Extend optical flow tutorial (#14314)
* extend python optical flow tutorial with cpp example code and add it to general tutorial directory
* remove unused parameters, fix comparison between signed and unsigned int
* fix hsv range problem
* switch to samples::findFile for sample file location
* switch to command line parameter for path
* remove old tutorial as in 14393
* minor fixes
Extend meanshift tutorial (#14393)
* copy original tutorial and python code
* add cpp code, fix python code
* add camshift cpp code, fix bug in meanshift code
* add description to ToC page
* fix shadowing previous local declaration
* fix grammar: with -> within
* docs: remove content of old py_meanshift tutorial, add link
* docs: replace meanshift tutorial subpage in Python tutorials
* switch to ref to fix wrong breadcrumb navigation
* switch to cmdline for path as in #14314
* Apply suggestions from code review
* order programming languages alphabetically
* Created python version of the code for the anisotropic image segmentation tutorial. Created python/cpp toggles for the markdown file.
* fix doxygen warnings
* Python wrapper for detail
* hide pyrotationwrapper
* copy code in pyopencv_rotationwarper.hpp
* move ImageFeatures MatchInfo and CameraParams in core/misc/
* add python test for detail
* move test_detail in test_stitching
* rename
The load() function returns a new object, and as such does not use the one it is called on.
This commit updates the uses of model.load in this program so it will work as intended and not throw an error.
[evolution] Stitching for OpenCV 4.0
* stitching: wrap Stitcher::create for bindings
* provide method for consistent stitcher usage across languages
* samples: add python stitching sample
* port cpp stitching sample to python
* stitching: consolidate Stitcher create methods
* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create
* stitching: avoid anonymous enum in Stitcher
* ORIG_RESOL should be double
* add documentatiton
* stitching: improve documentation in Stitcher
* stitching: expose estimator in Stitcher
* remove ABI hack
* stitching: drop try_use_gpu flag
* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually
* stitching: drop FeaturesFinder
* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d
* features2d: fix compute and detect to work with UMat vectors
* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg
* stitching: use nearest interpolation for resizing masks
* fix warnings
* moved DIS optical flow from opencv_contrib to opencv, moved TVL1 from opencv to opencv_contrib
* fixed compile warning
* TVL1 optical flow example moved to opencv_contrib
- accepts script parameter (allows drag & drop from 'explorer')
- use script dir instead of current dir (can launch samples from 'samples/dnn')
- added 'pause' to show error messages (about missing numpy) instead of instant closing
* fix faster_rcnn sample crashed at PoolingInvoker operator() of pooling_layer.
* find_odj onmouse bug about find matched point status.
* reverted AutoBuffer back to std::vector
Following were the errors in the digits_video.py
1 ) The code was not working because data type of x was float however in "cv2.rectangle" we require integer .
2 ) After pressing the "esc" button the image windows did not destroy
So I amended following things:
1 ) ~converted data type of x to int.~ Used Python integer division (//)
2 ) used cv2.destroyAllWindows() to close all windows after the press of "esc" by user.
*Fixing typos;
*Making codes more similar to the main one, in C++;
*Adding Grayscale option to the Python and Java codes;
*Fixing python identation, whitespaces and redundancies.
* Extending template_matching tutorial with Java
* adding mask to java version of the tutorial
* adding the python toggle and code
* updating table of content
* adding py and java to table of content
* adding mask to python
* going back to markdown with duplicated text
* non duplicated text
The docstring for one of the Python sample programs includes a link to the research paper describing the main algorithm. That link is no longer valid (results in a 404 error) so this update replaces it with another link from the same institution which is currently valid.
* GSoC 2016 - Adding toggle files to be used by tutorials.
Add a toggle option for tutorials.
* adds a button on the HTML tutorial pages to switch between blocks
* the default option is for languages: one can write a block
for C++ and another one for Python without re-writing the tutorial
Add aliases to the doxyfile.
* adding alises to make a link to previous and next tutorial.
* adding alias to specify the toggle options in the tutorials index.
* adding alias to add a youtube video directly from link.
Add a sample tutorial (mat_mask_opertaions) using the developed aliases:
* youtube alias
* previous and next tutorial alias
* buttons
* languages info for tutorial table of content
* code referances with snippets (and associated sample code files)
* Removing the automatic ordering.
Adding specific toggles for cpp, java and python.
Move all the code to the footer / header and Doxyfile.
Updating documentation.
I noticed that I missed the fact that `cimg` is used in the second `imshow()` call. Changed the scope of the second function call to be within the if-statement. Otherwise in cases where have not been detected the second `imshow()` will attempt to use `cimg` which will be empty leading to an error.
In the C++ equivalent of this example a check is made whether the vector (here in Python we have a list) actually has any lines in it that is whether the Hough lines function has managed to find any in the given image. This check is missing for the Python example and if no lines are found the application breaks.
In the C++ equivalent of this example a check is made whether the vector (here in Python we have a list) actually has any circles in it that is whether the Hough circles function has managed to find any in the given image. This check is missing for the Python example and if no circles are found the application breaks.
1. Following condition is True on each iteration becuase -1 % 0xFF is 255 not -1
code = cv2.waitKey(100) % 0x100
if code != -1:
break
this were resetting point position on each cycle not on key press as intended
2. Previous small bug were masking serious bug with matrix operation on matrices of incorrect size.
As the result on 2nd iteration of internal cycle program has crushed.
I have fixed it too, matrix operation was taken from examples/cpp/kalman.cpp where it looks like
randn( processNoise, Scalar(0), Scalar::all(sqrt(KF.processNoiseCov.at<float>(0, 0))));
which is something totally different from previous code here.
Example behave as it should now, i.e. point moving by circle trajectory as in C++ example.
