https://github.com/mitmul/chainer-imagenet-vgg

https://github.com/mitmul/chainer-imagenet-vgg

Last synced: 6 days ago
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• Host: GitHub
• URL: https://github.com/mitmul/chainer-imagenet-vgg
• Owner: mitmul
• Created: 2015-06-24T06:59:51.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2016-01-15T02:46:49.000Z (almost 9 years ago)
• Last Synced: 2024-10-14T12:37:01.857Z (20 days ago)
• Language: Python
• Size: 5.86 KB
• Stars: 34
• Watchers: 1
• Forks: 11
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# chainer-imagenet-vgg

Load caffemodel and transfer it to chainermodel, then save it & use it to predict label of a image.

## Requirements

- [Chainer](http://chainer.org/) is necessary

- If you create chainermodel from caffemodel by yourself,

    - [Caffe](http://caffe.berkeleyvision.org/) is required

## Download chainermodel

If you don't want to compile caffe, there is chainermodel of VGG-16 converted from caffemodel provided [here](https://gist.github.com/ksimonyan/211839e770f7b538e2d8#file-readme-md). It's trained on ILSVRC-2014 dataset.

To get it, just run

```

$ bash download_chainermodel.sh

```

### Run demo

```

$ python predict.py

```

It may produce the below outputs:

```

['n02124075' 'Egyptian cat']	probability:0.737295150757

['n02123045' 'tabby, tabby cat']	probability:0.17518492043

['n02123159' 'tiger cat']	probability:0.0533684939146

['n02127052' 'lynx, catamount']	probability:0.005824980326

['n04074963' 'remote control, remote']	probability:0.00200812658295

```

## Create chainermodel from caffemodel

### Download files

```

$ bash download_caffemodel.sh

```

### Load caffemodel and save it as chainermodel

```

$ python load_model.py

```