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DenseNet-Tensorflow

Reimplementation of DenseNet on Image Recognition

Densely Connected Convolutional Networks(DenseNet), won the Best Paper Award on CVPR 2017.

This is an (re-)implementation of DenseNet in TensorFlow for image recognition tasks. The (re-)implementation is based on official Torch DenseNet with Tensorflow Slim.

DenseNet Table

In the paper, DenseNet-264 seems to be a typo, since there is no way the number of layers to be an even number. See DenseNet-121, 169, 201, if you add up, which is 1 + 6 x 2 + 1 + 12 x 2 + 1 + 64 x 2 + 1 + 48 x 2 + 1 + 1 = 265.

Features

  • DenseNet-B, DenseNet-C, DenseNet-BC
  • DenseNet-121, DenseNet-169, DenseNet-201, DenseNet-265
  • Training on CIFAR
  • Training on SVHN
  • Training on ImageNet

Requirement

Tensorflow 1.4

python 3.5
tensorflow 1.4
CUDA  8.0
cuDNN 6.0

Tensorflow 1.2

python 3.5
tensorflow 1.2
CUDA  8.0
cuDNN 5.1

Installation

pip3 install -r requirements.txt

Performance

CIFAR10

L=100, k=12 Accuracy Top 1 Error
paper 94.08% 5.92%
repo 95.75% 4.25%

cifar10_train

cifar10_val

CIFAR100

L=100, k=12 Accuracy Top 1 Error
paper 75.85% 24.15%
repo 77.25% 22.75%

cifar100_train

cifar100_val

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