pascal_voc.py 文件源码

def prepare(self):
        gt_labels = self.load_labels()
        if self.flipped:
            print('Appending horizontally-flipped training examples ...')
            gt_labels_cp = copy.deepcopy(gt_labels)
            for idx in range(len(gt_labels_cp)):
                gt_labels_cp[idx]['flipped'] = True
                gt_labels_cp[idx]['label'] = gt_labels_cp[idx]['label'][:, ::-1, :]
                for i in xrange(self.cell_size):
                    for j in xrange(self.cell_size):
                        if gt_labels_cp[idx]['label'][i, j, 0] == 1:
                            gt_labels_cp[idx]['label'][i, j, 1] = self.image_size - 1 - gt_labels_cp[idx]['label'][i, j, 1]
            gt_labels += gt_labels_cp
        np.random.shuffle(gt_labels)
        self.gt_labels = gt_labels
        return gt_labels