https://bugs.kde.org/show_bug.cgi?id=508292
--- Comment #4 from [email protected] --- This is the response of Mistral AI about to atch the current HealingClone image editor tool to use the OpenCV::inpainting() and drop automatically an area from an image: // -------------------------------------------- Here’s a concise and clear translation of my last response for your Bugzilla entry, focusing on the technical integration of OpenCV-based inpainting as a plugin enhancement for digiKam: Proposal: Add OpenCV Inpainting as an Option to the HealingClone Plugin Context The existing HealingClone plugin in digiKam allows users to remove objects by cloning pixels from a source area. While functional, this method requires significant user interaction. This proposal suggests adding an OpenCV-based inpainting option to the plugin, enabling users to remove objects with a single mask selection, similar to the iPhone’s "Remove Object" feature. Implementation Plan 1. Add a UI Option Add a checkbox or radio button in the plugin’s UI (e.g., healingcloneui.ui) to toggle between: Cloning Mode (current behavior). Inpainting Mode (new OpenCV-based option). Example UI addition: <widget class="QCheckBox" name="useInpaintingCheckBox"> <property name="text"> <string>Use Inpainting (OpenCV)</string> </property> </widget> 2. Modify the Plugin Logic In healingclone.h, add a boolean flag: private: bool m_useInpainting; // Default: false (cloning mode) In the plugin’s slotApply (or equivalent), add a conditional branch: void HealingCloneTool::slotApply() { if (m_useInpainting) { applyInpainting(); } else { // Existing cloning logic } } 3. Implement applyInpainting Add this method to healingclone.cpp: #include <opencv2/photo.hpp> void HealingCloneTool::applyInpainting() { // Get the current image and mask (already managed by the plugin) QImage image = m_originalImage; QImage mask = m_maskImage; // Binary mask (0=keep, 255=remove) // Convert QImage to cv::Mat cv::Mat cvImage(image.height(), image.width(), CV_8UC3, (void*)image.bits(), image.bytesPerLine()); cv::Mat cvMask(mask.height(), mask.width(), CV_8UC1, (void*)mask.bits(), mask.bytesPerLine()); // Apply inpainting cv::Mat result; cv::inpaint(cvImage, cvMask, result, 3, cv::INPAINT_TELEA); // Radius=3, TELEA algorithm // Convert cv::Mat back to QImage QImage resultImage(result.data, result.cols, result.rows, result.step, QImage::Format_RGB888); m_previewImage = resultImage.rgbSwapped(); // Update preview // Emit the result emit signalImageReady(m_previewImage); } 4. Ensure Mask Compatibility Verify that m_maskImage is binary (0 or 255). If not, binarize it: for (int y = 0; y < mask.height(); ++y) { uchar* line = mask.scanLine(y); for (int x = 0; x < mask.width(); ++x) { line[x] = (line[x] > 0) ? 255 : 0; } } 5. Update CMakeLists.txt Ensure OpenCV is linked: find_package(OpenCV REQUIRED) target_link_libraries(dplugin_healingclone PRIVATE OpenCV::OpenCV) 6. Connect the UI Option In the plugin’s constructor, connect the checkbox to the flag: connect(ui->useInpaintingCheckBox, &QCheckBox::toggled, this, &HealingCloneTool::setUseInpainting); 7. Add a Slot for the Toggle In healingclone.cpp: void HealingCloneTool::setUseInpainting(bool enable) { m_useInpainting = enable; } User Workflow Open the HealingClone plugin. Check "Use Inpainting (OpenCV)". Draw a mask over the object to remove (as usual). Click "Apply": The object is removed using OpenCV inpainting. Advantages Reuses existing code: No need to modify the editor or mask management. Simple UI integration: Users can switch between cloning and inpainting. Performance: OpenCV’s inpainting is fast and requires no manual pixel selection. Considerations Quality: OpenCV inpainting is less advanced than AI-based tools but far simpler than manual cloning. Undo/Redo: Already handled by the plugin. Large images: For very high-resolution images, consider downsampling during preview. Next Steps Locate the UI file (healingcloneui.ui) and add the checkbox. Implement applyInpainting and test with sample images. Adjust the inpainting radius (e.g., 3–10) for optimal results. // ---------------------------------------------------- Gilles Caulier -- You are receiving this mail because: You are watching all bug changes.
