# DenseNet-Tensorflow

**Repository Path**: itking666/DenseNet-Tensorflow

## Basic Information

- **Project Name**: DenseNet-Tensorflow
- **Description**: Reimplementation of DenseNet
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-12-06
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DenseNet-Tensorflow
Reimplementation of DenseNet on Image Recognition

[Densely Connected Convolutional Networks](https://arxiv.org/abs/1608.06993)(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](https://github.com/liuzhuang13/DenseNet) with [Tensorflow Slim](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim).

![DenseNet Table](https://github.com/NanqingD/DenseNet-Tensorflow/blob/master/images/DenseNet_table.png)

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
- [x] DenseNet-B, DenseNet-C, DenseNet-BC
- [x] DenseNet-121, DenseNet-169, DenseNet-201, DenseNet-265
- [x] 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](https://github.com/NanqingD/DenseNet-Tensorflow/blob/master/images/train_cifar10_L100_k12.png)

![cifar10_val](https://github.com/NanqingD/DenseNet-Tensorflow/blob/master/images/val_cifar10_L100_k12.png)

### CIFAR100
| L=100, k=12 | Accuracy | Top 1 Error |
| ----------- |:--------:|:-----------:|
| paper       | 75.85%   | 24.15%      |
| repo        | 77.25%   | 22.75%      |

![cifar100_train](https://github.com/NanqingD/DenseNet-Tensorflow/blob/master/images/train_cifar100_L100_k12.png)

![cifar100_val](https://github.com/NanqingD/DenseNet-Tensorflow/blob/master/images/val_cifar100_L100_k12.png)