<!--
If you have a question rather than reporting a bug please go to http://answers.opencv.org where you get much faster responses.
-If you need further assistance please read [How To Contribute](https://github.com/Itseez/opencv/wiki/How_to_contribute).
+If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).
This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
-->
set(FFMPEG_FILE_HASH_BIN64 "35fe6ccdda6d7a04e9056b0d73b98e76")
set(FFMPEG_FILE_HASH_CMAKE "8606f947a780071f8fcce8cbf39ceef5")
-set(FFMPEG_DOWNLOAD_URL ${OPENCV_FFMPEG_URL};$ENV{OPENCV_FFMPEG_URL};https://raw.githubusercontent.com/Itseez/opencv_3rdparty/${FFMPEG_BINARIES_COMMIT}/ffmpeg/)
+set(FFMPEG_DOWNLOAD_URL ${OPENCV_FFMPEG_URL};$ENV{OPENCV_FFMPEG_URL};https://raw.githubusercontent.com/opencv/opencv_3rdparty/${FFMPEG_BINARIES_COMMIT}/ffmpeg/)
ocv_download(PACKAGE opencv_ffmpeg.dll
HASH ${FFMPEG_FILE_HASH_BIN32}
if(DEFINED ENV{OPENCV_ICV_URL})
set(OPENCV_ICV_URL $ENV{OPENCV_ICV_URL})
else()
- set(OPENCV_ICV_URL "https://raw.githubusercontent.com/Itseez/opencv_3rdparty/${IPPICV_BINARIES_COMMIT}/ippicv")
+ set(OPENCV_ICV_URL "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${IPPICV_BINARIES_COMMIT}/ippicv")
endif()
endif()
## Contributing guidelines
-All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/Itseez/opencv/wiki/How_to_contribute).
+All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/opencv/opencv/wiki/How_to_contribute).
* Homepage: <http://opencv.org>
* Docs: <http://docs.opencv.org/master/>
* Q&A forum: <http://answers.opencv.org>
-* Issue tracking: <https://github.com/Itseez/opencv/issues>
+* Issue tracking: <https://github.com/opencv/opencv/issues>
#### Contributing
-Please read before starting work on a pull request: <https://github.com/Itseez/opencv/wiki/How_to_contribute>
+Please read before starting work on a pull request: <https://github.com/opencv/opencv/wiki/How_to_contribute>
Summary of guidelines:
TOC_EXPAND = NO
GENERATE_QHP = @CMAKE_DOXYGEN_GENERATE_QHP@
QCH_FILE = ../opencv-@OPENCV_VERSION@.qch
-QHP_NAMESPACE = org.itseez.opencv.@OPENCV_VERSION@
+QHP_NAMESPACE = org.opencv.@OPENCV_VERSION@
QHP_VIRTUAL_FOLDER = opencv
QHP_CUST_FILTER_NAME =
QHP_CUST_FILTER_ATTRS =
Below code shows the computation of BRIEF descriptors with the help of CenSurE detector. (CenSurE
detector is called STAR detector in OpenCV)
-note, that you need [opencv contrib](https://github.com/Itseez/opencv_contrib)) to use this.
+note, that you need [opencv contrib](https://github.com/opencv/opencv_contrib)) to use this.
@code{.py}
import numpy as np
import cv2
So this is a summary of SIFT algorithm. For more details and understanding, reading the original
paper is highly recommended. Remember one thing, this algorithm is patented. So this algorithm is
-included in [the opencv contrib repo](https://github.com/Itseez/opencv_contrib)
+included in [the opencv contrib repo](https://github.com/opencv/opencv_contrib)
SIFT in OpenCV
--------------
Since OpenCV is an open source initiative, all are welcome to make contributions to the library,
documentation, and tutorials. If you find any mistake in this tutorial (from a small spelling
mistake to an egregious error in code or concept), feel free to correct it by cloning OpenCV in
-[GitHub](https://github.com/Itseez/opencv) and submitting a pull request. OpenCV developers will
+[GitHub](https://github.com/opencv/opencv) and submitting a pull request. OpenCV developers will
check your pull request, give you important feedback and (once it passes the approval of the
reviewer) it will be merged into OpenCV. You will then become an open source contributor :-)
choose this. It always keeps your OpenCV up-to-date). For that, you need to install **Git** first.
@code{.sh}
yum install git
-git clone https://github.com/Itseez/opencv.git
+git clone https://github.com/opencv/opencv.git
@endcode
It will create a folder OpenCV in home directory (or the directory you specify). The cloning may
take some time depending upon your internet connection.
-# Download OpenCV source. It can be from
[Sourceforge](http://sourceforge.net/projects/opencvlibrary/) (for official release version) or
- from [Github](https://github.com/Itseez/opencv) (for latest source).
+ from [Github](https://github.com/opencv/opencv) (for latest source).
-# Extract it to a folder, opencv and create a new folder build in it.
-# Open CMake-gui (*Start \> All Programs \> CMake-gui*)
-# Fill the fields as follows (see the image below):
You may also find the source code in the `samples/cpp/tutorial_code/calib3d/camera_calibration/`
folder of the OpenCV source library or [download it from here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
single argument: the name of its configuration file. If none is given then it will try to open the
one named "default.xml". [Here's a sample configuration file
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
configuration file you may choose to use camera as an input, a video file or an image list. If you
opt for the last one, you will need to create a configuration file where you enumerate the images to
-use. Here's [an example of this ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
+use. Here's [an example of this ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
The important part to remember is that the images need to be specified using the absolute path or
the relative one from your application's working directory. You may find all this in the samples
directory mentioned above.
- *camera_resolution*: resolution of camera which is used for calibration
**Note:** *charuco_dict*, *charuco_square_lenght* and *charuco_marker_size* are used for chAruco pattern generation
-(see Aruco module description for details: [Aruco tutorials](https://github.com/Itseez/opencv_contrib/tree/master/modules/aruco/tutorials))
+(see Aruco module description for details: [Aruco tutorials](https://github.com/opencv/opencv_contrib/tree/master/modules/aruco/tutorials))
Default chAruco pattern:
----
- This code is in your OpenCV sample folder. Otherwise you can grab it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
Explanation
-----------
-----------
You can [download this from here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
find it in the
`samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp` of the
OpenCV source code library.
example, let us find out if a text is horizontal or not? Looking at some text you'll notice that the
text lines sort of form also horizontal lines and the letters form sort of vertical lines. These two
main components of a text snippet may be also seen in case of the Fourier transform. Let us use
-[this horizontal ](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextR.png)
+[this horizontal ](https://github.com/opencv/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/opencv/opencv/tree/master/samples/data/imageTextR.png)
image about a text.
In case of the horizontal text:
-----------
You can [download this from here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
`samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp` of the OpenCV source code
library.
will make the scanning for each image using all of these methods, and print out how long it took.
You can download the full source code [here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
the samples directory of OpenCV at the cpp tutorial code for the core section. Its basic usage is:
@code{.bash}
how_to_scan_images imageName.jpg intValueToReduce [G]
You may also find the source code in the
`samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp` file of the OpenCV source library or
-download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
+download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
@include cpp/tutorial_code/core/ippasync/ippasync_sample.cpp
A case study
------------
-Now that you have the basics done [here's](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
+Now that you have the basics done [here's](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
an example that mixes the usage of the C interface with the C++ one. You will also find it in the
sample directory of the OpenCV source code library at the
`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp` .
You may observe a runtime instance of this on the [YouTube
here](https://www.youtube.com/watch?v=qckm-zvo31w) and you can [download the source code from here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
or find it in the
`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp`
of the OpenCV source code library.
You can download this source code from [here
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
OpenCV source code libraries sample directory at
`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
Most of the samples here have been included in a small console application. You can download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
or in the core section of the cpp samples.
You can also find a quick video demonstration of this on
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
@code{.cpp}
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
@include cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
@code{.cpp}
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
@code{.cpp}
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
You may also find the source code and these video file in the
`samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity` folder of the OpenCV
-source library or download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
+source library or download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
The full source code is quite long (due to the controlling of the application via the command line
arguments and performance measurement). Therefore, to avoid cluttering up these sections with those
you'll find here only the functions itself.
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
@include samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp
Explanation
- Applies 4 different kinds of filters (explained in Theory) and show the filtered images
sequentially
- **Downloadable code**: Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Smoothing.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Smoothing.cpp)
- **Code at glance:**
@code{.cpp}
#include "opencv2/imgproc.hpp"
- **Downloadable code**:
-# Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
for the basic version (explained in this tutorial).
-# For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
skin area) you can check the [improved
- demo](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
+ demo](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
-# ...or you can always check out the classical
- [camshiftdemo](https://github.com/Itseez/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
+ [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
in samples.
- **Code at glance:**
- Calculate the Histogram of each 1-channel plane by calling the function @ref cv::calcHist
- Plot the three histograms in a window
- **Downloadable code**: Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp
histogram of the lower half base image and with the same base image histogram.
- Display the numerical matching parameters obtained.
- **Downloadable code**: Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
- **Code at glance:**
@include cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
- Equalize the Histogram by using the OpenCV function @ref cv::equalizeHist
- Display the source and equalized images in a window.
- **Downloadable code**: Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp
- Localize the location with higher matching probability
- Draw a rectangle around the area corresponding to the highest match
- **Downloadable code**: Click
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
- Applies the mask obtained on the original image and display it in a window.
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
Explanation
- The program finishes when the user presses 'ESC'
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp
Explanation
----
This tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp).
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp).
@include samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
Explanation / Result
- The filter output (with each kernel) will be shown during 500 milliseconds
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp)
@code{.cpp}
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
- Applies the *Hough Circle Transform* to the blurred image .
- Display the detected circle in a window.
--# The sample code that we will explain can be downloaded from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/houghcircles.cpp).
+-# The sample code that we will explain can be downloaded from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/houghcircles.cpp).
A slightly fancier version (which shows trackbars for
- changing the threshold values) can be found [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp).
+ changing the threshold values) can be found [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp).
@include samples/cpp/houghcircles.cpp
Explanation
- Applies either a *Standard Hough Line Transform* or a *Probabilistic Line Transform*.
- Display the original image and the detected line in two windows.
--# The sample code that we will explain can be downloaded from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/houghlines.cpp). A slightly fancier version
+-# The sample code that we will explain can be downloaded from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/houghlines.cpp). A slightly fancier version
(which shows both Hough standard and probabilistic with trackbars for changing the threshold
- values) can be found [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp).
+ values) can be found [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp).
@include samples/cpp/houghlines.cpp
Explanation
- Display the result in a window
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
Explanation
- Wait for the user to exit the program
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp
Explanation
bright on a darker background.
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
Explanation
- Waits until the user exits the program
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp
Explanation
Code
----
-This tutorial code's is shown lines below. You can also download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp).
+This tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp).
@include samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp
Explanation / Result
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp)
@code{.cpp}
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Pyramids.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Pyramids.cpp)
@include samples/cpp/tutorial_code/ImgProc/Pyramids.cpp
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp
Explanation
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp
Explanation
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp
Explanation
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp
Explanation
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp
Explanation
----
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold.cpp)
@include samples/cpp/tutorial_code/ImgProc/Threshold.cpp
Explanation
----
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
@include samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp
Explanation
This tutorial also assumes you have an Android operated device with OpenCL enabled.
The related source code is located within OpenCV samples at
-[opencv/samples/android/tutorial-4-opencl](https://github.com/Itseez/opencv/tree/master/samples/android/tutorial-4-opencl/) directory.
+[opencv/samples/android/tutorial-4-opencl](https://github.com/opencv/opencv/tree/master/samples/android/tutorial-4-opencl/) directory.
Preface
-------
@endcode
Let's leave the details of their implementation beyond of this tutorial, please refer the
-[source code](https://github.com/Itseez/opencv/tree/master/samples/android/tutorial-4-opencl/) to see them.
+[source code](https://github.com/opencv/opencv/tree/master/samples/android/tutorial-4-opencl/) to see them.
Preview Frames modification
---------------------------
@code{.bash}
cd ~/
mkdir opt
-git clone https://github.com/Itseez/opencv.git
+git clone https://github.com/opencv/opencv.git
cd opencv
git checkout 2.4
mkdir build
--------------------------
You can use the latest stable OpenCV version available in *sourceforge* or you can grab the latest
-snapshot from our [Git repository](https://github.com/Itseez/opencv.git).
+snapshot from our [Git repository](https://github.com/opencv/opencv.git).
### Getting the Latest Stable OpenCV Version
### Getting the Cutting-edge OpenCV from the Git Repository
-Launch Git client and clone [OpenCV repository](http://github.com/itseez/opencv)
+Launch Git client and clone [OpenCV repository](http://github.com/opencv/opencv)
In Linux it can be achieved with the following command in Terminal:
@code{.bash}
cd ~/<my_working _directory>
-git clone https://github.com/Itseez/opencv.git
+git clone https://github.com/opencv/opencv.git
@endcode
Building OpenCV
sources.
Another option to get OpenCV sources is to clone [OpenCV git
-repository](https://github.com/Itseez/opencv/). In order to build OpenCV with Java bindings you need
+repository](https://github.com/opencv/opencv/). In order to build OpenCV with Java bindings you need
JDK (Java Development Kit) (we recommend [Oracle/Sun JDK 6 or
7](http://www.oracle.com/technetwork/java/javase/downloads/)), [Apache Ant](http://ant.apache.org/)
and Python v2.6 or higher to be installed.
Let's build OpenCV:
@code{.bash}
-git clone git://github.com/Itseez/opencv.git
+git clone git://github.com/opencv/opencv.git
cd opencv
git checkout 2.4
mkdir build
-----------
Download the source code from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp).
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp).
@include cpp/tutorial_code/introduction/display_image/display_image.cpp
### Getting the Cutting-edge OpenCV from Git Repository
-Launch GIT client and clone OpenCV repository from [here](http://github.com/itseez/opencv)
+Launch GIT client and clone OpenCV repository from [here](http://github.com/opencv/opencv)
In MacOS it can be done using the following command in Terminal:
@code{.bash}
cd ~/<my_working _directory>
-git clone https://github.com/Itseez/opencv.git
+git clone https://github.com/opencv/opencv.git
@endcode
Building OpenCV from Source, using CMake and Command Line
--------------------------
You can use the latest stable OpenCV version or you can grab the latest snapshot from our [Git
-repository](https://github.com/Itseez/opencv.git).
+repository](https://github.com/opencv/opencv.git).
### Getting the Latest Stable OpenCV Version
### Getting the Cutting-edge OpenCV from the Git Repository
-Launch Git client and clone [OpenCV repository](http://github.com/itseez/opencv). If you need
-modules from [OpenCV contrib repository](http://github.com/itseez/opencv_contrib) then clone it too.
+Launch Git client and clone [OpenCV repository](http://github.com/opencv/opencv). If you need
+modules from [OpenCV contrib repository](http://github.com/opencv/opencv_contrib) then clone it too.
For example
@code{.bash}
cd ~/<my_working_directory>
-git clone https://github.com/Itseez/opencv.git
-git clone https://github.com/Itseez/opencv_contrib.git
+git clone https://github.com/opencv/opencv.git
+git clone https://github.com/opencv/opencv_contrib.git
@endcode
Building OpenCV from Source Using CMake
---------------------------------------
-# [optional] Running tests
- Get the required test data from [OpenCV extra
- repository](https://github.com/Itseez/opencv_extra).
+ repository](https://github.com/opencv/opencv_extra).
For example
@code{.bash}
- git clone https://github.com/Itseez/opencv_extra.git
+ git clone https://github.com/opencv/opencv_extra.git
@endcode
- set OPENCV_TEST_DATA_PATH environment variable to \<path to opencv_extra/testdata\>.
- execute tests from build directory.
This section describes most notable changes in general, all details and examples of transition actions are in the next part of the document.
##### Contrib repository
-<https://github.com/Itseez/opencv_contrib>
+<https://github.com/opencv/opencv_contrib>
This is a place for all new, experimental and non-free algorithms. It does not receive so much attention from the support team comparing to main repository, but the community makes an effort to keep it in a good shape.
solutions described in those videos are no longer supported and may even break your install.
If you are building your own libraries you can take the source files from our [Git
-repository](https://github.com/Itseez/opencv.git).
+repository](https://github.com/opencv/opencv.git).
Building the OpenCV library from scratch requires a couple of tools installed beforehand:
you're doing -- it's OK.
-# Clone the repository to the selected directory. After clicking *Clone* button, a window will
appear where you can select from what repository you want to download source files
- (<https://github.com/Itseez/opencv.git>) and to what directory (`D:/OpenCV`).
+ (<https://github.com/opencv/opencv.git>) and to what directory (`D:/OpenCV`).
-# Push the OK button and be patient as the repository is quite a heavy download. It will take
some time depending on your Internet connection.
--------
Now to try this out download our little test [source code
-](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/introduction/windows_visual_studio_Opencv/introduction_windows_vs.cpp)
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/introduction/windows_visual_studio_Opencv/introduction_windows_vs.cpp)
or get it from the sample code folder of the OpenCV sources. Add this to your project and build it.
Here's its content:
This is important to remember when you code inside the code open and save commands. You're resources
will be saved ( and queried for at opening!!!) relatively to your working directory. This is unless
you give a full, explicit path as parameter for the I/O functions. In the code above we open [this
-OpenCV logo](https://github.com/Itseez/opencv/tree/master/samples/data/opencv-logo.png). Before starting up the application make sure you place
+OpenCV logo](https://github.com/opencv/opencv/tree/master/samples/data/opencv-logo.png). Before starting up the application make sure you place
the image file in your current working directory. Modify the image file name inside the code to try
it out on other images too. Run it and voil á:
-----------
This tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp).
+ [here](https://github.com/opencv/tree/master/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp).
@include cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp
-@note Another example using PCA for dimensionality reduction while maintaining an amount of variance can be found at [opencv_source_code/samples/cpp/pca.cpp](https://github.com/Itseez/opencv/tree/master/samples/cpp/pca.cpp)
+@note Another example using PCA for dimensionality reduction while maintaining an amount of variance can be found at [opencv_source_code/samples/cpp/pca.cpp](https://github.com/opencv/tree/master/samples/cpp/pca.cpp)
Explanation
-----------
-----------
You may also find the source code in `samples/cpp/tutorial_code/ml/non_linear_svms` folder of the OpenCV source library or
-[download it from here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp).
+[download it from here](https://github.com/opencv/tree/master/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp).
@note The following code has been implemented with OpenCV 3.0 classes and functions. An equivalent version of the code
using OpenCV 2.4 can be found in [this page.](http://docs.opencv.org/2.4/doc/tutorials/ml/non_linear_svms/non_linear_svms.html#nonlinearsvms)
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection.cpp)
+[here](https://github.com/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection.cpp)
. The second version (using LBP for face detection) can be [found
-here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp)
+here](https://github.com/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp)
@code{.cpp}
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
-# @ref cv::BackgroundSubtractorMOG2
The results as well as the input data are shown on the screen.
-The source file can be downloaded [here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/video/bg_sub.cpp).
+The source file can be downloaded [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/bg_sub.cpp).
@include samples/cpp/tutorial_code/video/bg_sub.cpp
flag value is assumed by default if neither of the two possible values of the property is set.
For more information please refer to the example of usage
-[intelperc_capture.cpp](https://github.com/Itseez/opencv/tree/master/samples/cpp/intelperc_capture.cpp)
+[intelperc_capture.cpp](https://github.com/opencv/tree/master/samples/cpp/intelperc_capture.cpp)
in opencv/samples/cpp folder.
- CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_REGISTRATION
For more information please refer to the example of usage
-[openni_capture.cpp](https://github.com/Itseez/opencv/tree/master/samples/cpp/openni_capture.cpp) in
+[openni_capture.cpp](https://github.com/opencv/tree/master/samples/cpp/openni_capture.cpp) in
opencv/samples/cpp folder.
video files and performs a similarity check between them. This is something you could use to check
just how well a new video compressing algorithms works. Let there be a reference (original) video
like [this small Megamind clip
-](https://github.com/Itseez/opencv/tree/master/samples/data/Megamind.avi) and [a compressed
-version of it ](https://github.com/Itseez/opencv/tree/master/samples/data/Megamind_bugy.avi).
+](https://github.com/opencv/opencv/tree/master/samples/data/Megamind.avi) and [a compressed
+version of it ](https://github.com/opencv/opencv/tree/master/samples/data/Megamind_bugy.avi).
You may also find the source code and these video file in the
`samples/data` folder of the OpenCV source library.
You may also find the source code and these video file in the
`samples/cpp/tutorial_code/videoio/video-write/` folder of the OpenCV source library or [download it
-from here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/videoio/video-write/video-write.cpp).
+from here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/videoio/video-write/video-write.cpp).
@include cpp/tutorial_code/videoio/video-write/video-write.cpp
Code
----
-You can download the code from [here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/viz/creating_widgets.cpp).
+You can download the code from [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/viz/creating_widgets.cpp).
@include samples/cpp/tutorial_code/viz/creating_widgets.cpp
Explanation
Code
----
-You can download the code from [here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/viz/launching_viz.cpp).
+You can download the code from [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/viz/launching_viz.cpp).
@include samples/cpp/tutorial_code/viz/launching_viz.cpp
Explanation
Code
----
-You can download the code from [here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/viz/transformations.cpp).
+You can download the code from [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/viz/transformations.cpp).
@include samples/cpp/tutorial_code/viz/transformations.cpp
Explanation
Code
----
-You can download the code from [here ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/viz/widget_pose.cpp).
+You can download the code from [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/viz/widget_pose.cpp).
@include samples/cpp/tutorial_code/viz/widget_pose.cpp
Explanation
3. Merge the results into a single disparity map.
With this algorithm, a dual GPU gave a 180% performance increase comparing to the single Fermi GPU.
-For a source code example, see <https://github.com/Itseez/opencv/tree/master/samples/gpu/>.
+For a source code example, see <https://github.com/opencv/opencv/tree/master/samples/gpu/>.
@param winname Name of the window.
@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
+<https://github.com/opencv/opencv/tree/master/samples/cpp/ffilldemo.cpp>, on how to specify and
use the callback.
@param userdata The optional parameter passed to the callback.
*/
regions are calculated rapidly using integral images (see below and the integral description).
To see the object detector at work, have a look at the facedetect demo:
-<https://github.com/Itseez/opencv/tree/master/samples/cpp/dbt_face_detection.cpp>
+<https://github.com/opencv/opencv/tree/master/samples/cpp/dbt_face_detection.cpp>
The following reference is for the detection part only. There is a separate application called
opencv_traincascade that can train a cascade of boosted classifiers from a set of samples.
class StatModel(object):
def load(self, fn):
- self.model.load(fn) # Known bug: https://github.com/Itseez/opencv/issues/4969
+ self.model.load(fn) # Known bug: https://github.com/opencv/opencv/issues/4969
def save(self, fn):
self.model.save(fn)
em.setCovarianceMatrixType(cv2.ml.EM_COV_MAT_GENERIC)
em.trainEM(points)
means = em.getMeans()
- covs = em.getCovs() # Known bug: https://github.com/Itseez/opencv/pull/4232
+ covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232
found_distrs = zip(means, covs)
matches_count = 0
repoPath = None
extraTestDataPath = None
# github repository url
- repoUrl = 'https://raw.github.com/Itseez/opencv/master'
+ repoUrl = 'https://raw.github.com/opencv/opencv/master'
def get_sample(self, filename, iscolor = cv2.IMREAD_COLOR):
if not filename in self.image_cache:
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>
+ <https://github.com/opencv/opencv/tree/master/samples/cpp/openni_capture.cpp>
*/
CV_WRAP virtual bool grab();
Tested On: LMLBT44 with 8 video inputs
Problems? Post your questions at answers.opencv.org,
Report bugs at code.opencv.org,
- Submit your fixes at https://github.com/Itseez/opencv/
+ Submit your fixes at https://github.com/opencv/opencv/
Patched Comments:
TW: The cv cam utils that came with the initial release of OpenCV for LINUX Beta4
Tested On: LMLBT44 with 8 video inputs
Problems? Post your questions at answers.opencv.org,
Report bugs at code.opencv.org,
- Submit your fixes at https://github.com/Itseez/opencv/
+ Submit your fixes at https://github.com/opencv/opencv/
Patched Comments:
TW: The cv cam utils that came with the initial release of OpenCV for LINUX Beta4
===============================
1. You might need to install this if you haven't already: http://www.microsoft.com/en-US/download/details.aspx?id=40784
-2. Set OPENCV_TEST_DATA_PATH environment variable to location of opencv_extra/testdata (cloning of https://github.com/Itseez/opencv_extra repo required) to get tests work correctly. Also, set OPENCV_PERF_VALIDATION_DIR environment variable in case you are planning to have place where to store performance test results and compare them with the future test runs.
+2. Set OPENCV_TEST_DATA_PATH environment variable to location of opencv_extra/testdata (cloning of https://github.com/opencv/opencv_extra repo required) to get tests work correctly. Also, set OPENCV_PERF_VALIDATION_DIR environment variable in case you are planning to have place where to store performance test results and compare them with the future test runs.
3. In case you'd like to adjust some flags that are defaulted by setup_winrt script, go to "Manual build" section. Otherwise go to platforms/winrt and execute
// http://docs.opencv.org/doc/tutorials/calib3d/camera_calibration/camera_calibration.html
//
// It uses standard OpenCV asymmetric circles grid pattern 11x4:
-// https://github.com/Itseez/opencv/blob/2.4/doc/acircles_pattern.png.
+// https://github.com/opencv/opencv/blob/2.4/doc/acircles_pattern.png.
// The results are the camera matrix and 5 distortion coefficients.
//
// Tap on highlighted pattern to capture pattern corners for calibration.
"\tThis will detect only the face in image.jpg.\n";
cout << " \n\nThe classifiers for face and eyes can be downloaded from : "
- " \nhttps://github.com/Itseez/opencv/tree/master/data/haarcascades";
+ " \nhttps://github.com/opencv/opencv/tree/master/data/haarcascades";
cout << "\n\nThe classifiers for nose and mouth can be downloaded from : "
- " \nhttps://github.com/Itseez/opencv_contrib/tree/master/modules/face/data/cascades\n";
+ " \nhttps://github.com/opencv/opencv_contrib/tree/master/modules/face/data/cascades\n";
}
static void detectFaces(Mat& img, vector<Rect_<int> >& faces, string cascade_path)
Online docs: http://docs.opencv.org
Q&A forum: http://answers.opencv.org
Issue tracker: http://code.opencv.org
- GitHub: https://github.com/Itseez/opencv/
+ GitHub: https://github.com/opencv/opencv/
************************************************** */
#include "opencv2/calib3d.hpp"
class StatModel(object):
def load(self, fn):
- self.model.load(fn) # Known bug: https://github.com/Itseez/opencv/issues/4969
+ self.model.load(fn) # Known bug: https://github.com/opencv/opencv/issues/4969
def save(self, fn):
self.model.save(fn)
model = cv2.ml.SVM_load(classifier_fn)
else:
model = cv2.ml.SVM_create()
- model.load_(classifier_fn) #Known bug: https://github.com/Itseez/opencv/issues/4969
+ model.load_(classifier_fn) #Known bug: https://github.com/opencv/opencv/issues/4969
while True:
ret, frame = cap.read()
'''
Feature-based image matching sample.
-Note, that you will need the https://github.com/Itseez/opencv_contrib repo for SIFT and SURF
+Note, that you will need the https://github.com/opencv/opencv_contrib repo for SIFT and SURF
USAGE
find_obj.py [--feature=<sift|surf|orb|akaze|brisk>[-flann]] [ <image1> <image2> ]
em.setCovarianceMatrixType(cv2.ml.EM_COV_MAT_GENERIC)
em.trainEM(points)
means = em.getMeans()
- covs = em.getCovs() # Known bug: https://github.com/Itseez/opencv/pull/4232
+ covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232
found_distrs = zip(means, covs)
print('ready!\n')
color = (0, 255, 0)
cap = cv2.VideoCapture(0)
-cap.set(cv2.CAP_PROP_AUTOFOCUS, False) # Known bug: https://github.com/Itseez/opencv/pull/5474
+cap.set(cv2.CAP_PROP_AUTOFOCUS, False) # Known bug: https://github.com/opencv/opencv/pull/5474
cv2.namedWindow("Video")
projects / platform / upstream / opencv.git / commitdiff