOW\_KEEPRATIO keeps the image ratio.
- **CV\_GUI\_NORMAL or CV\_GUI\_EXPANDED:** CV\_GUI\_NORMAL is the old way to draw the window
without statusbar and toolbar, whereas CV\_GUI\_EXPANDED is a new enhanced GUI.
By default, flags == CV\_WINDOW\_AUTOSIZE | CV\_WINDOW\_KEEPRATIO | CV\_GUI\_EXPANDED
*/
CV_EXPORTS_W void namedWindow(const String& winname, int flags = WINDOW_AUTOSIZE);
/** @brief Destroys a window.
@param winname Name of the window to be destroyed.
The function destroyWindow destroys the window with the given name.
*/
CV_EXPORTS_W void destroyWindow(const String& winname);
/** @brief Destroys all of the HighGUI windows.
The function destroyAllWindows destroys all of the opened HighGUI windows.
*/
CV_EXPORTS_W void destroyAllWindows();
CV_EXPORTS_W int startWindowThread();
/** @brief Waits for a pressed key.
@param delay Delay in milliseconds. 0 is the special value that means "forever".
The function waitKey waits for a key event infinitely (when \f$\texttt{delay}\leq 0\f$ ) or for delay
milliseconds, when it is positive. Since the OS has a minimum time between switching threads, the
function will not wait exactly delay ms, it will wait at least delay ms, depending on what else is
running on your computer at that time. It returns the code of the pressed key or -1 if no key was
pressed before the specified time had elapsed.
@note
This function is the only method in HighGUI that can fetch and handle events, so it needs to be
called periodically for normal event processing unless HighGUI is used within an environment that
takes care of event processing.
@note
The function only works if there is at least one HighGUI window created and the window is active.
If there are several HighGUI windows, any of them can be active.
*/
CV_EXPORTS_W int waitKey(int delay = 0);
/** @brief Displays an image in the specified window.
@param winname Name of the window.
@param mat Image to be shown.
The function imshow displays an image in the specified window. If the window was created with the
CV\_WINDOW\_AUTOSIZE flag, the image is shown with its original size. Otherwise, the image is scaled
to fit the window. The function may scale the image, depending on its depth:
- If the image is 8-bit unsigned, it is displayed as is.
- If the image is 16-bit unsigned or 32-bit integer, the pixels are divided by 256. That is, the
value range [0,255\*256] is mapped to [0,255].
- If the image is 32-bit floating-point, the pixel values are multiplied by 255. That is, the
value range [0,1] is mapped to [0,255].
If window was created with OpenGL support, imshow also support ogl::Buffer , ogl::Texture2D and
cuda::GpuMat as input.
@note This function should be followed by waitKey function which displays the image for specified
milliseconds. Otherwise, it won't display the image. For example, waitKey(0) will display the window
infinitely until any keypress (it is suitable for image display). waitKey(25) will display a frame
for 25 ms, after which display will be automatically closed. (If you put it in a loop to read
videos, it will display the video frame-by-frame)
@note
[Windows Backend Only] Pressing Ctrl+C will copy the image to the clipboard.
*/
CV_EXPORTS_W void imshow(const String& winname, InputArray mat);
/** @brief Resizes window to the specified size
@param winname Window name
@param width The new window width
@param height The new window height
@note
- The specified window size is for the image area. Toolbars are not counted.
- Only windows created without CV\_WINDOW\_AUTOSIZE flag can be resized.
*/
CV_EXPORTS_W void resizeWindow(const String& winname, int width, int height);
/** @brief Moves window to the specified position
@param winname Window name
@param x The new x-coordinate of the window
@param y The new y-coordinate of the window
*/
CV_EXPORTS_W void moveWindow(const String& winname, int x, int y);
/** @brief Changes parameters of a window dynamically.
@param winname Name of the window.
@param prop_id Window property to edit. The following operation flags are available:
- **CV\_WND\_PROP\_FULLSCREEN** Change if the window is fullscreen ( CV\_WINDOW\_NORMAL or
CV\_WINDOW\_FULLSCREEN ).
- **CV\_WND\_PROP\_AUTOSIZE** Change if the window is resizable (CV\_WINDOW\_NORMAL or
CV\_WINDOW\_AUTOSIZE ).
- **CV\_WND\_PROP\_ASPECTRATIO** Change if the aspect ratio of the image is preserved (
CV\_WINDOW\_FREERATIO or CV\_WINDOW\_KEEPRATIO ).
@param prop_value New value of the window property. The following operation flags are available:
- **CV\_WINDOW\_NORMAL** Change the window to normal size or make the window resizable.
- **CV\_WINDOW\_AUTOSIZE** Constrain the size by the displayed image. The window is not
resizable.
- **CV\_WINDOW\_FULLSCREEN** Change the window to fullscreen.
- **CV\_WINDOW\_FREERATIO** Make the window resizable without any ratio constraints.
- **CV\_WINDOW\_KEEPRATIO** Make the window resizable, but preserve the proportions of the
displayed image.
The function setWindowProperty enables changing properties of a window.
*/
CV_EXPORTS_W void setWindowProperty(const String& winname, int prop_id, double prop_value);
/** @brief Updates window title
*/
CV_EXPORTS_W void setWindowTitle(const String& winname, const String& title);
/** @brief Provides parameters of a window.
@param winname Name of the window.
@param prop_id Window property to retrieve. The following operation flags are available:
- **CV\_WND\_PROP\_FULLSCREEN** Change if the window is fullscreen ( CV\_WINDOW\_NORMAL or
CV\_WINDOW\_FULLSCREEN ).
- **CV\_WND\_PROP\_AUTOSIZE** Change if the window is resizable (CV\_WINDOW\_NORMAL or
CV\_WINDOW\_AUTOSIZE ).
- **CV\_WND\_PROP\_ASPECTRATIO** Change if the aspect ratio of the image is preserved
(CV\_WINDOW\_FREERATIO or CV\_WINDOW\_KEEPRATIO ).
See setWindowProperty to know the meaning of the returned values.
The function getWindowProperty returns properties of a window.
*/
CV_EXPORTS_W double getWindowProperty(const String& winname, int prop_id);
//! assigns callback for mouse events
/** @brief Sets mouse handler for the specified window
@param winname Window name
@param onMouse Mouse callback. See OpenCV samples, such as
<https://github.com/Itseez/opencv/tree/master/samples/cpp/ffilldemo.cpp>, on how to specify and
use the callback.
@param userdata The optional parameter passed to the callback.
*/
CV_EXPORTS void setMouseCallback(const String& winname, MouseCallback onMouse, void* userdata = 0);
/** @brief Gets the mouse-wheel motion delta, when handling mouse-wheel events EVENT\_MOUSEWHEEL and
EVENT\_MOUSEHWHEEL.
@param flags The mouse callback flags parameter.
For regular mice with a scroll-wheel, delta will be a multiple of 120. The value 120 corresponds to
a one notch rotation of the wheel or the threshold for action to be taken and one such action should
occur for each delta. Some high-precision mice with higher-resolution freely-rotating wheels may
generate smaller values.
For EVENT\_MOUSEWHEEL positive and negative values mean forward and backward scrolling,
respectively. For EVENT\_MOUSEHWHEEL, where available, positive and negative values mean right and
left scrolling, respectively.
With the C API, the macro CV\_GET\_WHEEL\_DELTA(flags) can be used alternatively.
@note
Mouse-wheel events are currently supported only on Windows.
*/
CV_EXPORTS int getMouseWheelDelta(int flags);
/** @brief Creates a trackbar and attaches it to the specified window.
@param trackbarname Name of the created trackbar.
@param winname Name of the window that will be used as a parent of the created trackbar.
@param value Optional pointer to an integer variable whose value reflects the position of the
slider. Upon creation, the slider position is defined by this variable.
@param count Maximal position of the slider. The minimal position is always 0.
@param onChange Pointer to the function to be called every time the slider changes position. This
function should be prototyped as void Foo(int,void\*); , where the first parameter is the trackbar
position and the second parameter is the user data (see the next parameter). If the callback is
the NULL pointer, no callbacks are called, but only value is updated.
@param userdata User data that is passed as is to the callback. It can be used to handle trackbar
events without using global variables.
The function createTrackbar creates a trackbar (a slider or range control) with the specified name
and range, assigns a variable value to be a position synchronized with the trackbar and specifies
the callback function onChange to be called on the trackbar position change. The created trackbar is
displayed in the specified window winname.
@note
**[Qt Backend Only]** winname can be empty (or NULL) if the trackbar should be attached to the
control panel.
Clicking the label of each trackbar enables editing the trackbar values manually.
@note
- An example of using the trackbar functionality can be found at
opencv\_source\_code/samples/cpp/connected\_components.cpp
*/
CV_EXPORTS int createTrackbar(const String& trackbarname, const String& winname,
int* value, int count,
TrackbarCallback onChange = 0,
void* userdata = 0);
/** @brief Returns the trackbar position.
@param trackbarname Name of the trackbar.
@param winname Name of the window that is the parent of the trackbar.
The function returns the current position of the specified trackbar.
@note
**[Qt Backend Only]** winname can be empty (or NULL) if the trackbar is attached to the control
panel.
*/
CV_EXPORTS_W int getTrackbarPos(const String& trackbarname, const String& winname);
/** @brief Sets the trackbar position.
@param trackbarname Name of the trackbar.
@param winname Name of the window that is the parent of trackbar.
@param pos New position.
The function sets the position of the specified trackbar in the specified window.
@note
**[Qt Backend Only]** winname can be empty (or NULL) if the trackbar is attached to the control
panel.
*/
CV_EXPORTS_W void setTrackbarPos(const String& trackbarname, const String& winname, int pos);
//! @addtogroup highgui_opengl OpenGL support
//! @{
// OpenGL support
CV_EXPORTS void imshow(const String& winname, const ogl::Texture2D& tex);
/** @brief Sets a callback function to be called to draw on top of displayed image.
@param winname Name of the window.
@param onOpenGlDraw Pointer to the function to be called every frame. This function should be
prototyped as void Foo(void\*) .
@param userdata Pointer passed to the callback function. *(Optional)*
The function setOpenGlDrawCallback can be used to draw 3D data on the window. See the example of
callback function below: :
@code
void on_opengl(void* param)
{
glLoadIdentity();
glTranslated(0.0, 0.0, -1.0);
glRotatef( 55, 1, 0, 0 );
glRotatef( 45, 0, 1, 0 );
glRotatef( 0, 0, 0, 1 );
static const int coords[6][4][3] = {
{ { +1, -1, -1 }, { -1, -1, -1 }, { -1, +1, -1 }, { +1, +1, -1 } },
{ { +1, +1, -1 }, { -1, +1, -1 }, { -1, +1, +1 }, { +1, +1, +1 } },
{ { +1, -1, +1 }, { +1, -1, -1 }, { +1, +1, -1 }, { +1, +1, +1 } },
{ { -1, -1, -1 }, { -1, -1, +1 }, { -1, +1, +1 }, { -1, +1, -1 } },
{ { +1, -1, +1 }, { -1, -1, +1 }, { -1, -1, -1 }, { +1, -1, -1 } },
{ { -1, -1, +1 }, { +1, -1, +1 }, { +1, +1, +1 }, { -1, +1, +1 } }
};
for (int i = 0; i < 6; ++i) {
glColor3ub( i*20, 100+i*10, i*42 );
glBegin(GL_QUADS);
for (int j = 0; j < 4; ++j) {
glVertex3d(0.2 * coords[i][j][0], 0.2 * coords[i][j][1], 0.2 * coords[i][j][2]);
}
glEnd();
}
}
@endcode
*/
CV_EXPORTS void setOpenGlDrawCallback(const String& winname, OpenGlDrawCallback onOpenGlDraw, void* userdata = 0);
/** @brief Sets the specified window as current OpenGL context.
@param winname Window name
*/
CV_EXPORTS void setOpenGlContext(const String& winname);
/** @brief Force window to redraw its context and call draw callback ( setOpenGlDrawCallback ).
@param winname Window name
*/
CV_EXPORTS void updateWindow(const String& winname);
//! @} highgui_opengl
//! @addtogroup highgui_qt
//! @{
// Only for Qt
struct QtFont
@ -182,27 +543,138 @@ struct QtFont
int line_type; // Qt: PointSize
};
/** @brief Creates the font to draw a text on an image.
@param nameFont Name of the font. The name should match the name of a system font (such as
*Times*). If the font is not found, a default one is used.
@param pointSize Size of the font. If not specified, equal zero or negative, the point size of the
font is set to a system-dependent default value. Generally, this is 12 points.
@param color Color of the font in BGRA where A = 255 is fully transparent. Use the macro CV \_ RGB
for simplicity.
@param weight Font weight. The following operation flags are available:
- **CV\_FONT\_LIGHT** Weight of 25
- **CV\_FONT\_NORMAL** Weight of 50
- **CV\_FONT\_DEMIBOLD** Weight of 63
- **CV\_FONT\_BOLD** Weight of 75
- **CV\_FONT\_BLACK** Weight of 87
You can also specify a positive integer for better control.
@param style Font style. The following operation flags are available:
- **CV\_STYLE\_NORMAL** Normal font
- **CV\_STYLE\_ITALIC** Italic font
- **CV\_STYLE\_OBLIQUE** Oblique font
@param spacing Spacing between characters. It can be negative or positive.
The function fontQt creates a CvFont object. This CvFont is not compatible with putText .
A basic usage of this function is the following: :
@code
CvFont font = fontQt(''Times'');
addText( img1, ``Hello World !'', Point(50,50), font);
@endcode
*/
CV_EXPORTS QtFont fontQt(const String& nameFont, int pointSize = -1,
Scalar color = Scalar::all(0), int weight = QT_FONT_NORMAL,
int style = QT_STYLE_NORMAL, int spacing = 0);
/** @brief Creates the font to draw a text on an image.
@param img 8-bit 3-channel image where the text should be drawn.
@param text Text to write on an image.
@param org Point(x,y) where the text should start on an image.
@param font Font to use to draw a text.
The function addText draws *text* on an image *img* using a specific font *font* (see example fontQt
)
*/
CV_EXPORTS void addText( const Mat& img, const String& text, Point org, const QtFont& font);
/** @brief Displays a text on a window image as an overlay for a specified duration.
@param winname Name of the window.
@param text Overlay text to write on a window image.
@param delayms The period (in milliseconds), during which the overlay text is displayed. If this
function is called before the previous overlay text timed out, the timer is restarted and the text
is updated. If this value is zero, the text never disappears.
The function displayOverlay displays useful information/tips on top of the window for a certain
amount of time *delayms*. The function does not modify the image, displayed in the window, that is,
after the specified delay the original content of the window is restored.
*/
CV_EXPORTS void displayOverlay(const String& winname, const String& text, int delayms = 0);
/** @brief Displays a text on the window statusbar during the specified period of time.
@param winname Name of the window.
@param text Text to write on the window statusbar.
@param delayms Duration (in milliseconds) to display the text. If this function is called before
the previous text timed out, the timer is restarted and the text is updated. If this value is
zero, the text never disappears.
The function displayOverlay displays useful information/tips on top of the window for a certain
amount of time *delayms* . This information is displayed on the window statusbar (the window must be
created with the CV\_GUI\_EXPANDED flags).
*/
CV_EXPORTS void displayStatusBar(const String& winname, const String& text, int delayms = 0);
/** @brief Saves parameters of the specified window.
@param windowName Name of the window.
The function saveWindowParameters saves size, location, flags, trackbars value, zoom and panning
location of the window window\_name .
*/
CV_EXPORTS void saveWindowParameters(const String& windowName);
/** @brief Loads parameters of the specified window.
@param windowName Name of the window.
The function loadWindowParameters loads size, location, flags, trackbars value, zoom and panning
location of the window window\_name .
*/
CV_EXPORTS void loadWindowParameters(const String& windowName);
CV_EXPORTS int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]);
CV_EXPORTS void stopLoop();
/** @brief Attaches a button to the control panel.
@param bar_name
Name of the button.
@param on_change Pointer to the function to be called every time the button changes its state.
This function should be prototyped as void Foo(int state,\*void); . *state* is the current state
of the button. It could be -1 for a push button, 0 or 1 for a check/radio box button.
@param userdata Pointer passed to the callback function.
@param type Optional type of the button.
- **CV\_PUSH\_BUTTON** Push button
- **CV\_CHECKBOX** Checkbox button
- **CV\_RADIOBOX** Radiobox button. The radiobox on the same buttonbar (same line) are
exclusive, that is only one can be selected at a time.
@param initial_button_state Default state of the button. Use for checkbox and radiobox. Its
value could be 0 or 1. *(Optional)*
The function createButton attaches a button to the control panel. Each button is added to a
buttonbar to the right of the last button. A new buttonbar is created if nothing was attached to the
control panel before, or if the last element attached to the control panel was a trackbar.
See below various examples of the createButton function call: :
@code
createButton(NULL,callbackButton);//create a push button "button 0", that will call callbackButton.
createButton("button2",callbackButton,NULL,CV_CHECKBOX,0);
createButton("button3",callbackButton,&value);
createButton("button5",callbackButton1,NULL,CV_RADIOBOX);
createButton("button6",callbackButton2,NULL,CV_PUSH_BUTTON,1);
@endcode
*/
CV_EXPORTS int createButton( const String& bar_name, ButtonCallback on_change,
void* userdata = 0, int type = QT_PUSH_BUTTON,
bool initial_button_state = false);
//! @} highgui_qt
//! @} highgui
} // cv
#endif

6
modules/highgui/include/opencv2/highgui/highgui_c.h
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@ -51,6 +51,10 @@
extern "C" {
#endif /* __cplusplus */
/** @addtogroup highgui_c
@{
*/
/****************************************************************************************\
* Basic GUI functions *
\****************************************************************************************/
@ -237,6 +241,8 @@ CVAPI(void) cvSetPostprocessFuncWin32_(const void* callback);
#endif
/** @} highgui_c */
#ifdef __cplusplus
}
#endif

158
modules/imgcodecs/include/opencv2/imgcodecs.hpp
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@ -45,10 +45,21 @@
#include "opencv2/core.hpp"
/**
@defgroup imgcodecs Image file reading and writing
@{
@defgroup imgcodecs_c C API
@defgroup imgcodecs_ios iOS glue
@}
*/
//////////////////////////////// image codec ////////////////////////////////
namespace cv
{
//! @addtogroup imgcodecs
//! @{
enum { IMREAD_UNCHANGED = -1, // 8bit, color or not
IMREAD_GRAYSCALE = 0, // 8bit, gray
IMREAD_COLOR = 1, // ?, color
@ -77,19 +88,166 @@ enum { IMWRITE_PNG_STRATEGY_DEFAULT = 0,
IMWRITE_PNG_STRATEGY_FIXED = 4
};
/** @brief Loads an image from a file.
@param filename Name of file to be loaded.
@param flags Flags specifying the color type of a loaded image:
- CV\_LOAD\_IMAGE\_ANYDEPTH - If set, return 16-bit/32-bit image when the input has the
corresponding depth, otherwise convert it to 8-bit.
- CV\_LOAD\_IMAGE\_COLOR - If set, always convert image to the color one
- CV\_LOAD\_IMAGE\_GRAYSCALE - If set, always convert image to the grayscale one
- **\>0** Return a 3-channel color image.
@note In the current implementation the alpha channel, if any, is stripped from the output image.
Use negative value if you need the alpha channel.
- **=0** Return a grayscale image.
- **\<0** Return the loaded image as is (with alpha channel).
The function imread loads an image from the specified file and returns it. If the image cannot be
read (because of missing file, improper permissions, unsupported or invalid format), the function
returns an empty matrix ( Mat::data==NULL ). Currently, the following file formats are supported:
- Windows bitmaps - \*.bmp, \*.dib (always supported)
- JPEG files - \*.jpeg, \*.jpg, \*.jpe (see the *Notes* section)
- JPEG 2000 files - \*.jp2 (see the *Notes* section)
- Portable Network Graphics - \*.png (see the *Notes* section)
- WebP - \*.webp (see the *Notes* section)
- Portable image format - \*.pbm, \*.pgm, \*.ppm (always supported)
- Sun rasters - \*.sr, \*.ras (always supported)
- TIFF files - \*.tiff, \*.tif (see the *Notes* section)
@note
- The function determines the type of an image by the content, not by the file extension.
- On Microsoft Windows\* OS and MacOSX\*, the codecs shipped with an OpenCV image (libjpeg,
libpng, libtiff, and libjasper) are used by default. So, OpenCV can always read JPEGs, PNGs,
and TIFFs. On MacOSX, there is also an option to use native MacOSX image readers. But beware
that currently these native image loaders give images with different pixel values because of
the color management embedded into MacOSX.
- On Linux\*, BSD flavors and other Unix-like open-source operating systems, OpenCV looks for
codecs supplied with an OS image. Install the relevant packages (do not forget the development
files, for example, "libjpeg-dev", in Debian\* and Ubuntu\*) to get the codec support or turn
on the OPENCV\_BUILD\_3RDPARTY\_LIBS flag in CMake.
@note In the case of color images, the decoded images will have the channels stored in B G R order.
*/
CV_EXPORTS_W Mat imread( const String& filename, int flags = IMREAD_COLOR );
/** @brief Saves an image to a specified file.
@param filename Name of the file.
@param img Image to be saved.
@param params Format-specific save parameters encoded as pairs
paramId\_1, paramValue\_1, paramId\_2, paramValue\_2, ... . The following parameters are currently
supported:
- For JPEG, it can be a quality ( CV\_IMWRITE\_JPEG\_QUALITY ) from 0 to 100 (the higher is
the better). Default value is 95.
- For WEBP, it can be a quality ( CV\_IMWRITE\_WEBP\_QUALITY ) from 1 to 100 (the higher is
the better). By default (without any parameter) and for quality above 100 the lossless
compression is used.
- For PNG, it can be the compression level ( CV\_IMWRITE\_PNG\_COMPRESSION ) from 0 to 9. A
higher value means a smaller size and longer compression time. Default value is 3.
- For PPM, PGM, or PBM, it can be a binary format flag ( CV\_IMWRITE\_PXM\_BINARY ), 0 or 1.
Default value is 1.
The function imwrite saves the image to the specified file. The image format is chosen based on the
filename extension (see imread for the list of extensions). Only 8-bit (or 16-bit unsigned (CV\_16U)
in case of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with 'BGR' channel order) images
can be saved using this function. If the format, depth or channel order is different, use
Mat::convertTo , and cvtColor to convert it before saving. Or, use the universal FileStorage I/O
functions to save the image to XML or YAML format.
It is possible to store PNG images with an alpha channel using this function. To do this, create
8-bit (or 16-bit) 4-channel image BGRA, where the alpha channel goes last. Fully transparent pixels
should have alpha set to 0, fully opaque pixels should have alpha set to 255/65535. The sample below
shows how to create such a BGRA image and store to PNG file. It also demonstrates how to set custom
compression parameters :
@code
#include <vector>
#include <stdio.h>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
void createAlphaMat(Mat &mat)
{
for (int i = 0; i < mat.rows; ++i) {
for (int j = 0; j < mat.cols; ++j) {
Vec4b& rgba = mat.at<Vec4b>(i, j);
rgba[0] = UCHAR_MAX;
rgba[1] = saturate_cast<uchar>((float (mat.cols - j)) / ((float)mat.cols) * UCHAR_MAX);
rgba[2] = saturate_cast<uchar>((float (mat.rows - i)) / ((float)mat.rows) * UCHAR_MAX);
rgba[3] = saturate_cast<uchar>(0.5 * (rgba[1] + rgba[2]));
}
}
}
int main(int argv, char **argc)
{
// Create mat with alpha channel
Mat mat(480, 640, CV_8UC4);
createAlphaMat(mat);
vector<int> compression_params;
compression_params.push_back(CV_IMWRITE_PNG_COMPRESSION);
compression_params.push_back(9);
try {
imwrite("alpha.png", mat, compression_params);
}
catch (runtime_error& ex) {
fprintf(stderr, "Exception converting image to PNG format: %s\n", ex.what());
return 1;
}
fprintf(stdout, "Saved PNG file with alpha data.\n");
return 0;
}
@endcode
*/
CV_EXPORTS_W bool imwrite( const String& filename, InputArray img,
const std::vector<int>& params = std::vector<int>());
/** @overload */
CV_EXPORTS_W Mat imdecode( InputArray buf, int flags );
/** @brief Reads an image from a buffer in memory.
@param buf Input array or vector of bytes.
@param flags The same flags as in imread .
@param dst The optional output placeholder for the decoded matrix. It can save the image
reallocations when the function is called repeatedly for images of the same size.
The function reads an image from the specified buffer in the memory. If the buffer is too short or
contains invalid data, the empty matrix/image is returned.
See imread for the list of supported formats and flags description.
@note In the case of color images, the decoded images will have the channels stored in B G R order.
*/
CV_EXPORTS Mat imdecode( InputArray buf, int flags, Mat* dst);
/** @brief Encodes an image into a memory buffer.
@param ext File extension that defines the output format.
@param img Image to be written.
@param buf Output buffer resized to fit the compressed image.
@param params Format-specific parameters. See imwrite .
The function compresses the image and stores it in the memory buffer that is resized to fit the
result. See imwrite for the list of supported formats and flags description.
@note cvEncodeImage returns single-row matrix of type CV\_8UC1 that contains encoded image as array
of bytes.
*/
CV_EXPORTS_W bool imencode( const String& ext, InputArray img,
CV_OUT std::vector<uchar>& buf,
const std::vector<int>& params = std::vector<int>());
//! @} imgcodecs
} // cv
#endif //__OPENCV_IMGCODECS_HPP__

5
modules/imgcodecs/include/opencv2/imgcodecs/imgcodecs_c.h
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@ -48,6 +48,10 @@
extern "C" {
#endif /* __cplusplus */
/** @addtogroup imgcodecs_c
@{
*/
enum
{
/* 8bit, color or not */
@ -124,6 +128,7 @@ CVAPI(int) cvHaveImageWriter(const char* filename);
#define cvvSaveImage cvSaveImage
#define cvvConvertImage cvConvertImage
/** @} imgcodecs_c */
#ifdef __cplusplus
}

5
modules/imgcodecs/include/opencv2/imgcodecs/ios.h
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@ -47,6 +47,11 @@
#import <ImageIO/ImageIO.h>
#include "opencv2/core/core.hpp"
//! @addtogroup imgcodecs_ios
//! @{
UIImage* MatToUIImage(const cv::Mat& image);
void UIImageToMat(const UIImage* image,
cv::Mat& m, bool alphaExist = false);
//! @}

9
modules/video/include/opencv2/video.hpp
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@ -44,6 +44,15 @@
#ifndef __OPENCV_VIDEO_HPP__
#define __OPENCV_VIDEO_HPP__
/**
@defgroup video Video Analysis
@{
@defgroup video_motion Motion Analysis
@defgroup video_track Object Tracking
@defgroup video_c C API
@}
*/
#include "opencv2/video/tracking.hpp"
#include "opencv2/video/background_segm.hpp"

189
modules/video/include/opencv2/video/background_segm.hpp
View File

@ -49,49 +49,102 @@
namespace cv
{
/*!
The Base Class for Background/Foreground Segmentation
//! @addtogroup video_motion
//! @{
The class is only used to define the common interface for
the whole family of background/foreground segmentation algorithms.
*/
/** @brief Base class for background/foreground segmentation. :
The class is only used to define the common interface for the whole family of background/foreground
segmentation algorithms.
*/
class CV_EXPORTS_W BackgroundSubtractor : public Algorithm
{
public:
//! the update operator that takes the next video frame and returns the current foreground mask as 8-bit binary image.
/** @brief Computes a foreground mask.
@param image Next video frame.
@param fgmask The output foreground mask as an 8-bit binary image.
@param learningRate The value between 0 and 1 that indicates how fast the background model is
learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
rate. 0 means that the background model is not updated at all, 1 means that the background model
is completely reinitialized from the last frame.
*/
CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) = 0;
//! computes a background image
/** @brief Computes a background image.
@param backgroundImage The output background image.
@note Sometimes the background image can be very blurry, as it contain the average background
statistics.
*/
CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const = 0;
};
/*!
The class implements the following algorithm:
"Improved adaptive Gausian mixture model for background subtraction"
Z.Zivkovic
International Conference Pattern Recognition, UK, August, 2004.
http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf
/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
The class implements the Gaussian mixture model background subtraction described in @cite Zivkovic2004
and @cite Zivkovic2006 .
*/
class CV_EXPORTS_W BackgroundSubtractorMOG2 : public BackgroundSubtractor
{
public:
/** @brief Returns the number of last frames that affect the background model
*/
CV_WRAP virtual int getHistory() const = 0;
/** @brief Sets the number of last frames that affect the background model
*/
CV_WRAP virtual void setHistory(int history) = 0;
/** @brief Returns the number of gaussian components in the background model
*/
CV_WRAP virtual int getNMixtures() const = 0;
/** @brief Sets the number of gaussian components in the background model.
The model needs to be reinitalized to reserve memory.
*/
CV_WRAP virtual void setNMixtures(int nmixtures) = 0;//needs reinitialization!
/** @brief Returns the "background ratio" parameter of the algorithm
If a foreground pixel keeps semi-constant value for about backgroundRatio\*history frames, it's
considered background and added to the model as a center of a new component. It corresponds to TB
parameter in the paper.
*/
CV_WRAP virtual double getBackgroundRatio() const = 0;
/** @brief Sets the "background ratio" parameter of the algorithm
*/
CV_WRAP virtual void setBackgroundRatio(double ratio) = 0;
/** @brief Returns the variance threshold for the pixel-model match
The main threshold on the squared Mahalanobis distance to decide if the sample is well described by
the background model or not. Related to Cthr from the paper.
*/
CV_WRAP virtual double getVarThreshold() const = 0;
/** @brief Sets the variance threshold for the pixel-model match
*/
CV_WRAP virtual void setVarThreshold(double varThreshold) = 0;
/** @brief Returns the variance threshold for the pixel-model match used for new mixture component generation
Threshold for the squared Mahalanobis distance that helps decide when a sample is close to the
existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it
is considered foreground or added as a new component. 3 sigma =\> Tg=3\*3=9 is default. A smaller Tg
value generates more components. A higher Tg value may result in a small number of components but
they can grow too large.
*/
CV_WRAP virtual double getVarThresholdGen() const = 0;
/** @brief Sets the variance threshold for the pixel-model match used for new mixture component generation
*/
CV_WRAP virtual void setVarThresholdGen(double varThresholdGen) = 0;
/** @brief Returns the initial variance of each gaussian component
*/
CV_WRAP virtual double getVarInit() const = 0;
/** @brief Sets the initial variance of each gaussian component
*/
CV_WRAP virtual void setVarInit(double varInit) = 0;
CV_WRAP virtual double getVarMin() const = 0;
@ -100,62 +153,154 @@ public:
CV_WRAP virtual double getVarMax() const = 0;
CV_WRAP virtual void setVarMax(double varMax) = 0;
/** @brief Returns the complexity reduction threshold
This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05
is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the
standard Stauffer&Grimson algorithm.
*/
CV_WRAP virtual double getComplexityReductionThreshold() const = 0;
/** @brief Sets the complexity reduction threshold
*/
CV_WRAP virtual void setComplexityReductionThreshold(double ct) = 0;
/** @brief Returns the shadow detection flag
If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for
details.
*/
CV_WRAP virtual bool getDetectShadows() const = 0;
/** @brief Enables or disables shadow detection
*/
CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
/** @brief Returns the shadow value
Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
in the mask always means background, 255 means foreground.
*/
CV_WRAP virtual int getShadowValue() const = 0;
/** @brief Sets the shadow value
*/
CV_WRAP virtual void setShadowValue(int value) = 0;
/** @brief Returns the shadow threshold
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
*Detecting Moving Shadows...*, IEEE PAMI,2003.
*/
CV_WRAP virtual double getShadowThreshold() const = 0;
/** @brief Sets the shadow threshold
*/
CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
};
/** @brief Creates MOG2 Background Subtractor
@param history Length of the history.
@param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model
to decide whether a pixel is well described by the background model. This parameter does not
affect the background update.
@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the
speed a bit, so if you do not need this feature, set the parameter to false.
*/
CV_EXPORTS_W Ptr<BackgroundSubtractorMOG2>
createBackgroundSubtractorMOG2(int history=500, double varThreshold=16,
bool detectShadows=true);
/*!
The class implements the K nearest neigbours algorithm from:
"Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction"
Z.Zivkovic, F. van der Heijden
Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006
http://www.zoranz.net/Publications/zivkovicPRL2006.pdf
Fast for small foreground object. Results on the benchmark data is at http://www.changedetection.net.
*/
/** @brief K-nearest neigbours - based Background/Foreground Segmentation Algorithm.
The class implements the K-nearest neigbours background subtraction described in @cite Zivkovic2006 .
Very efficient if number of foreground pixels is low.
*/
class CV_EXPORTS_W BackgroundSubtractorKNN : public BackgroundSubtractor
{
public:
/** @brief Returns the number of last frames that affect the background model
*/
CV_WRAP virtual int getHistory() const = 0;
/** @brief Sets the number of last frames that affect the background model
*/
CV_WRAP virtual void setHistory(int history) = 0;
/** @brief Returns the number of data samples in the background model
*/
CV_WRAP virtual int getNSamples() const = 0;
/** @brief Sets the number of data samples in the background model.
The model needs to be reinitalized to reserve memory.
*/
CV_WRAP virtual void setNSamples(int _nN) = 0;//needs reinitialization!
/** @brief Returns the threshold on the squared distance between the pixel and the sample
The threshold on the squared distance between the pixel and the sample to decide whether a pixel is
close to a data sample.
*/
CV_WRAP virtual double getDist2Threshold() const = 0;
/** @brief Sets the threshold on the squared distance
*/
CV_WRAP virtual void setDist2Threshold(double _dist2Threshold) = 0;
/** @brief Returns the number of neighbours, the k in the kNN.
K is the number of samples that need to be within dist2Threshold in order to decide that that
pixel is matching the kNN background model.
*/
CV_WRAP virtual int getkNNSamples() const = 0;
/** @brief Sets the k in the kNN. How many nearest neigbours need to match.
*/
CV_WRAP virtual void setkNNSamples(int _nkNN) = 0;
/** @brief Returns the shadow detection flag
If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for
details.
*/
CV_WRAP virtual bool getDetectShadows() const = 0;
/** @brief Enables or disables shadow detection
*/
CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
/** @brief Returns the shadow value
Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
in the mask always means background, 255 means foreground.
*/
CV_WRAP virtual int getShadowValue() const = 0;
/** @brief Sets the shadow value
*/
CV_WRAP virtual void setShadowValue(int value) = 0;
/** @brief Returns the shadow threshold
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
*Detecting Moving Shadows...*, IEEE PAMI,2003.
*/
CV_WRAP virtual double getShadowThreshold() const = 0;
/** @brief Sets the shadow threshold
*/
CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
};
/** @brief Creates KNN Background Subtractor
@param history Length of the history.
@param dist2Threshold Threshold on the squared distance between the pixel and the sample to decide
whether a pixel is close to that sample. This parameter does not affect the background update.
@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the
speed a bit, so if you do not need this feature, set the parameter to false.
*/
CV_EXPORTS_W Ptr<BackgroundSubtractorKNN>
createBackgroundSubtractorKNN(int history=500, double dist2Threshold=400.0,
bool detectShadows=true);
//! @} video_motion
} // cv
#endif

339
modules/video/include/opencv2/video/tracking.hpp
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@ -50,26 +50,126 @@
namespace cv
{
//! @addtogroup video_track
//! @{
enum { OPTFLOW_USE_INITIAL_FLOW = 4,
OPTFLOW_LK_GET_MIN_EIGENVALS = 8,
OPTFLOW_FARNEBACK_GAUSSIAN = 256
};
//! updates the object tracking window using CAMSHIFT algorithm
/** @brief Finds an object center, size, and orientation.
@param probImage Back projection of the object histogram. See calcBackProject.
@param window Initial search window.
@param criteria Stop criteria for the underlying meanShift.
returns
(in old interfaces) Number of iterations CAMSHIFT took to converge
The function implements the CAMSHIFT object tracking algorithm @cite Bradski98. First, it finds an
object center using meanShift and then adjusts the window size and finds the optimal rotation. The
function returns the rotated rectangle structure that includes the object position, size, and
orientation. The next position of the search window can be obtained with RotatedRect::boundingRect()
See the OpenCV sample camshiftdemo.c that tracks colored objects.
@note
- (Python) A sample explaining the camshift tracking algorithm can be found at
opencv\_source\_code/samples/python2/camshift.py
*/
CV_EXPORTS_W RotatedRect CamShift( InputArray probImage, CV_IN_OUT Rect& window,
TermCriteria criteria );
//! updates the object tracking window using meanshift algorithm
/** @brief Finds an object on a back projection image.
@param probImage Back projection of the object histogram. See calcBackProject for details.
@param window Initial search window.
@param criteria Stop criteria for the iterative search algorithm.
returns
: Number of iterations CAMSHIFT took to converge.
The function implements the iterative object search algorithm. It takes the input back projection of
an object and the initial position. The mass center in window of the back projection image is
computed and the search window center shifts to the mass center. The procedure is repeated until the
specified number of iterations criteria.maxCount is done or until the window center shifts by less
than criteria.epsilon. The algorithm is used inside CamShift and, unlike CamShift , the search
window size or orientation do not change during the search. You can simply pass the output of
calcBackProject to this function. But better results can be obtained if you pre-filter the back
projection and remove the noise. For example, you can do this by retrieving connected components
with findContours , throwing away contours with small area ( contourArea ), and rendering the
remaining contours with drawContours.
@note
- A mean-shift tracking sample can be found at opencv\_source\_code/samples/cpp/camshiftdemo.cpp
*/
CV_EXPORTS_W int meanShift( InputArray probImage, CV_IN_OUT Rect& window, TermCriteria criteria );
//! constructs a pyramid which can be used as input for calcOpticalFlowPyrLK
/** @brief Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
@param img 8-bit input image.
@param pyramid output pyramid.
@param winSize window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.
@param maxLevel 0-based maximal pyramid level number.
@param withDerivatives set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.
@param pyrBorder the border mode for pyramid layers.
@param derivBorder the border mode for gradients.
@param tryReuseInputImage put ROI of input image into the pyramid if possible. You can pass false
to force data copying.
@return number of levels in constructed pyramid. Can be less than maxLevel.
*/
CV_EXPORTS_W int buildOpticalFlowPyramid( InputArray img, OutputArrayOfArrays pyramid,
Size winSize, int maxLevel, bool withDerivatives = true,
int pyrBorder = BORDER_REFLECT_101,
int derivBorder = BORDER_CONSTANT,
bool tryReuseInputImage = true );
//! computes sparse optical flow using multi-scale Lucas-Kanade algorithm
/** @brief Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
@param prevImg first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.
@param nextImg second input image or pyramid of the same size and the same type as prevImg.
@param prevPts vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.
@param nextPts output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW\_USE\_INITIAL\_FLOW flag is passed, the vector must have the same size as in the input.
@param status output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.
@param err output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).
@param winSize size of the search window at each pyramid level.
@param maxLevel 0-based maximal pyramid level number; if set to 0, pyramids are not used (single
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.
@param criteria parameter, specifying the termination criteria of the iterative search algorithm
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.
@param flags operation flags:
- **OPTFLOW\_USE\_INITIAL\_FLOW** uses initial estimations, stored in nextPts; if the flag is
not set, then prevPts is copied to nextPts and is considered the initial estimate.
- **OPTFLOW\_LK\_GET\_MIN\_EIGENVALS** use minimum eigen values as an error measure (see
minEigThreshold description); if the flag is not set, then L1 distance between patches
around the original and a moved point, divided by number of pixels in a window, is used as a
error measure.
@param minEigThreshold the algorithm calculates the minimum eigen value of a 2x2 normal matrix of
optical flow equations (this matrix is called a spatial gradient matrix in @cite Bouguet00), divided
by number of pixels in a window; if this value is less than minEigThreshold, then a corresponding
feature is filtered out and its flow is not processed, so it allows to remove bad points and get a
performance boost.
The function implements a sparse iterative version of the Lucas-Kanade optical flow in pyramids. See
@cite Bouguet00. The function is parallelized with the TBB library.
@note
- An example using the Lucas-Kanade optical flow algorithm can be found at
opencv\_source\_code/samples/cpp/lkdemo.cpp
- (Python) An example using the Lucas-Kanade optical flow algorithm can be found at
opencv\_source\_code/samples/python2/lk\_track.py
- (Python) An example using the Lucas-Kanade tracker for homography matching can be found at
opencv\_source\_code/samples/python2/lk\_homography.py
*/
CV_EXPORTS_W void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg,
InputArray prevPts, InputOutputArray nextPts,
OutputArray status, OutputArray err,
@ -77,14 +177,76 @@ CV_EXPORTS_W void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01),
int flags = 0, double minEigThreshold = 1e-4 );
//! computes dense optical flow using Farneback algorithm
/** @brief Computes a dense optical flow using the Gunnar Farneback's algorithm.
@param prev first 8-bit single-channel input image.
@param next second input image of the same size and the same type as prev.
@param flow computed flow image that has the same size as prev and type CV\_32FC2.
@param pyr\_scale parameter, specifying the image scale (\<1) to build pyramids for each image;
pyr\_scale=0.5 means a classical pyramid, where each next layer is twice smaller than the previous
one.
@param levels number of pyramid layers including the initial image; levels=1 means that no extra
layers are created and only the original images are used.
@param winsize averaging window size; larger values increase the algorithm robustness to image
noise and give more chances for fast motion detection, but yield more blurred motion field.
@param iterations number of iterations the algorithm does at each pyramid level.
@param poly\_n size of the pixel neighborhood used to find polynomial expansion in each pixel;
larger values mean that the image will be approximated with smoother surfaces, yielding more
robust algorithm and more blurred motion field, typically poly\_n =5 or 7.
@param poly\_sigma standard deviation of the Gaussian that is used to smooth derivatives used as a
basis for the polynomial expansion; for poly\_n=5, you can set poly\_sigma=1.1, for poly\_n=7, a
good value would be poly\_sigma=1.5.
@param flags operation flags that can be a combination of the following:
- **OPTFLOW\_USE\_INITIAL\_FLOW** uses the input flow as an initial flow approximation.
- **OPTFLOW\_FARNEBACK\_GAUSSIAN** uses the Gaussian \f$\texttt{winsize}\times\texttt{winsize}\f$
filter instead of a box filter of the same size for optical flow estimation; usually, this
option gives z more accurate flow than with a box filter, at the cost of lower speed;
normally, winsize for a Gaussian window should be set to a larger value to achieve the same
level of robustness.
The function finds an optical flow for each prev pixel using the @cite Farneback2003 algorithm so that
\f[\texttt{prev} (y,x) \sim \texttt{next} ( y + \texttt{flow} (y,x)[1], x + \texttt{flow} (y,x)[0])\f]
@note
- An example using the optical flow algorithm described by Gunnar Farneback can be found at
opencv\_source\_code/samples/cpp/fback.cpp
- (Python) An example using the optical flow algorithm described by Gunnar Farneback can be
found at opencv\_source\_code/samples/python2/opt\_flow.py
*/
CV_EXPORTS_W void calcOpticalFlowFarneback( InputArray prev, InputArray next, InputOutputArray flow,
double pyr_scale, int levels, int winsize,
int iterations, int poly_n, double poly_sigma,
int flags );
//! estimates the best-fit Euqcidean, similarity, affine or perspective transformation
// that maps one 2D point set to another or one image to another.
/** @brief Computes an optimal affine transformation between two 2D point sets.
@param src First input 2D point set stored in std::vector or Mat, or an image stored in Mat.
@param dst Second input 2D point set of the same size and the same type as A, or another image.
@param fullAffine If true, the function finds an optimal affine transformation with no additional
restrictions (6 degrees of freedom). Otherwise, the class of transformations to choose from is
limited to combinations of translation, rotation, and uniform scaling (5 degrees of freedom).
The function finds an optimal affine transform *[A|b]* (a 2 x 3 floating-point matrix) that
approximates best the affine transformation between:
* Two point sets
* Two raster images. In this case, the function first finds some features in the src image and
finds the corresponding features in dst image. After that, the problem is reduced to the first
case.
In case of point sets, the problem is formulated as follows: you need to find a 2x2 matrix *A* and
2x1 vector *b* so that:
\f[[A^*|b^*] = arg \min _{[A|b]} \sum _i \| \texttt{dst}[i] - A { \texttt{src}[i]}^T - b \| ^2\f]
where src[i] and dst[i] are the i-th points in src and dst, respectively
\f$[A|b]\f$ can be either arbitrary (when fullAffine=true ) or have a form of
\f[\begin{bmatrix} a_{11} & a_{12} & b_1 \\ -a_{12} & a_{11} & b_2 \end{bmatrix}\f]
when fullAffine=false.
@sa
getAffineTransform, getPerspectiveTransform, findHomography
*/
CV_EXPORTS_W Mat estimateRigidTransform( InputArray src, InputArray dst, bool fullAffine );
@ -96,37 +258,106 @@ enum
MOTION_HOMOGRAPHY = 3
};
//! estimates the best-fit Translation, Euclidean, Affine or Perspective Transformation
// with respect to Enhanced Correlation Coefficient criterion that maps one image to
// another (area-based alignment)
//
// see reference:
// Evangelidis, G. E., Psarakis, E.Z., Parametric Image Alignment using
// Enhanced Correlation Coefficient Maximization, PAMI, 30(8), 2008
/** @brief Finds the geometric transform (warp) between two images in terms of the ECC criterion @cite EP08.
@param templateImage single-channel template image; CV\_8U or CV\_32F array.
@param inputImage single-channel input image which should be warped with the final warpMatrix in
order to provide an image similar to templateImage, same type as temlateImage.
@param warpMatrix floating-point \f$2\times 3\f$ or \f$3\times 3\f$ mapping matrix (warp).
@param motionType parameter, specifying the type of motion:
- **MOTION\_TRANSLATION** sets a translational motion model; warpMatrix is \f$2\times 3\f$ with
the first \f$2\times 2\f$ part being the unity matrix and the rest two parameters being
estimated.
- **MOTION\_EUCLIDEAN** sets a Euclidean (rigid) transformation as motion model; three
parameters are estimated; warpMatrix is \f$2\times 3\f$.
- **MOTION\_AFFINE** sets an affine motion model (DEFAULT); six parameters are estimated;
warpMatrix is \f$2\times 3\f$.
- **MOTION\_HOMOGRAPHY** sets a homography as a motion model; eight parameters are
estimated;\`warpMatrix\` is \f$3\times 3\f$.
@param criteria parameter, specifying the termination criteria of the ECC algorithm;
criteria.epsilon defines the threshold of the increment in the correlation coefficient between two
iterations (a negative criteria.epsilon makes criteria.maxcount the only termination criterion).
Default values are shown in the declaration above.
The function estimates the optimum transformation (warpMatrix) with respect to ECC criterion
(@cite EP08), that is
\f[\texttt{warpMatrix} = \texttt{warpMatrix} = \arg\max_{W} \texttt{ECC}(\texttt{templateImage}(x,y),\texttt{inputImage}(x',y'))\f]
where
\f[\begin{bmatrix} x' \\ y' \end{bmatrix} = W \cdot \begin{bmatrix} x \\ y \\ 1 \end{bmatrix}\f]
(the equation holds with homogeneous coordinates for homography). It returns the final enhanced
correlation coefficient, that is the correlation coefficient between the template image and the
final warped input image. When a \f$3\times 3\f$ matrix is given with motionType =0, 1 or 2, the third
row is ignored.
Unlike findHomography and estimateRigidTransform, the function findTransformECC implements an
area-based alignment that builds on intensity similarities. In essence, the function updates the
initial transformation that roughly aligns the images. If this information is missing, the identity
warp (unity matrix) should be given as input. Note that if images undergo strong
displacements/rotations, an initial transformation that roughly aligns the images is necessary
(e.g., a simple euclidean/similarity transform that allows for the images showing the same image
content approximately). Use inverse warping in the second image to take an image close to the first
one, i.e. use the flag WARP\_INVERSE\_MAP with warpAffine or warpPerspective. See also the OpenCV
sample image\_alignment.cpp that demonstrates the use of the function. Note that the function throws
an exception if algorithm does not converges.
@sa
estimateRigidTransform, findHomography
*/
CV_EXPORTS_W double findTransformECC( InputArray templateImage, InputArray inputImage,
InputOutputArray warpMatrix, int motionType = MOTION_AFFINE,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001));
/*!
Kalman filter.
/** @brief Kalman filter class.
The class implements standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter.
However, you can modify KalmanFilter::transitionMatrix, KalmanFilter::controlMatrix and
KalmanFilter::measurementMatrix to get the extended Kalman filter functionality.
*/
The class implements a standard Kalman filter <http://en.wikipedia.org/wiki/Kalman_filter>,
@cite Welch95. However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get
an extended Kalman filter functionality. See the OpenCV sample kalman.cpp.
@note
- An example using the standard Kalman filter can be found at
opencv\_source\_code/samples/cpp/kalman.cpp
*/
class CV_EXPORTS_W KalmanFilter
{
public:
//! the default constructor
/** @brief The constructors.
@note In C API when CvKalman\* kalmanFilter structure is not needed anymore, it should be released
with cvReleaseKalman(&kalmanFilter)
*/
CV_WRAP KalmanFilter();
//! the full constructor taking the dimensionality of the state, of the measurement and of the control vector
/** @overload
@param dynamParams Dimensionality of the state.
@param measureParams Dimensionality of the measurement.
@param controlParams Dimensionality of the control vector.
@param type Type of the created matrices that should be CV\_32F or CV\_64F.
*/
CV_WRAP KalmanFilter( int dynamParams, int measureParams, int controlParams = 0, int type = CV_32F );
//! re-initializes Kalman filter. The previous content is destroyed.
/** @brief Re-initializes Kalman filter. The previous content is destroyed.
@param dynamParams Dimensionalityensionality of the state.
@param measureParams Dimensionality of the measurement.
@param controlParams Dimensionality of the control vector.
@param type Type of the created matrices that should be CV\_32F or CV\_64F.
*/
void init( int dynamParams, int measureParams, int controlParams = 0, int type = CV_32F );
//! computes predicted state
/** @brief Computes a predicted state.
@param control The optional input control
*/
CV_WRAP const Mat& predict( const Mat& control = Mat() );
//! updates the predicted state from the measurement
/** @brief Updates the predicted state from the measurement.
@param measurement The measured system parameters
*/
CV_WRAP const Mat& correct( const Mat& measurement );
CV_PROP_RW Mat statePre; //!< predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k)
@ -149,21 +380,69 @@ public:
};
/** @brief "Dual TV L1" Optical Flow Algorithm.
The class implements the "Dual TV L1" optical flow algorithm described in @cite Zach2007 and
@cite Javier2012.
Here are important members of the class that control the algorithm, which you can set after
constructing the class instance:
- member double tau
Time step of the numerical scheme.
- member double lambda
Weight parameter for the data term, attachment parameter. This is the most relevant
parameter, which determines the smoothness of the output. The smaller this parameter is,
the smoother the solutions we obtain. It depends on the range of motions of the images, so
its value should be adapted to each image sequence.
- member double theta
Weight parameter for (u - v)\^2, tightness parameter. It serves as a link between the
attachment and the regularization terms. In theory, it should have a small value in order
to maintain both parts in correspondence. The method is stable for a large range of values
of this parameter.
- member int nscales
Number of scales used to create the pyramid of images.
- member int warps
Number of warpings per scale. Represents the number of times that I1(x+u0) and grad(
I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the
method. It also affects the running time, so it is a compromise between speed and
accuracy.
- member double epsilon
Stopping criterion threshold used in the numerical scheme, which is a trade-off between
precision and running time. A small value will yield more accurate solutions at the
expense of a slower convergence.
- member int iterations
Stopping criterion iterations number used in the numerical scheme.
C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
*/
class CV_EXPORTS_W DenseOpticalFlow : public Algorithm
{
public:
/** @brief Calculates an optical flow.
@param I0 first 8-bit single-channel input image.
@param I1 second input image of the same size and the same type as prev.
@param flow computed flow image that has the same size as prev and type CV\_32FC2.
*/
CV_WRAP virtual void calc( InputArray I0, InputArray I1, InputOutputArray flow ) = 0;
/** @brief Releases all inner buffers.
*/
CV_WRAP virtual void collectGarbage() = 0;
};
// Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method
//
// see reference:
// [1] C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
// [2] Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
/** @brief Creates instance of cv::DenseOpticalFlow
*/
CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_DualTVL1();
//! @} video_track
} // cv
#endif

5
modules/video/include/opencv2/video/tracking_c.h
View File

@ -50,6 +50,10 @@
extern "C" {
#endif
/** @addtogroup video_c
@{
*/
/****************************************************************************************\
* Motion Analysis *
\****************************************************************************************/
@ -218,6 +222,7 @@ CVAPI(const CvMat*) cvKalmanCorrect( CvKalman* kalman, const CvMat* measurement
#define cvKalmanUpdateByTime cvKalmanPredict
#define cvKalmanUpdateByMeasurement cvKalmanCorrect
/** @} video_c */
#ifdef __cplusplus
} // extern "C"

237
modules/videoio/include/opencv2/videoio.hpp
View File

@ -45,6 +45,13 @@
#include "opencv2/core.hpp"
/**
@defgroup videoio Media I/O
@{
@defgroup videoio_c C API
@defgroup videoio_ios iOS glue
@}
*/
////////////////////////////////// video io /////////////////////////////////
@ -54,6 +61,9 @@ typedef struct CvVideoWriter CvVideoWriter;
namespace cv
{
//! @addtogroup videoio
//! @{
// Camera API
enum { CAP_ANY = 0, // autodetect
CAP_VFW = 200, // platform native
@ -345,26 +355,209 @@ enum { CAP_INTELPERC_DEPTH_MAP = 0, // Each pixel is a 16-bit integ
class IVideoCapture;
/** @brief Class for video capturing from video files, image sequences or cameras. The class provides C++ API
for capturing video from cameras or for reading video files and image sequences. Here is how the
class can be used: :
@code
#include "opencv2/opencv.hpp"
using namespace cv;
int main(int, char**)
{
VideoCapture cap(0); // open the default camera
if(!cap.isOpened()) // check if we succeeded
return -1;
Mat edges;
namedWindow("edges",1);
for(;;)
{
Mat frame;
cap >> frame; // get a new frame from camera
cvtColor(frame, edges, COLOR_BGR2GRAY);
GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
Canny(edges, edges, 0, 30, 3);
imshow("edges", edges);
if(waitKey(30) >= 0) break;
}
// the camera will be deinitialized automatically in VideoCapture destructor
return 0;
}
@endcode
@note In C API the black-box structure CvCapture is used instead of VideoCapture.
@note
- A basic sample on using the VideoCapture interface can be found at
opencv\_source\_code/samples/cpp/starter\_video.cpp
- Another basic video processing sample can be found at
opencv\_source\_code/samples/cpp/video\_dmtx.cpp
- (Python) A basic sample on using the VideoCapture interface can be found at
opencv\_source\_code/samples/python2/video.py
- (Python) Another basic video processing sample can be found at
opencv\_source\_code/samples/python2/video\_dmtx.py
- (Python) A multi threaded video processing sample can be found at
opencv\_source\_code/samples/python2/video\_threaded.py
*/
class CV_EXPORTS_W VideoCapture
{
public:
/** @brief
@note In C API, when you finished working with video, release CvCapture structure with
cvReleaseCapture(), or use Ptr\<CvCapture\> that calls cvReleaseCapture() automatically in the
destructor.
*/
CV_WRAP VideoCapture();
/** @overload
@param filename name of the opened video file (eg. video.avi) or image sequence (eg.
img\_%02d.jpg, which will read samples like img\_00.jpg, img\_01.jpg, img\_02.jpg, ...)
*/
CV_WRAP VideoCapture(const String& filename);
/** @overload
@param device id of the opened video capturing device (i.e. a camera index). If there is a single
camera connected, just pass 0.
*/
CV_WRAP VideoCapture(int device);
virtual ~VideoCapture();
/** @brief Open video file or a capturing device for video capturing
@param filename name of the opened video file (eg. video.avi) or image sequence (eg.
img\_%02d.jpg, which will read samples like img\_00.jpg, img\_01.jpg, img\_02.jpg, ...)
The methods first call VideoCapture::release to close the already opened file or camera.
*/
CV_WRAP virtual bool open(const String& filename);
/** @overload
@param device id of the opened video capturing device (i.e. a camera index).
*/
CV_WRAP virtual bool open(int device);
/** @brief Returns true if video capturing has been initialized already.
If the previous call to VideoCapture constructor or VideoCapture::open succeeded, the method returns
true.
*/
CV_WRAP virtual bool isOpened() const;
/** @brief Closes video file or capturing device.
The methods are automatically called by subsequent VideoCapture::open and by VideoCapture
destructor.
The C function also deallocates memory and clears \*capture pointer.
*/
CV_WRAP virtual void release();
/** @brief Grabs the next frame from video file or capturing device.
The methods/functions grab the next frame from video file or camera and return true (non-zero) in
the case of success.
The primary use of the function is in multi-camera environments, especially when the cameras do not
have hardware synchronization. That is, you call VideoCapture::grab() for each camera and after that
call the slower method VideoCapture::retrieve() to decode and get frame from each camera. This way
the overhead on demosaicing or motion jpeg decompression etc. is eliminated and the retrieved frames
from different cameras will be closer in time.
Also, when a connected camera is multi-head (for example, a stereo camera or a Kinect device), the
correct way of retrieving data from it is to call VideoCapture::grab first and then call
VideoCapture::retrieve one or more times with different values of the channel parameter. See
<https://github.com/Itseez/opencv/tree/master/samples/cpp/openni_capture.cpp>
*/
CV_WRAP virtual bool grab();
/** @brief Decodes and returns the grabbed video frame.
The methods/functions decode and return the just grabbed frame. If no frames has been grabbed
(camera has been disconnected, or there are no more frames in video file), the methods return false
and the functions return NULL pointer.
@note OpenCV 1.x functions cvRetrieveFrame and cv.RetrieveFrame return image stored inside the video
capturing structure. It is not allowed to modify or release the image! You can copy the frame using
:ocvcvCloneImage and then do whatever you want with the copy.
*/
CV_WRAP virtual bool retrieve(OutputArray image, int flag = 0);
virtual VideoCapture& operator >> (CV_OUT Mat& image);
virtual VideoCapture& operator >> (CV_OUT UMat& image);
/** @brief Grabs, decodes and returns the next video frame.
The methods/functions combine VideoCapture::grab and VideoCapture::retrieve in one call. This is the
most convenient method for reading video files or capturing data from decode and return the just
grabbed frame. If no frames has been grabbed (camera has been disconnected, or there are no more
frames in video file), the methods return false and the functions return NULL pointer.
@note OpenCV 1.x functions cvRetrieveFrame and cv.RetrieveFrame return image stored inside the video
capturing structure. It is not allowed to modify or release the image! You can copy the frame using
:ocvcvCloneImage and then do whatever you want with the copy.
*/
CV_WRAP virtual bool read(OutputArray image);
/** @brief Sets a property in the VideoCapture.
@param propId Property identifier. It can be one of the following:
- **CV\_CAP\_PROP\_POS\_MSEC** Current position of the video file in milliseconds.
- **CV\_CAP\_PROP\_POS\_FRAMES** 0-based index of the frame to be decoded/captured next.
- **CV\_CAP\_PROP\_POS\_AVI\_RATIO** Relative position of the video file: 0 - start of the
film, 1 - end of the film.
- **CV\_CAP\_PROP\_FRAME\_WIDTH** Width of the frames in the video stream.
- **CV\_CAP\_PROP\_FRAME\_HEIGHT** Height of the frames in the video stream.
- **CV\_CAP\_PROP\_FPS** Frame rate.
- **CV\_CAP\_PROP\_FOURCC** 4-character code of codec.
- **CV\_CAP\_PROP\_FRAME\_COUNT** Number of frames in the video file.
- **CV\_CAP\_PROP\_FORMAT** Format of the Mat objects returned by retrieve() .
- **CV\_CAP\_PROP\_MODE** Backend-specific value indicating the current capture mode.
- **CV\_CAP\_PROP\_BRIGHTNESS** Brightness of the image (only for cameras).
- **CV\_CAP\_PROP\_CONTRAST** Contrast of the image (only for cameras).
- **CV\_CAP\_PROP\_SATURATION** Saturation of the image (only for cameras).
- **CV\_CAP\_PROP\_HUE** Hue of the image (only for cameras).
- **CV\_CAP\_PROP\_GAIN** Gain of the image (only for cameras).
- **CV\_CAP\_PROP\_EXPOSURE** Exposure (only for cameras).
- **CV\_CAP\_PROP\_CONVERT\_RGB** Boolean flags indicating whether images should be converted
to RGB.
- **CV\_CAP\_PROP\_WHITE\_BALANCE** Currently unsupported
- **CV\_CAP\_PROP\_RECTIFICATION** Rectification flag for stereo cameras (note: only supported
by DC1394 v 2.x backend currently)
@param value Value of the property.
*/
CV_WRAP virtual bool set(int propId, double value);
/** @brief Returns the specified VideoCapture property
@param propId Property identifier. It can be one of the following:
- **CV\_CAP\_PROP\_POS\_MSEC** Current position of the video file in milliseconds or video
capture timestamp.
- **CV\_CAP\_PROP\_POS\_FRAMES** 0-based index of the frame to be decoded/captured next.
- **CV\_CAP\_PROP\_POS\_AVI\_RATIO** Relative position of the video file: 0 - start of the
film, 1 - end of the film.
- **CV\_CAP\_PROP\_FRAME\_WIDTH** Width of the frames in the video stream.
- **CV\_CAP\_PROP\_FRAME\_HEIGHT** Height of the frames in the video stream.
- **CV\_CAP\_PROP\_FPS** Frame rate.
- **CV\_CAP\_PROP\_FOURCC** 4-character code of codec.
- **CV\_CAP\_PROP\_FRAME\_COUNT** Number of frames in the video file.
- **CV\_CAP\_PROP\_FORMAT** Format of the Mat objects returned by retrieve() .
- **CV\_CAP\_PROP\_MODE** Backend-specific value indicating the current capture mode.
- **CV\_CAP\_PROP\_BRIGHTNESS** Brightness of the image (only for cameras).
- **CV\_CAP\_PROP\_CONTRAST** Contrast of the image (only for cameras).
- **CV\_CAP\_PROP\_SATURATION** Saturation of the image (only for cameras).
- **CV\_CAP\_PROP\_HUE** Hue of the image (only for cameras).
- **CV\_CAP\_PROP\_GAIN** Gain of the image (only for cameras).
- **CV\_CAP\_PROP\_EXPOSURE** Exposure (only for cameras).
- **CV\_CAP\_PROP\_CONVERT\_RGB** Boolean flags indicating whether images should be converted
to RGB.
- **CV\_CAP\_PROP\_WHITE\_BALANCE** Currently not supported
- **CV\_CAP\_PROP\_RECTIFICATION** Rectification flag for stereo cameras (note: only supported
by DC1394 v 2.x backend currently)
**Note**: When querying a property that is not supported by the backend used by the VideoCapture
class, value 0 is returned.
*/
CV_WRAP virtual double get(int propId);
protected:
@ -374,21 +567,63 @@ private:
static Ptr<IVideoCapture> createCameraCapture(int index);
};
/** @brief Video writer class.
*/
class CV_EXPORTS_W VideoWriter
{
public:
/** @brief VideoWriter constructors
The constructors/functions initialize video writers. On Linux FFMPEG is used to write videos; on
Windows FFMPEG or VFW is used; on MacOSX QTKit is used.
*/
CV_WRAP VideoWriter();
/** @overload
@param filename Name of the output video file.
@param fourcc 4-character code of codec used to compress the frames. For example,
VideoWriter::fourcc('P','I','M','1') is a MPEG-1 codec, VideoWriter::fourcc('M','J','P','G') is a
motion-jpeg codec etc. List of codes can be obtained at [Video Codecs by
FOURCC](http://www.fourcc.org/codecs.php) page.
@param fps Framerate of the created video stream.
@param frameSize Size of the video frames.
@param isColor If it is not zero, the encoder will expect and encode color frames, otherwise it
will work with grayscale frames (the flag is currently supported on Windows only).
*/
CV_WRAP VideoWriter(const String& filename, int fourcc, double fps,
Size frameSize, bool isColor = true);
virtual ~VideoWriter();
/** @brief Initializes or reinitializes video writer.
The method opens video writer. Parameters are the same as in the constructor
VideoWriter::VideoWriter.
*/
CV_WRAP virtual bool open(const String& filename, int fourcc, double fps,
Size frameSize, bool isColor = true);
/** @brief Returns true if video writer has been successfully initialized.
*/
CV_WRAP virtual bool isOpened() const;
CV_WRAP virtual void release();
virtual VideoWriter& operator << (const Mat& image);
/** @brief Writes the next video frame
@param image The written frame
The functions/methods write the specified image to video file. It must have the same size as has
been specified when opening the video writer.
*/
CV_WRAP virtual void write(const Mat& image);
/** @brief Concatenates 4 chars to a fourcc code
This static method constructs the fourcc code of the codec to be used in the constructor
VideoWriter::VideoWriter or VideoWriter::open.
*/
CV_WRAP static int fourcc(char c1, char c2, char c3, char c4);
protected:
@ -398,6 +633,8 @@ protected:
template<> CV_EXPORTS void DefaultDeleter<CvCapture>::operator ()(CvCapture* obj) const;
template<> CV_EXPORTS void DefaultDeleter<CvVideoWriter>::operator ()(CvVideoWriter* obj) const;
//! @} videoio
} // cv
#endif //__OPENCV_VIDEOIO_HPP__

6
modules/videoio/include/opencv2/videoio/cap_ios.h
View File

@ -32,6 +32,9 @@
#import <ImageIO/ImageIO.h>
#include "opencv2/core.hpp"
//! @addtogroup videoio_ios
//! @{
/////////////////////////////////////// CvAbstractCamera /////////////////////////////////////
@class CvAbstractCamera;
@ -167,3 +170,6 @@
- (void)takePicture;
@end
//! @} videoio_ios

5
modules/videoio/include/opencv2/videoio/videoio_c.h
View File

@ -48,6 +48,10 @@
extern "C" {
#endif /* __cplusplus */
/**
@addtogroup videoio_c
@{
*/
/****************************************************************************************\
* Working with Video Files and Cameras *
@ -416,6 +420,7 @@ CVAPI(void) cvReleaseVideoWriter( CvVideoWriter** writer );
#define cvCreateAVIWriter cvCreateVideoWriter
#define cvWriteToAVI cvWriteFrame
/** @} videoio_c */
#ifdef __cplusplus
}