PyTorch dataset wrappers for PHOENIX 2014 & PHOENIX-2014-T sign language datasets.
Project description
PHOENIX Datasets 🐦
Introduction
PHOENIX-2014 and PHOENIX-2014-T are popular large scale German sign language datasets developed by Human Language Technology & Pattern Recognition Group from RWTH Aachen University, Germany. This package provides a PyTorch dataset wrapper for those two datasets to make the building of PyTorch model on these two datasets easier.
Installation
pip install git+https://github.com/enhuiz/phoenix-datasets
Example Usage
from phoenix_datasets import PhoenixVideoTextDataset
from torch.utils.data import DataLoader
dtrain = PhoenixVideoTextDataset(
# your path to this folder, download it from official website first.
root="data/phoenix-2014-multisigner",
split="train",
p_drop=0.5,
random_drop=True,
)
vocab = dtrain.vocab
print("Vocab", vocab)
dl = DataLoader(dtrain, collate_fn=dtrain.collate_fn)
for batch in dl:
video = batch["video"]
text = batch["text"]
# Do per-frame augmentation (e.g. normalization, cropping) here if needed.
# kornia will be a good tool for this
# video = augment(video)
assert len(video) == len(text)
print(len(video))
print(video[0].shape)
print(text[0].shape)
break
Supported Features
- Load the automatic alignments for PHOENIX-2014
- Randomly/evenly frame dropping augmentation
TODOs
- Implement Corpus for PHOENIX-2014-T
- Evaluation Wrappers
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