EfficientNet
Quickstart
Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with:
from efficientnet_pytorch import EfficientNet
model = EfficientNet.from_pretrained('efficientnet-b0')Overview
This repository contains an op-for-op PyTorch reimplementation of EfficientNet, along with pre-trained models and examples. The goal of this implementation is to be simple, highly extensible, and easy to integrate into your own projects. This implementation is a work in progress -- new features are currently being implemented.
Details about the models are below:
| Name | # Params | Top-1 Acc. | Pretrained? |
|---|---|---|---|
efficientnet-b0 | 5.3M | 76.3 | ✓ |
efficientnet-b1 | 7.8M | 78.8 | ✓ |
efficientnet-b2 | 9.2M | 79.8 | ✓ |
efficientnet-b3 | 12M | 81.1 | ✓ |
efficientnet-b4 | 19M | 82.6 | ✓ |
efficientnet-b5 | 30M | 83.3 | ✓ |
efficientnet-b6 | 43M | 84.0 | ✓ |
efficientnet-b7 | 66M | 84.4 | ✓ |
Example: Feature Extraction
You can easily extract features with model.extract_features:
from efficientnet_pytorch import EfficientNet
model = EfficientNet.from_pretrained('efficientnet-b0')
# ... image preprocessing as in the classification example ...
print(img.shape) # torch.Size([1, 3, 224, 224])
features = model.extract_features(img)
print(features.shape) # torch.Size([1, 1280, 7, 7])