def __init__()

in lib/dataset/coco.py [0:0]

• 34 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self, cfg, root, image_set, is_train, transform=None):
        super().__init__(cfg, root, image_set, is_train, transform)
        self.nms_thre = cfg.TEST.NMS_THRE
        self.image_thre = cfg.TEST.IMAGE_THRE
        self.oks_thre = cfg.TEST.OKS_THRE
        self.in_vis_thre = cfg.TEST.IN_VIS_THRE
        self.bbox_file = cfg.TEST.COCO_BBOX_FILE
        self.use_gt_bbox = cfg.TEST.USE_GT_BBOX
        self.image_width = cfg.MODEL.IMAGE_SIZE[0]
        self.image_height = cfg.MODEL.IMAGE_SIZE[1]
        self.aspect_ratio = self.image_width * 1.0 / self.image_height
        self.pixel_std = 200
        self.coco = COCO(self._get_ann_file_keypoint())

        # deal with class names
        cats = [cat['name']
                for cat in self.coco.loadCats(self.coco.getCatIds())]
        self.classes = ['__background__'] + cats
        logger.info('=> classes: {}'.format(self.classes))
        self.num_classes = len(self.classes)
        self._class_to_ind = dict(zip(self.classes, range(self.num_classes)))
        self._class_to_coco_ind = dict(zip(cats, self.coco.getCatIds()))
        self._coco_ind_to_class_ind = dict([(self._class_to_coco_ind[cls],
                                             self._class_to_ind[cls])
                                            for cls in self.classes[1:]])

        # load image file names
        self.image_set_index = self._load_image_set_index()
        self.num_images = len(self.image_set_index)
        logger.info('=> num_images: {}'.format(self.num_images))

        self.num_joints = 17
        self.flip_pairs = [[1, 2], [3, 4], [5, 6], [7, 8],
                           [9, 10], [11, 12], [13, 14], [15, 16]]
        self.parent_ids = None

        self.db = self._get_db()

        if is_train and cfg.DATASET.SELECT_DATA:
            self.db = self.select_data(self.db)

        logger.info('=> load {} samples'.format(len(self.db)))