"""
parse PASCAL VOC xml annotations
"""

import os
import sys
import xml.etree.ElementTree as ET
import glob


def _pp(l):  # pretty printing
    for i in l: print('{}: {}'.format(i, l[i]))


def pascal_voc_clean_xml(ANN, pick, exclusive=False):
    print('Parsing for {} {}'.format(
        pick, 'exclusively' * int(exclusive)))

    dumps = list()
    cur_dir = os.getcwd()
    os.chdir(ANN)
    annotations = os.listdir('.')
    annotations = glob.glob(str(annotations) + '*.xml')
    size = len(annotations)

    for i, file in enumerate(annotations):
        # progress bar      
        sys.stdout.write('\r')
        percentage = 1. * (i + 1) / size
        progress = int(percentage * 20)
        bar_arg = [progress * '=', ' ' * (19 - progress), percentage * 100]
        bar_arg += [file]
        sys.stdout.write('[{}>{}]{:.0f}%  {}'.format(*bar_arg))
        sys.stdout.flush()

        # actual parsing 
        in_file = open(file)
        tree = ET.parse(in_file)
        root = tree.getroot()
        jpg = str(root.find('filename').text)
        imsize = root.find('size')
        w = int(imsize.find('width').text)
        h = int(imsize.find('height').text)
        all = list()

        for obj in root.iter('object'):
            current = list()
            name = obj.find('name').text
            if name not in pick:
                continue

            xmlbox = obj.find('bndbox')
            xn = int(float(xmlbox.find('xmin').text))
            xx = int(float(xmlbox.find('xmax').text))
            yn = int(float(xmlbox.find('ymin').text))
            yx = int(float(xmlbox.find('ymax').text))
            current = [name, xn, yn, xx, yx]
            all += [current]

        add = [[jpg, [w, h, all]]]
        dumps += add
        in_file.close()

    # gather all stats
    stat = dict()
    for dump in dumps:
        all = dump[1][2]
        for current in all:
            if current[0] in pick:
                if current[0] in stat:
                    stat[current[0]] += 1
                else:
                    stat[current[0]] = 1

    print('\nStatistics:')
    _pp(stat)
    print('Dataset size: {}'.format(len(dumps)))

    os.chdir(cur_dir)
    return dumps