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#Colorization By nilboy

A Tensorflow implementation of ECCV2016 paper(Colorful Image Colorization)

presentation

###Train

Download imagenet data
  1. Download imagenet data and Extract to one directory named 'Imagenet'

  2. link the Imagenet data directory to this project path

    ln -s $Imagenet data/imagenet
    

convert the imagenet data to text_record file

python tools/create_imagenet_list.py

train

python tools/train.py -c conf/train.cfg

Train your customer data

  1. transform your training data to text_record file

  2. calculate the training data prior-probs(reference to tools/create_prior_probs.py)

  3. write your own train-configure file

  4. train (python tools/train.py -c $your_configure_file)

###test demo

  1. Download pretrained model(https://drive.google.com/file/d/0B-yiAeTLLamRWVVDQ1VmZ3BxWG8/view?usp=sharing)

    mv color_model.ckpt models/model.ckpt
    
  2. Test

    python demo.py
    

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A Tensorflow implementation of ECCV2016 paper([Colorful Image Colorization](https://arxiv.org/pdf/1603.08511.pdf))

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