https://bugs.kde.org/show_bug.cgi?id=508606
--- Comment #9 from [email protected] --- Maik, I ask to Mistral AI to review my code and to take a look to the demo video. Yes Mistral AI can analyze code online in git repository and it can judge the contents of a video. Incredible no? Now the Mistral AI response: // ----------------------------------------------------------- Congratulations on Your First Working Version! 🎉 Your demo video looks very promising! The core functionality is already in place, and the integration with digiKam’s editor is smooth. Below are some observations and suggestions to refine the plugin and address visible bugs. 1. Strengths ✅ Core functionality works: Segmentation and background blur are functional. ✅ Seamless integration: The plugin works well with digiKam’s rectangular selection tool and UI. ✅ Real-time preview: A great feature for user experience. 2. Bugs and Areas for Improvement A. Issues Visible in the Demo Fuzzy Edges Around the Subject Likely cause: GrabCut can leave artifacts around fine details (e.g., hair, complex edges). Solutions: Add an option to refine edges (e.g., morphological operations to smooth the mask). Allow manual corrections with a brush tool (like Photoshop’s "Refine Edge"). Uniform Blur Likely cause: Gaussian blur is applied uniformly, which can look unnatural. Solutions: Implement progressive blur (stronger blur farther from the subject) to mimic depth of field. Add a parameter to control the blur transition. Performance Likely cause: GrabCut can be slow for large images. Solutions: Downscale the image during preview (e.g., work at 50% resolution). Use cv::UMat to accelerate processing with OpenCL (if available). B. Code Improvements Image Format Handling Ensure robust conversion between DImg and cv::Mat for all formats (grayscale, RGBA, etc.). Example check: if (input.empty()) { qWarning() << "BackgroundBlur: Input image is empty!"; output = input.clone(); return; } Error Handling Add debug logs for cases where GrabCut fails or the selection is invalid. Example: if (width <= 0 || height <= 0) { qWarning() << "BackgroundBlur: Invalid selection area. Using full image."; roi = cv::Rect(0, 0, input.cols, input.rows); } User Parameters Add options to: Fine-tune blur intensity (already present, but could be more precise). Adjust the blur kernel size (cv::Size in GaussianBlur). Choose between Gaussian blur and motion blur for dynamic effects. C. User Experience Visual Feedback Show a semi-transparent overlay or outline of the selected area before applying blur. Display a warning if the selection is too small or invalid. Undo/Redo Support Ensure the plugin works seamlessly with digiKam’s undo/redo history. Documentation Add tooltips or a short description in the UI to guide users. 3. Next Steps Test Edge Cases Large images (e.g., 24MP+). Subjects with complex edges (hair, transparent objects). Selections near image borders. Compare with Other Tools Test your plugin against results from Photoshop/GIMP to benchmark quality. Optimization Profile the code to identify bottlenecks (e.g., using perf or Qt Creator). If GrabCut is too slow, consider adding a lighter segmentation model (e.g., MediaPipe) as an alternative. 4. Example Code for Progressive Blur To experiment with more natural blur, here’s how to implement distance-based blur: // After obtaining the "mask" from GrabCut cv::Mat distanceMap; cv::distanceTransform(~mask, distanceMap, cv::DIST_L2, cv::DIST_MASK_5); // Normalize distance for progressive blur cv::normalize(distanceMap, distanceMap, 0, 1, cv::NORM_MINMAX); cv::Mat blurred; cv::GaussianBlur(inputBGR, blurred, cv::Size(0, 0), blurIntensity); // Blend with variable blur cv::Mat result; inputBGR.copyTo(result); for (int y = 0; y < input.rows; y++) { for (int x = 0; x < input.cols; x++) { float alpha = distanceMap.at<float>(y, x); result.at<cv::Vec3b>(y, x) = alpha * blurred.at<cv::Vec3b>(y, x) + (1 - alpha) * inputBGR.at<cv::Vec3b>(y, x); } } 5. Priorities for Further Development Fix Critical Bugs First: Refine subject edges. Improve blur transitions. Add Advanced Features: Progressive blur. Manual correction tools. Community Testing: Share a beta version with digiKam users for feedback. 6. Keep Up the Great Work! You’ve already achieved the core goal: a functional plugin integrated into digiKam! The remaining tasks are optimizations and polish. If you’d like, I can help implement any of the suggestions above (e.g., progressive blur or manual refinement tools). Question for you: Would you like to focus first on edge refinement, or explore other features (like progressive blur)? 😊 Note: This is a fantastic start, and the digiKam community will surely appreciate your contributions! Let me know how I can assist further. // ----------------------------------------------------------- Maik, i recommend to give a try to Mistral AI. Take a free account to gain all features without limitations (https://mistral.ai/). I use it through the new Firfox left sidebar dedicated to AI chat usage... -- You are receiving this mail because: You are watching all bug changes.
