pascal_voc2.py 文件源码

def __init__(self, image_set, year, pascal_path=None):
        datasets.imdb.__init__(self, 'voc_' + year + '_' + image_set)
        self._year = year
        self._image_set = image_set
        self._pascal_path = self._get_default_path() if pascal_path is None \
                            else pascal_path
        self._data_path = os.path.join(self._pascal_path, 'VOCdevkit' + self._year, 'VOC' + self._year)
        self._classes = ('__background__', # always index 0
                         'aeroplane', 'bicycle', 'bird', 'boat',
                         'bottle', 'bus', 'car', 'cat', 'chair',
                         'cow', 'diningtable', 'dog', 'horse',
                         'motorbike', 'person', 'pottedplant',
                         'sheep', 'sofa', 'train', 'tvmonitor')
        self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
        self._image_ext = '.jpg'
        self._image_index = self._load_image_set_index()
        # Default to roidb handler
        if cfg.IS_RPN:
            self._roidb_handler = self.gt_roidb
        else:
            self._roidb_handler = self.region_proposal_roidb

        # num of subclasses
        self._num_subclasses = 240 + 1

        # load the mapping for subcalss to class
        filename = os.path.join(self._pascal_path, 'subcategory_exemplars', 'mapping.txt')
        assert os.path.exists(filename), 'Path does not exist: {}'.format(filename)

        mapping = np.zeros(self._num_subclasses, dtype=np.int)
        with open(filename) as f:
            for line in f:
                words = line.split()
                subcls = int(words[0])
                mapping[subcls] = self._class_to_ind[words[1]]
        self._subclass_mapping = mapping

        # PASCAL specific config options
        self.config = {'cleanup'  : True,
                       'use_salt' : True,
                       'top_k'    : 2000}

        # statistics for computing recall
        self._num_boxes_all = np.zeros(self.num_classes, dtype=np.int)
        self._num_boxes_covered = np.zeros(self.num_classes, dtype=np.int)
        self._num_boxes_proposal = 0

        assert os.path.exists(self._pascal_path), \
                'PASCAL path does not exist: {}'.format(self._pascal_path)
        assert os.path.exists(self._data_path), \
                'Path does not exist: {}'.format(self._data_path)