本文详细介绍如何使用EfficientNet进行图像分类任务，包括安装、导入、加载预训练模型及特征提取等关键步骤。通过实例演示了EfficientNet在图像处理领域的高效应用。
使用pip安装efficientnet
pip install efficientnet_pytorch
导入efficientnet
from efficientnet_pytorch import EfficientNet
model = EfficientNet.from_name('efficientnet-b0') # load an EfficientNet
model = EfficientNet.from_pretrained('efficientnet-b0', num_classes=2) # load a pretrained EfficientNet
EfficientNet 提取特征
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])
网络结构为：
图源自于https://blog.youkuaiyun.com/Trent1985/article/details/91126085
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