FrancescoSaverioZuppichini/ResNet
Clean, scalable and easy to use ResNet implementation in Pytorch
This project offers a clear and organized implementation of the ResNet deep learning model in PyTorch. It provides the building blocks for creating image classification systems that can process visual data like photos or scans and output categorized results. Scientists or machine learning engineers working on computer vision tasks will find this useful for developing robust image recognition applications.
217 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher looking for a well-structured and scalable PyTorch implementation of the ResNet architecture for image classification or other computer vision problems.
Not ideal if you are an end-user seeking a ready-to-use application for image classification, as this project provides the underlying code rather than a plug-and-play solution.
Stars
217
Forks
46
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 21, 2020
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