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python: attempts to fix 3d mat parsing problem for dnn #25810 Fixes https://github.com/opencv/opencv/issues/25762 https://github.com/opencv/opencv/issues/23242 Relates https://github.com/opencv/opencv/issues/25763 https://github.com/opencv/opencv/issues/19091 Although `cv.Mat` has already been introduced to workaround this problem, people do not know it and it kind of leads to confusion with `numpy.array`. This patch adds a "switch" to turn off the auto multichannel feature when the API is from cv::dnn::Net (more specifically, `setInput`) and the parameter is of type `Mat`. This patch only leads to changes of three places in `pyopencv_generated_types_content.h`: ```.diff static PyObject* pyopencv_cv_dnn_dnn_Net_setInput(PyObject* self, PyObject* py_args, PyObject* kw) { ... - pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) && + pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) && ... } // I guess we also need to change this as one-channel blob is expected for param static PyObject* pyopencv_cv_dnn_dnn_Net_setParam(PyObject* self, PyObject* py_args, PyObject* kw) { ... - pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) ) + pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) ) ... - pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) ) + pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) ) ... } ``` Others are unchanged, e.g. `dnn_SegmentationModel` and stuff like that. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
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