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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 >0
in 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
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.
resample
flag on RandomRotation
, RandomAffine
actually do somethingFAQs
A drop-in replacement for Torchvision Transforms using OpenCV
We found that opencv-transforms demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket now supports Scala and Kotlin, bringing AI-powered threat detection to JVM projects with easy manifest generation and fast, accurate scans.
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