[G-API] Add support for more types serialization
* Support more types
* Add std::string support
* Fix GOpaque and gin interaction
* Fix tests on kind
* Make map serialization support templates and add tests on kind
Update G-API slides to OpenCV 4.4
* G-API: Updated slides to v4.4 (+ sample)
* Slight formatting changes + Python API page
* Some more updates to slides:
- Added more info on 4.2 and 4.4 versions
- Added explanation on Operations and their functional wrappers
* G-API: Make GFrame a new (distinct) G-type, not an alias to GMat
- The underlying host type is still cv::Mat, a new cv::MediaFrame
type is to be added as a separate PR
* Fix warnings and review comments
- Somewhow there was a switch() without a default: clause in Fluid
[G-API]: Add Fluid bitwise operations implementation for (GMat, GScalar)
* Added Fluid `bitwise` with `Scalar` + acc.tests
- simple loop implementation for Fluid used (no `hal`);
- `Scalar` is casted to `int` in the beginning
- tests just modified to work with `Scalar`
- expected output in operators' tests fixed (operators can't change Mat's depth)
- `float` `Scalar` `RNG` added, `RNG` reworked (`time` is used now), initialization of test fixtures reworked
- if input or output is `float` Scalar is initialized by `float`
- some problems with Fluid/OCV floating-point comparison difference stashed by `AbsSimilarPoints()` usage, FIXME added
- divide-by-zero is now fixed differently and everywhere
* - Added perf_tests for bitwise_Scalar operations
- due to errors of Fluid floating-point comparison operations, added support of different validation in Cmp perf_tests; added FIXME
- reworked integral initialization of Scalar
* Addressing comments
- NULL -> nullptr
- Scalar convertion moved to the function
- avoid -> avoiding
* Addressing comments
* CV_assert -> GAPI_assert
* Addressed DM comments
- refactored convertScalarForBitwise()
- removed unnecessary braces for switch
* Changed the operators tests
- switch via `enum` implemented
- infrastructure for that refactored
[G-API]: Add four kernels to parse NN outputs & provide information in Streaming scenarios
* Kernels from GL "blue" branch, acc and perf tests
* Code cleanup
* Output fix
* Comment fix
* Added new file for parsers, stylistic corrections
* Added end line
* Namespace fix
* Code cleanup
* nnparsers.hpp moved to gapi/infer/, nnparsers -> parsers
* Removed cv:: from parsers.hpp
[G-API]: Add GArray initialization support
* Added GArray initialization (CONST_VALUE, GScalar analog) and test for this
* Whitespaces
* And one more space
* Trailing whitespace
* Test name changed. Build with magic commands.
* GArray works with rvalue initialization
* Code cleanup
* Ternary operator in the initialization list.
Fix loading of ONNX models with Resize operation with Opset 11 for newer versions of Pytorch
* Add reproducer for Resize operation from newer versions of Pytorch
* Fix loading of scales parameter for Resize layer
* Change check type for better diagnostic messages