# ---- memo -----------------------
# フォルダの中にある画像の中で
# 類似したものを見つける
# ---------------------------------
import cv2
from sys import argv
from glob import glob
from itertools import combinations
import networkx as nx
import subprocess as sb


# global variances
THRESHOLD = 0.15


def usage():
    print('Usage:\n\tpython3 {f} folder_name'.format(f=__file__))
    exit()

def matching():

    # 画像リストの作成
    Pictures = glob('{folder}/*'.format(folder=FolderName))

    # ヒストグラムの計算
    image_hists = dict()
    for picture in Pictures:
        im = cv2.imread(picture)
        image_hists[picture] = cv2.calcHist([im], [0], None, [256], [0, 256])

    # 類似度の計算
    result = list()
    for pictA, pictB in combinations(Pictures, 2):
        image_histA, image_histB = image_hists[pictA], image_hists[pictB]
        tmp = cv2.compareHist(image_histA, image_histB, 3)
        if tmp < THRESHOLD:
            result.append((tmp, pictA, pictB))

    # クラスタの計算
    G = nx.Graph()
    for _, nodeA, nodeB in result:
        G.add_edge(nodeA, nodeB)
        # print('類似度:{0:0.3f} 画像名:{1} {2}'.format(result[i][0], result[i][1], result[i][2]))

    # 結果の出力
    # 類似画像なし
    if G.number_of_nodes() == 0:
        print('Same pictures are not found.')
        exit()

    # 類似画像あり
    print('Maybe same pictures ...')
    for i, component in enumerate(nx.connected_components(G)):
        print('[{}] {}'.format(i, ' '.join(component)))

    # 画像をOpenするかどうか
    print('Open those?(y or n)')
    ans = input()
    if ans in ['y', 'yes']:
        for component in nx.connected_components(G):
            component = list(component)
            print(['open'] + component)
            sb.run(['open'] + component)

    return 1

if __name__ == '__main__':
    if len(argv) == 2:
        FolderName = argv[1] if argv[1] != '/' else argv[1][:-1]
        matching()
    else:
        usage()