git clone https://github.com/pdollar/coco

http://mscoco.org/dataset/#download

Python 2.7.11
       numpy
       PIL
       scikit-image
       cython  
       chainer

*Prepare resized images(256, 256)
cd data
python prepare_data.py {YOUR_IMAGE_PATH} {YOUR_RESIZE_IMAGE_PATH} {YOUR ANOTTION DATA DIR} {CHOOSE DATA TYPE "val2014", "train2014"} > {MS_COCO_img_label_list.txt}

*change the images' relative path to absolute path

cd chainer_code/
python compute_mean.py {MS_COCO_img_label_list.txt} > {rmGray.txt}

cd data/
python rmGray.py  {MS_COCO_img_label_list.txt} {rmGray.txt} {MS_COCO_img_label_list_rmGray.txt}

cd chainer/examples/imagenet
python train_imagenet.py {MS_COCO_img_label_list_train_rmGray.txt} {MS_COCO_img_label_list_val_rmGray.txt} --arch {YOU CHOOSE MODEL "nin", "alex", "alexbin", "googlenet", "googlenetbn"}

Dialogue ipython notebook and Encoder Decoder Model
  - Data/　　　　　... Preparing data Code
  - code/       ...
    - util/       ... 
    - test/       ... 

The MIT License (MIT)

Copyright (c) 2016 Yumi Hamazono

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