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
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
* 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
I had to make this modification locally to get opencv to build with python 2.6. Python 2.6 requires indices in the format string (the `0` I added). This requirement was relaxed in 2.7, so what used to be there would be working for people who could upgrade. I don't think the change has any negative consequences for future python versions, but I'm no expert.
- all parsed headers are included into "cv2.cpp" with "pyopencv_generated_include.h"
- types starting with "Ptr_" converted to "Ptr<...>" form (avoids many typedefs in "cv2.cpp")
