We provide a simple tool to add masks on face images automatically.
We can use this tool to do data augmentation while training our face recognition models.
Face Image | OP | Mask Image | Out |
---|---|---|---|
+F | |||
+F | |||
+H |
F means FULL while H means HALF.
-
insightface package library
pip install -U insightface
-
insightface model pack
bash> insightface-cli model.download antelope
-
BFM models
Please follow the tutorial of https://github.com/YadiraF/face3d/tree/master/examples/Data/BFM to generate
BFM.mat
andBFM_UV.mat
. Put them into the insightface model pack directory, such as~/.insightface/models/antelope/
-
mask images
some mask images are included in insightface package, such as 'mask_blue', 'mask_white', 'mask_black' and 'mask_green'.
Please refer to make_renderer.py
for detail example.
(1) init renderer:
import insightface
from insightface.app import MaskRenderer
tool = MaskRenderer()
tool.prepare(ctx_id=0, det_size=(128,128)) #use gpu
(2) load face and mask images
from insightface.data import get_image as ins_get_image
image = ins_get_image('Tom_Hanks_54745')
mask_image = "mask_blue"
(3) build necessary params for face image, this can be done in offline.
params = tool.build_params(image)
(4) do mask render, it costs about 10ms
on 224x224 UV size, CPU single thread.
mask_out = tool.render_mask(image, mask_image, params)
(5) do half mask render.
mask_half_out = tool.render_mask(image, mask_image, params, positions=[0.1, 0.5, 0.9, 0.7])