Tutorial for parallel_for_ and Universal Intrinsic (GSoC '21)
* New parallel_for tutorial
* Universal Intrinsics Draft Tutorial
* Added draft of universal intrinsic tutorial
* * Added final markdown for parallel_for_new
* Added first half of universal intrinsic tutorial
* Fixed warnings in documentation and sample code for parallel_for_new
tutorial
* Restored original parallel_for_ tutorial and table_of_content_core
* Minor changes
* Added demonstration of 1-D vectorized convolution
* * Added 2-D convolution implementation and tutorial
* Minor changes in vectorized implementation of 1-D and 2-D convolution
* Minor changes to univ_intrin tutorial. Added new tutorials to the table of contents
* Minor changes
* Removed variable sized array initializations
* Fixed conversion warnings
* Added doxygen references, minor fixes
* Added jpg image for parallel_for_ doc
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
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 :)
