https://bugs.kde.org/show_bug.cgi?id=444160
--- Comment #28 from Michael Miller <michael_mil...@msn.com> --- Hi Jonathan, Yes, many, many things have changed. First, we've introduced 2 new models in 8.5.0. YuNet is now the preferred face detection model. It is much faster than YOLO and SSD. Second, we have a new face feature extraction model called SFace. SFace is faster and more accurate than OpenFace for extracting the face vectors from the thumbnail (which should be generated by YuNet). Next, we've significantly modified the KNN classifier to reduce both false positives and false negatives. While the new classifier is slightly slower, the performance enhancements of the detector and extractor make the overall process much faster and more accurate. Finally, there are several other minor changes in the face pipeline to improve performance. I've been working on the models every day for several weeks now, and updates are introduced in the daily builds. I've been tuning the models against the well-known Labeled Faces in the Wild dataset. I have a good baseline to use for measuring my results. Results are better every day. https://vis-www.cs.umass.edu/lfw/ With YuNet, SFace, and the updated classifier, I'm getting detection accuracy scores of about 91% to 97%, and recognition scores of 92% to 96%. The scores will vary based on the settings, which are driven by your tolerance for false-positives and false-negatives. Overall, the new models are showing much better t-SNE clusters when data dimensionality is reduced so it can be plotted in 2-dimensional space. This is a significant improvement over the aging SDD or YOLO detection models and OpenFace feature extractor with pseudo KDTree classifier where there was marginal clustering at best. The most important pieces are: 1. you are using YuNet for face detection 2. you are using SFace for recognition 3. You have re-trained the face DB after changing those settings Cheers, Mike -- You are receiving this mail because: You are watching all bug changes.
