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基于pytorch的CV入门教程（图像分类与目标检测）

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CV-Pytorch-Classification

基于pytorch的CV入门教程（图像分类）

Author: Ruilong Ren

Date: 2022-1-12

GPU: 4 × GTX 1080Ti

Backbones

  • LetNet
  • AlexNet
  • ResNet18/34/50/101/152
  • GoogLeNet
  • VGG16/19
  • DenseNet
  • ResNeXt
  • SENet
  • MobileNetv2
  • EfficientNetB0
  • Darknet53
  • CSPDarknet53

Datasets

  • MNIST
  • CIFAR10
  • PASCAL VOC2007/2012

Output(Accurancy)

CIFAR10

  • EPOCH: 100
  • LR: CosineAnnealing
METHODS BEST-ACC TIME(s)
LetNet 71.8% 1754.7
AlexNet 70.09% 6292.1
ResNet18 95.23% 3987.9
ResNet50 95.2% 8468.4
GoogLeNet 95.02% 13144.3
VGG16 93.8% 9618
DenseNet121 94.55% 7735.3
ResNeXt29_32×4d 95.18% 9573.5
SENet18 95.22 % 6988.3
MobileNetv2 93.37% 5995.6
EfficientNetB0 90.49% 7210.8
Darknet53 91.85% 8440.4
CSPDarknet53 88.75% 5898.9
MobileNetv3
ShuffleNetv2_x0.5

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基于pytorch的CV入门教程（图像分类与目标检测）

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