All classes are registered in the scope that corresponds to C++
namespace or exported class.
Example:
`cv::ml::Boost` is exported as `cv.ml.Boost`
`cv::SimpleBlobDetector::Params` is exported as
`cv.SimpleBlobDetector.Params`
For backward compatibility all classes are registered in the global
module with their mangling name containing scope information.
Example:
`cv::ml::Boost` has `cv.ml_Boost` alias to `cv.ml.Boost` type
4.x: submodule or a class scope for exported classes
* feature: submodule or a class scope for exported classes
All classes are registered in the scope that corresponds to C++
namespace or exported class.
Example:
`cv::ml::Boost` is exported as `cv.ml.Boost`
`cv::SimpleBlobDetector::Params` is exported as
`cv.SimpleBlobDetector.Params`
For backward compatibility all classes are registered in the global
module with their mangling name containing scope information.
Example:
`cv::ml::Boost` has `cv.ml_Boost` alias to `cv.ml.Boost` type
* refactor: remove redundant GAPI aliases
* fix: use explicit string literals in CVPY_TYPE macro
* fix: add handling for class aliases
this corrects bug #16592 where a Stream is created at
each GpuMat::load(arr,stream) call
a correct solution would have been to add a default to GpuMat::load
but due to circular dependence between Stream and GpuMat, this is not possible
add test_cuda_upload_download_stream to test_cuda.py
[G-API] Introduce GOpaque and GArray for python
* Introduce GOpaque and GArray for python
* Fix ctor
* Avoid code duplication by using macros
* gapi: move Python-specific files to misc/python
* Fix windows build
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* Implement G-API python bindings
* Fix hdr_parser
* Drop initlization with brackets using regexp
* Handle bracket initilization another way
* Add test for core operations
* Declaration and definition of View constructor now in different files
* Refactor tests
* Remove combine decorator from tests
* Fix comment to review
* Fix test
* Fix comments to review
* Remove GCompilerArgs implementation from python
Co-authored-by: Pinaev <danil.pinaev@intel.com>
Fix implicit conversion from array to scalar in python bindings
* Fix wrong conversion behavior for primitive types
- Introduce ArgTypeInfo namedtuple instead of plain tuple.
If strict conversion parameter for type is set to true, it is
handled like object argument in PyArg_ParseTupleAndKeywords and
converted to concrete type with the appropriate pyopencv_to function
call.
- Remove deadcode and unused variables.
- Fix implicit conversion from numpy array with 1 element to scalar
- Fix narrowing conversion to size_t type.
* Fix wrong conversion behavior for primitive types
- Introduce ArgTypeInfo namedtuple instead of plain tuple.
If strict conversion parameter for type is set to true, it is
handled like object argument in PyArg_ParseTupleAndKeywords and
converted to concrete type with the appropriate pyopencv_to function
call.
- Remove deadcode and unused variables.
- Fix implicit conversion from numpy array with 1 element to scalar
- Fix narrowing conversion to size_t type.·
- Enable tests with wrong conversion behavior
- Restrict passing None as value
- Restrict bool to integer/floating types conversion
* Add PyIntType support for Python 2
* Remove possible narrowing conversion of size_t
* Bindings conversion update
- Remove unused macro
- Add better conversion for types to numpy types descriptors
- Add argument name to fail messages
- NoneType treated as a valid argument. Better handling will be added
as a standalone patch
* Add descriptor specialization for size_t
* Add check for signed to unsigned integer conversion safety
- If signed integer is positive it can be safely converted
to unsigned
- Add check for plain python 2 objects
- Add check for numpy scalars
- Add simple type_traits implementation for better code style
* Resolve type "overflow" false negative in safe casting check
- Move type_traits to separate header
* Add copyright message to type_traits.hpp
* Limit conversion scope for integral numpy types
- Made canBeSafelyCasted specialized only for size_t, so
type_traits header became unused and was removed.
- Added clarification about descriptor pointer
Fix cudacodec python
* Add python bindings to cudacodec.
* Allow args with CV_OUT GpuMat& or CV_OUT cuda::GpuMat& to generate python bindings that allow the argument to be an optional output in the same way as OutputArray.
* Add wrapper flag to indicate that an OutputArray is a GpuMat.
* python: drop CV_GPU, extra checks in test
* Remove "cuda::GpuMat" check rom python parser
* Adding constants to json file
* adding sub-module to constants name
* adding namespace to functions
* adding namespace to classes
* remove namespace from methods
* static methods
* python signatures generation
* python: more fixes for signatures generation
Python names existence can be checked via command:
python -c "import cv2 as cv; print(repr(<py_name>))"
- cv2.UMat implemented - python thin wrapper for UMat
- no implicit copy from GPU to Host done, resulting UMat can be passed to next function without overhead
- cv2.UMat.get() - to fetch data to Host
- new tests covers: ORB, BFMatcher, goodFeaturesToTrack, calcOpticalFlowPyrLK
Alexander Alekhin
Vadim Levin
David Geldreich
Anatoliy Talamanov
Vadim Pisarevsky
cudawarped
cudawarped
Alexander Alekhin
berak
luz.paz
Maksim Shabunin
Diego Barrios Romero
Hamdi Sahloul
Cartucho
Lewis B
lewisjb
Vitaliy Lyudvichenko
Alexander Alekhin
Nikolay Polyarniy