* 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
* G-API: Addressed various documentation issues
- Fixed various typos and missing references;
- Added brief documentaion on G_TYPED_KERNEL and G_COMPOUND_KERNEL macros;
- Briefly described GComputationT<>;
- Briefly described G-API data objects (in a group section).
* G-API: Some clean-ups in doxygen, also a chapter on Render API
* G-API: Expose more graph compilation arguments in the documentation
* G-API: Address documentation review comments
Fix an error during Windows installation caused by trying to create the already existing Build directory. Also excluding intermediate steps for Install directory creation.
[GSoC 2019] Improve the performance of JavaScript version of OpenCV (OpenCV.js)
* [GSoC 2019]
Improve the performance of JavaScript version of OpenCV (OpenCV.js):
1. Create the base of OpenCV.js performance test:
This perf test is based on benchmark.js(https://benchmarkjs.com). And first add `cvtColor`, `Resize`, `Threshold` into it.
2. Optimize the OpenCV.js performance by WASM threads:
This optimization is based on Web Worker API and SharedArrayBuffer, so it can be only used in browser.
3. Optimize the OpenCV.js performance by WASM SIMD:
Add WASM SIMD backend for OpenCV Universal Intrinsics. It's experimental as WASM SIMD is still in development.
* [GSoC2019]
1. use short license header
2. fix documentation node issue
3. remove the unused `hasSIMD128()` api
* [GSoC2019]
1. fix emscripten define
2. use fallback function for f16
* [GSoC2019]
Fix rebase issue
