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# -*- coding: utf-8 -*-
from __future__ import division
import os
from PIL import Image

import xml.dom.minidom #xml.dom.minidom解析模塊解析xml文件
import numpy as np

#文件路徑
ImgPath = './JPEGImages/' #圖片路徑
AnnoPath = './Annotations/' #xml文件路徑
savepath = './CropedVOC/' #裁剪之后，圖片存放路徑

#如果路徑不存在，則創(chuàng  )建路徑目錄
if not os.path.exists(savepath):
    os.makedirs(savepath)

imagelist = os.listdir(ImgPath)#返回該路徑下的文件和文件夾列表

for image in imagelist:
    print 'a new image:', image #000001.jpg
    image_pre, ext = os.path.splitext(image)#將文件名和文件后綴給分開(kāi)
    #image_pre 為文件名000001   ext為文件后綴jpg

    imgfile = ImgPath + image #./JPEGImages/000001.jpg
    xmlfile = AnnoPath + image_pre + '.xml' #獲取圖片對應的xml文件
    #./Annotations/000001.xml

    DomTree = xml.dom.minidom.parse(xmlfile)#打開(kāi)xml文檔
    annotation = DomTree.documentElement #得到xml對象

    #通過(guò)標簽對filename之間，嵌入的數據 看右邊 # <filename>000001.jpg</filename>
    filenamelist = annotation.getElementsByTagName('filename')  # <filename>000001.jpg</filename>
    #該返回值類(lèi)型為nodelist，是一個(gè)list由，標簽filename之間所有的node節點(diǎn)組成
    filename = filenamelist[0].childNodes[0].data
    #獲取filename標簽對之間的值

    # 通過(guò)標簽object獲取標簽屬性值
    objectlist = annotation.getElementsByTagName('object')
    #objectlist 是一個(gè)NodeList列表

    i = 1
    for objects in objectlist:
        # print objects  

        ## 通過(guò)name標簽對之間的數據
        namelist = objects.getElementsByTagName('name')
        objectname = namelist[0].childNodes[0].data
        print objectname

    # 通過(guò)bndbox標簽對之間的數據 NodeList列表
    bndbox = objects.getElementsByTagName('bndbox')

    cropboxes = []
    for box in bndbox:
        try:
            # 通過(guò)  標簽對   之間的數據
            x1_list = box.getElementsByTagName('xmin')
            x1 = int(x1_list[0].childNodes[0].data)
            y1_list = box.getElementsByTagName('ymin')
            y1 = int(y1_list[0].childNodes[0].data)
            x2_list = box.getElementsByTagName('xmax')
            x2 = int(x2_list[0].childNodes[0].data)
            y2_list = box.getElementsByTagName('ymax')
            y2 = int(y2_list[0].childNodes[0].data)
            w = x2 - x1
            h = y2 - y1

            img = Image.open(imgfile)#打開(kāi)文件
            width, height = img.size #文件的尺寸

            obj = np.array([x1, y1, x2, y2])
            #shift 是9個(gè)[0., 0., 1., 1.]組成 shape=[9,4]
            shift = np.array([[0.8, 0.8, 1.2, 1.2], [0.9, 0.9, 1.1, 1.1], [1, 1, 1, 1], [0.8, 0.8, 1, 1], [1, 1, 1.2, 1.2], \
                            [0.8, 1, 1, 1.2], [1, 0.8, 1.2, 1],
                            [(x1 + w * 1 / 6) / x1, (y1 + h * 1 / 6) / y1, (x2 + w * 1 / 6) / x2, (y2 + h * 1 / 6) / y2], \
                            [(x1 - w * 1 / 6) / x1, (y1 - h * 1 / 6) / y1, (x2 - w * 1 / 6) / x2, (y2 - h * 1 / 6) / y2]])

            XYmatrix = np.tile(obj, (9, 1))#將obj[,,,]復制，9份，構成一個(gè)二維數組
            #最終XYmatrix  shape=[9,4]

            cropboxes = XYmatrix * shift #shape=[9,4]

            for cropbox in cropboxes:
                # print 'cropbox:',cropbox
                minX = (int)(max(0, cropbox[0]))
                minY = (int)(max(0, cropbox[1]))
                maxX = (int)(min(cropbox[2], width))
                maxY = (int)(min(cropbox[3], height))


                cropbox = (minX, minY, maxX, maxY)
                cropedimg = img.crop(cropbox)#原圖片進(jìn)行裁剪

                #將裁剪后的圖片進(jìn)行保存
                cropedimg.save(savepath + image_pre + '_' + str(i) + '.jpg')
                i += 1

        except Exception, e:
            print e