This repository is intended as a faster drop-in replacement for Pytorch's Torchvision augmentations. This repo uses OpenCV for fast image augmentation for PyTorch computer vision pipelines. I wrote this code because the Pillow-based Torchvision transforms was starving my GPU due to slow image augmentation.
num_workers >0in a pytorch
DataLoader. I haven't run into this issue yet.
opencv_transforms is now a pip package! Simply use
pip install opencv_transforms
Breaking change! Please note the import syntax!
from opencv_transforms import transforms
import numpy as np image = np.random.randint(low=0, high=255, size=(1024, 2048, 3)) resize = transforms.Resize(size=(256,256)) image = resize(image)
Should be 1.5 to 10 times faster than PIL. See benchmarks
The changes start to add up when you compose multiple transformations together.
RandomAffineactually do something