Datasets¶
gluonfr.data
provides input pipeline for training and validation, all
datasets is aligned by mtcnn and cropped to (112, 112) by DeepInsight,
they converted images to train.rec
, train.idx
and
val_data.bin
files, please check out
[insightface/Dataset-Zoo]
for more information. In examples/dali_utils.py
, there is a simple
example of Nvidia-DALI. It is worth trying when data augmentation with
cpu can not satisfy the speed of gpu training,
The files should be prepared like:
face/
emore/
train.rec
train.idx
property
ms1m/
train.rec
train.idx
property
lfw.bin
agedb_30.bin
...
vgg2_fp.bin
We use ~/.mxnet/datasets
as default dataset root to match mxnet setting.
References¶
- CFP_fp, CFP_ff
- “Frontal to Profile Face Verification in the Wild”