Hello, Community! This post is a summary of development on OpenCV 5 in the last week. You can always find the most up-to-date information on the OpenCV 5 Work Board. Many thanks to Jia Wu for her excellent notes!
Latest Developments from the OpenCV Core Team:
- Unified Samples for Edge Detection: Improved and unified samples for edge detection in PR #25515, enhancing the user experience and consistency across different edge detection algorithms. These submissions are awaiting review.
- DNN Image Classification Samples: PR #25519 introduces improved samples for DNN image classification, streamlining the process and providing users with more efficient and informative examples. These submissions are also awaiting review.
- Combined C++ Samples Cleanup: PR #25252 proposes a combined cleanup of C++ samples, addressing issues and enhancing clarity and consistency. This PR is awaiting review, consolidating efforts to improve the quality of sample code.
- Exploring Semantic Segmentation with U-2-Net: For semantic segmentation tasks, we’re considering the usage of U-2-Net, an effective and efficient model for producing high-quality segmentation masks.
- Continued Work on G-API: Our efforts on G-API continue as we strive to enhance its capabilities and performance.
- Advancements in the New Inference Engine: We’re making progress on the new inference engine, with a focus on improving the ONNX parser for seamless integration with OpenCV.
- DNN Support Enhancements: We’re enhancing DNN support with improvements such as 0D/1D support and OpenVINO backend integration. Next, we plan to work on additional features like bool layers and logical layers to further enhance the functionality and flexibility of the DNN module.
- HAL Improvements: We’re making strides in improving the Hardware Abstraction Layer (HAL), optimizing performance and efficiency across different hardware architectures.
- OpenCV Numpy Integration: Integration with OpenCV Numpy is ongoing, providing users with enhanced capabilities for data manipulation and analysis.
- Documentation Enhancements: We’re actively working on improving documentation, ensuring it remains comprehensive, up-to-date, and accessible to users of all levels.
- fp16 Intrinsics PR Merged: A PR for fp16 intrinsics has been merged, enhancing performance and efficiency in certain operations, particularly on hardware that supports half-precision floating-point arithmetic.
- MacOS Building Warning PR Awaiting Review: A PR addressing building warnings on MacOS is awaiting review, ensuring smooth integration and compatibility with MacOS platforms.
- GoTurn Model Deletion: The GoTurn model has been deleted, streamlining the model zoo and focusing resources on more relevant and impactful models.
- Experiments with ann-benchmark Framework: We’ve conducted experiments with the ann-benchmark framework.
- Creation of Segmentation Sample: We’re creating a segmentation sample to showcase advanced segmentation techniques and provide users with practical examples for segmentation tasks.
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- Check out the Contribution Guidelines on the OpenCV Wiki for detailed instructions on how to contribute code, report issues, and participate in discussions.
- Familiarize yourself with the OpenCV development process, including coding standards and conventions, version control practices, and testing procedures.
- Join the vibrant OpenCV community on GitHub and start collaborating with developers from around the world. Your contributions, no matter how big or small, play a crucial role in shaping the future of OpenCV.
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Thanks for reading this OpenCV 5 update, we’ll be back with more soon.
The post OpenCV 5 Progress Update (May 9, 2024) appeared first on OpenCV.