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chainer-dfi

Implementation of "Deep Feature Interpolation for Image Content Changes"(https://arxiv.org/abs/1611.05507) using Chainer.

Requirements

Usage

Download Caffe VGG-19 layer model

Download VGG_ILSVRC_19_layers.caffemodel from https://gist.github.com/ksimonyan/3785162f95cd2d5fee77.

Convert Caffe model to Chainer model.

$ python src/create_chainer_model.py

Download dataset

Extract images that has specific feature

Example:

$ python src/extract_image.py img_align_celeba list_attr_celeba.txt image/smile image/normal smiling young,black_hair,straight_hair -e eyeglasses,male,wearing_hat,pale_skin,narrow_eyes,bushy_eyebrows,chubby,double_chin,bald,bangs,receding_hairline,sideburns,wavy_hair

Interpolate feature

Example:

$ python src/train.py sample/sample.png sample/out.png image/normal image/smile -g 0 -i 2000

License

MIT License

chainer-dfi's People

Contributors

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Watchers

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