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:

• OpenVINO Backend in DNN: We’re enhancing the OpenVINO backend in the Deep Neural Network (DNN) module to support integers and OpenCL acceleration. These improvements will significantly boost performance and expand the capabilities of OpenCV in various applications.
• Charuco Development: Our team is actively working on Charuco, a hybrid marker composed of a checkerboard and ArUco markers, to improve its functionality and usability in computer vision tasks.
• Circles Detector Enhancement: We’re refining the circles detector algorithm to improve accuracy and efficiency in detecting circular shapes, a fundamental task in many computer vision applications.
• 3D Module Enhancements: We’re adding texture support and visualization capabilities to the 3D module, empowering users to create more realistic and immersive 3D reconstructions and visualizations.
• PR Reviews and Merges: Several PRs have been reviewed and merged, including the addition of FaceDetectorYN JS API.
• OpenCL GEMM Kernel Testing: We’ve completed testing of the OpenCL GEMM kernel, ensuring its reliability and performance in matrix multiplication tasks, a critical operation in many computer vision algorithms.
• Apple Accelerate Building Fixes: Building warnings with the new Apple Accelerate framework have been addressed.
• Caffe Importer Removal: We’re continuing the removal of the Caffe importer and associated models, streamlining the codebase and focusing on more efficient and modern alternatives.
• Sample Cleanup Progress: We’ve made progress on sample cleanup, with one PR merged last week. This ongoing effort aims to improve the quality and relevance of sample code for users’ reference and learning.
• HAL Discussions: We’re working on the new Hardware Abstraction Layer (HAL) for OpenCV 5.x, addressing questions and expectations for future support and collaboration.

How to Contribute to OpenCV:

Interested in contributing to OpenCV? Follow these steps:

1. Check out the Contribution Guidelines on the OpenCV Wiki for detailed instructions on how to contribute code, report issues, and participate in discussions.
2. Familiarize yourself with the OpenCV development process, including coding standards and conventions, version control practices, and testing procedures.
3. 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.

Support OpenCV:

If you’d like to support OpenCV financially, consider purchasing a shirt or donating directly at OpenCV Support. Your contribution helps sustain and advance the development of OpenCV, ensuring it remains a powerful and accessible tool for the computer vision community.