https://bugs.kde.org/show_bug.cgi?id=508606
--- Comment #1 from [email protected] --- Subject: Proposal for Implementing AI-Based Background Blur Tool in digiKam Image Editor Summary: This feature request aims to add a new tool to the digiKam image editor that allows users to select a foreground subject and apply a blur effect to the background, simulating the depth-of-field effect found in modern smartphones (e.g., iPhone 15 Portrait Mode). The proposed solution uses OpenCV's GrabCut algorithm for segmentation and Gaussian blur for the background, leveraging digiKam's existing rectangular selection tool and DImg/OpenCV integration helpers. 1. Context and Goals User Need: Select a subject (person/object) in a photo. Blur the background while keeping the subject sharp. Use the existing rectangular selection tool in the editor for simplicity. Technical Approach: Use GrabCut (OpenCV) for foreground/background segmentation. Apply Gaussian blur to the background. Integrate with digiKam's DImg and QtOpenCVImg helpers for seamless conversion between DImg and cv::Mat. 2. Technical Implementation Steps A. Plugin Structure Create the following files in digikam/editor/plugins/backgroundblur/: backgroundblurplugin.h/cppMain plugin class (inherits from DPluginEditor).backgroundblurtool.h/cppCore logic: GrabCut segmentation + background blur.ui/backgroundblurwidget.uiUser interface (slider for blur intensity, "Apply" button).CMakeLists.txtBuild configuration (link to OpenCV, Qt). B. Key Code Snippets 1. Retrieve Rectangular Selection and Convert DImg to cv::Mat: // In backgroundblurtool.cpp void BackgroundBlurTool::preparePreview(Digikam::ImageIface* iface, int blurIntensity) { QRect selection = iface->selectionRect(); Digikam::DImg original = iface->original(); cv::Mat input = Digikam::QtOpenCVImg::image2Mat(original); cv::Mat output; applyBackgroundBlur(input, output, selection, blurIntensity); Digikam::DImg result = Digikam::QtOpenCVImg::mat2Image(output).toImage(); iface->setImage(result); } 2. Apply GrabCut and Background Blur: void BackgroundBlurTool::applyBackgroundBlur(const cv::Mat& input, cv::Mat& output, const QRect& selection, int blurIntensity) { cv::Rect roi(selection.x(), selection.y(), selection.width(), selection.height()); cv::Mat mask(input.rows, input.cols, CV_8UC1, cv::GC_PR_BGD); mask(roi) = cv::GC_PR_FGD; cv::Mat bgModel, fgModel; cv::grabCut(input, mask, roi, bgModel, fgModel, 5, cv::GC_INIT_WITH_RECT); cv::compare(mask, cv::GC_PR_FGD, mask, cv::CMP_EQ); cv::Mat blurred; cv::GaussianBlur(input, blurred, cv::Size(0, 0), blurIntensity); input.copyTo(output, mask); blurred.copyTo(output, ~mask); } 3. User Interface (ui/backgroundblurwidget.ui): <ui version="4.0"> <class>BackgroundBlurWidget</class> <widget class="QWidget"> <layout class="QVBoxLayout"> <item><widget class="QLabel" text="Blur Intensity:"/></item> <item><widget class="QSlider" name="blurSlider" minimum="1" maximum="50" value="15"/></item> <item><widget class="QPushButton" name="applyButton" text="Apply"/></item> </layout> </widget> </ui> 4. CMake Integration: find_package(OpenCV REQUIRED) find_package(Qt5 REQUIRED COMPONENTS Widgets) add_library(backgroundblurplugin MODULE backgroundblurplugin.cpp backgroundblurtool.cpp ) target_link_libraries(backgroundblurplugin Qt5::Widgets ${OpenCV_LIBS} ) 3. Expected Deliverables Functional Plugin: Integrates with digiKam's editor and selection tools. Applies background blur using GrabCut + Gaussian blur. Includes a user-friendly interface for adjusting blur intensity. Code Quality: Follows digiKam's coding standards. Includes comments and documentation for key functions. Handles edge cases (e.g., invalid selections, empty images). Testing: Test with various images (portraits, objects, complex backgrounds). Verify performance with high-resolution images. Ensure no crashes or visual artifacts. 4. Assignment Notes for Students/Contributors Prerequisites: Familiarity with C++, Qt, and OpenCV. Basic understanding of digiKam's plugin architecture. Access to a development environment with digiKam's build dependencies. Resources: OpenCV GrabCut Documentation digiKam Developer Guide QtOpenCVImg Helpers Mentorship: Assign a mentor from the digiKam team to review progress and provide guidance. Encourage incremental commits and code reviews via digiKam's Phabricator. 5. Timeline (Suggested) Set up development environment1–2 daysCreate plugin skeleton and UI2–3 daysImplement GrabCut + blur logic3–5 daysIntegrate with digiKam editor2–3 daysTesting and bug fixing2–3 daysDocumentation and final review1–2 days Next Steps: Assign this task to a student/contributor. Provide access to the digiKam repository and relevant documentation. Schedule regular check-ins to monitor progress. Note: This feature is a great opportunity for students to contribute to a widely used open-source project while learning about image processing, Qt, and OpenCV. The digiKam team is available to support and guide contributors throughout the process. -- You are receiving this mail because: You are watching all bug changes.
