猫画像から猫部分のみを抽出する(matting/semantig segmentation) ref: http://qiita.com/knok/items/6ad09cc870739dbd921b

file0.txt

$ pip install -r requirements.txt
$ curl -L https://github.com/nicolov/segmentation_keras/releases/download/model/nicolov_segmentation_model.tar.gz \
 | tar xvf -
$ python predict.py --weights_path \ 
 conversion/converted/dilation8_pascal_voc.npy \
 images/cat.jpg

file1.py

# -*- coding: utf-8 -*-

import argparse
import os, sys
from PIL import Image
import numpy as np

def get_args():
    p = argparse.ArgumentParser()
    p.add_argument("--contents-dir", '-c', default=None)
    p.add_argument("--segments-dir", '-s', default=None)
    p.add_argument("--output-dir", '-o', default=None)
    p.add_argument("--cat-label-vals", '-v', default="64,0,0")
    args = p.parse_args()
    if args.contents_dir is None or args.segments_dir is None or args.output_dir is None:
        p.print_help()
        sys.exit(1)

    return args

def cat_col_array(val_str):
    vals = val_str.split(',')
    vals = [int(i) for i in vals]
    return vals

def cmpary(a1, a2):
    v1 = np.asarray(a1)
    v2 = np.asarray(a2)
    norm = np.linalg.norm(v1-v2)
    if norm <= 32:
        return True
    return False

def make_images(cont_dir, seg_dir, out_dir, cat_vals):
    files = []
    for fname in os.listdir(cont_dir): # make target file list
        seg_fname = os.path.join(seg_dir, fname)
        if os.path.exists(seg_fname):
            files.append(fname)
    for fname in files:
        print("processing: %s" % fname)
        c_fname = os.path.join(cont_dir, fname)
        cont = np.asarray(Image.open(c_fname)).copy()
        s_fname = os.path.join(seg_dir, fname)
        seg = np.asarray(Image.open(s_fname))
        width, height, _ = seg.shape
        for y in range(height):
            for x in range(width):
                vals = seg[x, y]
                if not cmpary(vals, cat_vals):
                    cont[x, y] = [255, 255, 255]
        out = Image.fromarray(cont)
        o_fname = os.path.join(out_dir, fname)
        out.save(o_fname)

def main():
    args = get_args()
    cat_vals = cat_col_array(args.cat_label_vals)
    make_images(args.contents_dir, args.segments_dir, args.output_dir,
                cat_vals)

if __name__ == '__main__':
    main()