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Merge pull request #27228 from utibenkei:fix_java_enum_wrapper

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Explicitly specify enum type scopes to improve Java wrapper generation #27228 

Changed DataLayout and ImagePaddingMode to dnn::DataLayout and dnn::ImagePaddingMode to explicitly specify their scopes. This allows gen_java.py to correctly register  disc_type, preventing constructors and methods using these enum types from being skipped during Java wrapper generation.

Similarly updated QRCodeEncoder::CorrectionLevel and QRCodeEncoder::EncodeMode with explicit scope declarations.

Also added a new Java test class `DnnBlobFromImageWithParamsTest` based on: https://github.com/opencv/opencv/blob/4.x/modules/dnn/test/test_misc.cpp#L133-L243

Related issues
#23753 

### 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
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
utibenkei
2025-04-22 02:51:38 +09:00
committed by GitHub
parent a08b1b6566
commit 97f73ba0b5
3 changed files with 140 additions and 6 deletions
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modules/dnn/include/opencv2/dnn/dnn.hpp
+4 -4
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@@ -1219,16 +1219,16 @@ CV__DNN_INLINE_NS_BEGIN
{
CV_WRAP Image2BlobParams();
CV_WRAP Image2BlobParams(const Scalar& scalefactor, const Size& size = Size(), const Scalar& mean = Scalar(),
bool swapRB = false, int ddepth = CV_32F, DataLayout datalayout = DNN_LAYOUT_NCHW,
ImagePaddingMode mode = DNN_PMODE_NULL, Scalar borderValue = 0.0);
bool swapRB = false, int ddepth = CV_32F, dnn::DataLayout datalayout = DNN_LAYOUT_NCHW,
ImagePaddingMode mode = dnn::DNN_PMODE_NULL, Scalar borderValue = 0.0);
CV_PROP_RW Scalar scalefactor; //!< scalefactor multiplier for input image values.
CV_PROP_RW Size size; //!< Spatial size for output image.
CV_PROP_RW Scalar mean; //!< Scalar with mean values which are subtracted from channels.
CV_PROP_RW bool swapRB; //!< Flag which indicates that swap first and last channels
CV_PROP_RW int ddepth; //!< Depth of output blob. Choose CV_32F or CV_8U.
CV_PROP_RW DataLayout datalayout; //!< Order of output dimensions. Choose DNN_LAYOUT_NCHW or DNN_LAYOUT_NHWC.
CV_PROP_RW ImagePaddingMode paddingmode; //!< Image padding mode. @see ImagePaddingMode.
CV_PROP_RW dnn::DataLayout datalayout; //!< Order of output dimensions. Choose DNN_LAYOUT_NCHW or DNN_LAYOUT_NHWC.
CV_PROP_RW dnn::ImagePaddingMode paddingmode; //!< Image padding mode. @see ImagePaddingMode.
CV_PROP_RW Scalar borderValue; //!< Value used in padding mode for padding.
/** @brief Get rectangle coordinates in original image system from rectangle in blob coordinates.