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Throwing a 'what' to everything machine leanring

Home Page: https://basicml.com

License: MIT License

HTML 56.82% Ruby 2.80% Shell 0.99% Makefile 0.19% Python 2.80% JavaScript 2.16% SCSS 34.25%
basics machine-learning

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performance/2019/05/02/pytorch-augmentation-with-libjpeg-turbo

Squeezing image loading performance using libjpeg in Pytorch | Basic Machine Learning

Sometimes in your project you seek cheap thrills out of changing couple of lines of code. This is what happened when I came across the libjpeg-turbo project. The turbo version of libjpeg boasts to be 2-6x faster in performing image processing operations. Performance is what everyone wants, right?

https://www.basicml.com/performance/2019/05/02/pytorch-augmentation-with-libjpeg-turbo.html

performance/2019/05/18/efficiently-storing-and-retrieving-image-datasets

Efficiently processing large image datasets in Python | Basic Machine Learning

I have been working on Computer Vision projects for some time now and moving from NLP domain the first thing I realized was that image datasets are yuge! I typically process 500GiB to 1TB of data at a time while training deep learning models. Out of the box, I rely on using ImageFolder class of Pytorch but disk reads are so slow (innit?). I was reading through open source projects to see how people efficiently process large image data sets like Places. That’s how I stumbled into LMDB store which is the focus of this post. The tagline on the official project page justifies the benefits of using LMDB: -

https://www.basicml.com/performance/2019/05/18/efficiently-storing-and-retrieving-image-datasets.html

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