DFACE uses the YOLOV5 neural network object detection framework to run face detection in a web browser so photos never leave a user’s device. It can process up to 1,000 faces per image at down to 10x10 pixels per face with varying effects (color fill, blur, or emoji), and supports batch-processing multiple images. Research and development of DFACE (as part of the VFRAME project) received support through the NGI0 PET Fund, a fund established by NLnet with financial support from the European Commission’s Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 825310.