We develop EfficientNets based on AutoML and Compound Scaling. If you're new to EfficientNets, here is an explanation straight from the official TensorFlow implementation:ĮfficientNets are a family of image classification models, which achieve state-of-the-art accuracy, yet being an order-of-magnitude smaller and faster than previous models. Export EfficientNet models for production.Quickly finetune an EfficientNet on your own dataset.Train new models from scratch on ImageNet with a simple command.Upcoming features: In the next few days, you will be able to: Evaluate EfficientNet models on ImageNet or your own images.Use EfficientNet models for classification or feature extraction.This implementation is a work in progress - new features are currently being implemented. The goal of this implementation is to be simple, highly extensible, and easy to integrate into your own projects. This repository contains an op-for-op PyTorch reimplementation of EfficientNet, along with pre-trained models and examples. from_pretrained( 'efficientnet-b4') Overview Usage is the same as before:įrom efficientnet_pytorch import EfficientNet model = EfficientNet. Additionally, all pretrained models have been updated to use AutoAugment preprocessing, which translates to better performance across the board. Upgrade the pip package with pip install -upgrade efficientnet-pytorch Thanks to the authors of all the pull requests! Update (July 31, 2019) It also addresses pull requests #72, #73, #85, and #86. This update makes the Swish activation function more memory-efficient. This update addresses issues #88 and #89. To switch to the export-friendly version, simply call t_swish(memory_efficient=False) after loading your desired model. For this purpose, we have also included a standard (export-friendly) swish activation function. The memory-efficient version is chosen by default, but it cannot be used when exporting using PyTorch JIT. This update allows you to choose whether to use a memory-efficient Swish activation. This update also addresses multiple other issues ( #115, #128). If advprop: # for models using advprop pretrained weights normalize = transforms. As a result, by default, advprop models are not used. It is important to note that the preprocessing required for the advprop pretrained models is slightly different from normal ImageNet preprocessing. This update adds a new category of pre-trained model based on adversarial training, called advprop. This update adds comprehensive comments and documentation (thanks to Update (January 23, 2020) Code quality improvements and fixes ( #215 #223).A new include_top (default: True) option ( #208).Here is a comparison: Update (Aug 25, 2020) The models were searched from the search space enriched with new ops such as Fused-MBConv. To develop this family of models, we use a combination of training-aware neural architecture search and scaling, to jointly optimize training speed and parameter efficiency. The EfficientNetV2 paper has been released! I am working on implementing it as you read this :)ĮfficientNetV2 is a new family of convolutional networks that have faster training speed and better parameter efficiency than previous models. from_pretrained( 'efficientnet-b0') Updates Update (April 2, 2021) Soon after I was introduced to my now dear friend Tim Roach who had a sports equipment manufacturing company and together we fixed a broken product and made it durable to weather. I was raised poor but we were always happily playing basketball together and my family has been given scholarships to college through basketball for generations.From efficientnet_pytorch import EfficientNet model = EfficientNet. We originally hung chain nets that made our hands bleed when we touched them and realized they weren't safe for anyone. I then noticed that almost all of New York didn't have nets on the courts, and I didn't think that was fun or fair so I ran a successful GoFundMe fundraiser with the help of my friends and family. The Freedom Swish Indestructible Basketball Nets were born when a middle school basketball court playground didn't have any nets on them, and I couldn't find a solution that didn't hurt the kids' hands and wouldn't be stolen or torn down.
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