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Lightly download for Windows

Free download Lightly Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named Lightly whose latest release can be downloaded as CyclicCosineScheduler.zip. It can be run online in the free hosting provider OnWorks for workstations.

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Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS

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Lightly


DESCRIPTION

A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions.



Features

  • Modular framework which exposes low-level building blocks such as loss functions
  • Support for multi-gpu training using PyTorch Lightning
  • Easy to use and written in a PyTorch like style
  • Supports custom backbone models for self-supervised pre-training
  • You can find sample code for all the supported models
  • We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project


Programming Language

Python


Categories

Libraries, Machine Learning, Deep Learning Frameworks, Data Labeling

This is an application that can also be fetched from https://sourceforge.net/projects/lightly.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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