I believe you are using the wrong version of open() on line 28 - adding deviceID + appId together. It's better to use the new version of .open() taking two integers as parameter.
Added a sample file for qrcode detection in python
* sample python file for qrcode detection added in samples/python
* input taken using argparse and the indents were removed
* Removed unused variables
* updated the format and removed unused variables
Removed the use of global variables and used parameterised contructor instead
=set multi detection true by default
* added detection from camera
* samples(python): coding style in qrcode.py
Added DaSiamRPN tracker
* added DaSiamRPN tracker
* whitespace trouble handled
* Fixes for PR
* Fixes for PR
* Fixes for PR
* added new line in the end of the file and x_crop fix
* removed cxy_wh_2_rect function
* removed loop from sofrmax function
* more detailed discription about absolute paths to onnx models
* removed nested while loop, initialization moved from main tracking loop
* added assert message for small init bb
* initial bounding box on videostream
* selection of initial bounding box improved
* created tracker class, fixed initializing bounding box
* fix round of value
* names fix
* private methods renamed
* names fixed, case for video WIP
* fix case with video
* removed hardcoded size of window
* whitespace fix
* links to models fixed
* bounding box drawing fix
* changes does not required
* code style fixes
* fixes
* frame checker added in tracking loop
* fixed import sys
* Add python version of panorama_stitching_rotating_camera and perspective_correction
* Updated code
* added in the docs
* added python code in the docs
* docs change
* Add java tutorial as well
* Add toggle in documentation
* Added the link for Java code
* format code
* Refactored code
QR-Code detector : multiple detection
* change in qr-codes detection
* change in qr-codes detection
* change in test
* change in test
* add multiple detection
* multiple detection
* multiple detect
* add parallel implementation
* add functional for performance tests
* change in test
* add perftest
* returned implementation for 1 qr-code, added support for vector<Mat> and vector<vector<Point2f>> in MultipleDetectAndDecode
* deleted all lambda expressions
* changing in triangle sort
* fixed warnings
* fixed errors
* add java and python tests
* change in java tests
* change in java and python tests
* change in perf test
* change in qrcode.cpp
* add spaces
* change in qrcode.cpp
* change in qrcode.cpp
* change in qrcode.cpp
* change in java tests
* change in java tests
* solved problems
* solved problems
* change in java and python tests
* change in python tests
* change in python tests
* change in python tests
* change in methods name
* deleted sample qrcode_multi, change in qrcode.cpp
* change in perf tests
* change in objdetect.hpp
* deleted code duplication in sample qrcode.cpp
* returned spaces
* added spaces
* deleted draw function
* change in qrcode.cpp
* change in qrcode.cpp
* deleted all draw functions
* objdetect(QR): extractVerticalLines
* objdetect(QR): whitespaces
* objdetect(QR): simplify operations, avoid duplicated code
* change in interface, additional checks in java and python tests, added new key in sample for saving original image from camera
* fix warnings and errors in python test
* fix
* write in file with space key
* solved error with empty mat check in python test
* correct path to test image
* deleted spaces
* solved error with check empty mat in python tests
* added check of empty vector of points
* samples: rework qrcode.cpp
* objdetect(QR): fix API, input parameters must be first
* objdetect(QR): test/fix points layout
* Added java code for meanshift and optical_flow
* added java code for module video
* added appropriate spaces in codes
* converted absolute path to command line arguments
* added spaces at appropriate places
Python code examples for file IO in xml and yml format
* Initial "Pythonization" of file_input_output.cpp
* Moved file_input_output.py to correct location
* Nearly done Pythonizing file_input_output.cpp
* Python equivalent of file_input_output.py created
* Started Pythonizing camera_calibration.cpp
* Completed Python tutorial/sample code for file_input_output
* Resolved whitespace issues
* Removed tabs in file_input_output.cpp
* Patched import order and wrapped code in main function
* Changed string to docstring format in help file
* Updated link to Python example code
G-API: Tutorial: Face beautification algorithm implementation
* Introduce a tutorial on face beautification algorithm
- small typo issue in render_ocv.cpp
* Addressing comments rgarnov smirnov-alexey
* G-API-NG/Docs: Added a tutorial page on interactive face detection sample
- Introduced a "--ser" option to run the pipeline serially for
benchmarking purposes
- Reorganized sample code to better fit the documentation;
- Fixed a couple of issues (mainly typos) in the public headers
* G-API-NG/Docs: Reflected meta-less compilation in new G-API tutorial
* G-API-NG/Docs: Addressed review comments on Face Analytics Pipeline example
* core: disable invalid constructors in C API by default
- C API objects will lose their default initializers through constructors
* samples: stop using of C API
* Changes disparity image to float representation
Signed-off-by: Connor James Smith <cjs.connor.smith@gmail.com>
* samples: update disparity multiplier handling in stereo_match.cpp
I think it would help to change all 3 of the the input file arguments to be "positional" for consistency with the other tutorials. This also simplifies the command line input to run this tutorial by reducing typing, and helpfully prints the "usage" info if any of the 3 required inputs are missing.
I'm new to OpenCV and working through the tutorials. I kept getting runtime errors with this one until I realized that the arguments weren't positional, and I was missing the "--input1", "--input2, "--input3" flags preceding the filenames. All of the previous tutorials had required filenames as positional arguments and didn't require this.
The original code would require each input to be specified like this:
./compareHist_Demo --input1 filename1 --input2 filename2 --input3 filename3
But with this change, the above command is simplified to:
./compareHist_Demo filename1 filename2 filename3
This avoids a confusing runtime error to make things simpler for newcomers like me :)
The usage function states that the default for match_conf is
0.65 if the default SURF feature finder is used, and 0.3 for
orbs. Indeed, if --feature orbs is used, match_conf is set
to 0.3f. This is a NOP, because the real default is also set
to 0.3f. Change it to 0.65f when SURF is in play.
* G-API: Doxygen documentatation for Async API
* G-API: Doxygen documentatation for Async API
- renamed local variable (reading parameter async) async ->
asyncNumReq in object_detection DNN sample
to avoid Doxygen erroneous linking the sample to cv::gapi::wip::async
documentation
Description:
Moved NVIDIA_Optical_flow sample app and comparison app to
opencv_contrib branch. Added CUDA_CUDA_LIBRARY in CMakeLists.txt for
resolving linker errors.
G-API: Kernel package design (#13851)
* Remove cv::unite_policy from API
* Add check that all id in kernel package are unique
* Refactor checker id procedure
* Remove cv::gapi::GLookupOrder from API
* Implement cv::gapi::use_only
* Fix samples
* Fix docs
* Fix comments to review
* Remove unite_policy
* Fix GKernelPackage::backends()
* Fix comments to review
* Fix all_unique
* Fix comments to review
* Fix comments to review
* Remove out of date tests
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
Grammatical errors for help() in detect_mser.cpp (#14122)
* Grammatical errors for help() statement
Corrected spelling of "synthetic" and added grammatical clarification for keys to press to change view or use mouse.
* Adjustment of superfluous spaces
* Created python version of the code for the anisotropic image segmentation tutorial. Created python/cpp toggles for the markdown file.
* fix doxygen warnings
Many of the Android samples rely on an options menu to work properly
but, at least on newer devices, the menu is permanently hidden by the
Android theme "Theme.NoTitleBar.Fullscreen", which means that most
of the examples were dysfunctional.
Improve stitching detailed (#13584)
* Added block size getter/setters
* Added a bunch of new features to the stitching_detailed sample
* Do not required XFEATURES2D for default use
* Add support for akaze features in stitching_detailed
* Improved sample logs
* 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.
* G-API: First steps with tutorial
* G-API Tutorial: First iteration
* G-API port of anisotropic image segmentation tutorial;
* Currently works via OpenCV only;
* Some new kernels have been required.
* G-API Tutorial: added chapters on execution code, inspection, and profiling
* G-API Tutorial: make Fluid kernel headers public
For some reason, these headers were not moved to the public
headers subtree during the initial development. Somehow it even
worked for the existing workloads.
* G-API Tutorial: Fix a couple of issues found during the work
* Introduced Phase & Sqrt kernels, OCV & Fluid versions
* Extended GKernelPackage to allow kernel removal & policies on include()
All the above stuff needs to be tested, tests will be added later
* G-API Tutorial: added chapter on running Fluid backend
* G-API Tutorial: fix a number of issues in the text
* G-API Tutorial - some final updates
- Fixed post-merge issues after Sobel kernel renaming;
- Simplified G-API code a little bit;
- Put a conclusion note in text.
* G-API Tutorial - fix build issues in test/perf targets
Public headers were refactored but tests suites were not updated in time
* G-API Tutorial: Added tests & reference docs on new kernels
* Phase
* Sqrt
* G-API Tutorial: added link to the tutorial from the main module doc
* G-API Tutorial: Added tests on new GKernelPackage functionality
* G-API Tutorial: Extended InRange tests to cover 32F
* G-API Tutorial: Misc fixes
* Avoid building examples when gapi module is not there
* Added a volatile API disclaimer to G-API root documentation page
* G-API Tutorial: Fix perf tests build issue
This change came from master where Fluid kernels are still used
incorrectly.
* G-API Tutorial: Fixed channels support in Sqrt/Phase fluid kernels
Extended tests to cover this case
* G-API Tutorial: Fix text problems found on team review
[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
