Known limitations and important notes
As of September 2020
- No TensorFlow integration
- Currently only supports ImageNet
- Unknown effect on model accuracy of transcoding from various JPEG formats to
H.265
- Current transcoding filters failed on 81 images of the ImageNet 2012
dataset forcing them to be excluded. More information can be found in the
dataset’s README.
- Current transcoding filters required 111 images of the ImageNet 2012
dataset to first be transcoded to PNG prior to the final H.265 format. More
information can be found in the dataset’s README.
- High resolution images stored in the
bzna_input track of the input samples are currently
not available through the
Dataloader
. Their varying size prevent
them from being decoded using a single hardware decoder configuration. The
selected solution is to represent the images in the HEIF format which will be
completed in future development.
- It is currently not possible to compose transformations like you can with
torchvision.transforms.Compose
but
SimilarityTransform
should cover most
of the necessary images transformations.
SimilarityTransform
and
RandomResizedCrop
slightly differ from
the behaviour of torchvision.transforms.RandomResizedCrop
where, instead
of falling back to a center crop when the random crop area doesn’t fit after
10 tries, SimilarityTransform
will still perform the crop and only
center it on the dimension not fitting. Due to the encoding methods used in
Benzina, this will usually result in an image with a black top border and a
smeared bottom border or a black left border and a smeared right border if
the crop area did not fit vertically or horizontally respectively.