https://bugs.kde.org/show_bug.cgi?id=426309
--- Comment #7 from Minh Nghia Duong <minhnghiaduong...@gmail.com> --- (In reply to Rob D from comment #6) Hi Rob, I agree with your concern. Normally, for the current CNN models of object detection, the pre-processing and post-processing are nearly the same between different neural network. The only significant differences are the backend type for network importation and the input size of the network. The input size seems easy to configure in user interface but the backend type supported by OpenCV is limited and therefore needs better specialization to avoid errors. About YOLOv4 and v5, it's already out and I tried it on digikam. It requires the latest version of OpenCV and doesn't seem to make a significant change in performance on CPU. Might be it would work better on GPU but the only GPU driver supported by OpenCV is CUDA. Can you describe to me more about the workflow of loading a customized neural network that you have in mind? Nghia -- You are receiving this mail because: You are watching all bug changes.
