Download and compile Matconvnet as a submodule. Make sure it passes all test cases after compilation. Feel free to refer to my compilation code as in compile.m
.
We provide a demo script to run our detector on an input image and visualize the detections, as in minimal_demo.m
. By default, this script takes images under demo/data and outputs detections to demo/visual.
Download WIDER FACE dataset and place its data and annotations under data/widerface/, following such structure:
- data/widerface/wider_face_train.mat (annotations for training set)
- data/widerface/WIDER_train (images for training set)
Coming soon.