def __init__()

in detic/evaluation/oideval.py [0:0]

• 64 lines of code
• 20 McCabe index (conditional complexity)

    def __init__(
        self, lvis_gt, lvis_dt, iou_type="bbox", expand_pred_label=False, 
        oid_hierarchy_path='./datasets/oid/annotations/challenge-2019-label500-hierarchy.json'):
        """Constructor for OIDEval.
        Args:
            lvis_gt (LVIS class instance, or str containing path of annotation file)
            lvis_dt (LVISResult class instance, or str containing path of result file,
            or list of dict)
            iou_type (str): segm or bbox evaluation
        """
        self.logger = logging.getLogger(__name__)

        if iou_type not in ["bbox", "segm"]:
            raise ValueError("iou_type: {} is not supported.".format(iou_type))

        if isinstance(lvis_gt, LVIS):
            self.lvis_gt = lvis_gt
        elif isinstance(lvis_gt, str):
            self.lvis_gt = LVIS(lvis_gt)
        else:
            raise TypeError("Unsupported type {} of lvis_gt.".format(lvis_gt))

        if isinstance(lvis_dt, LVISResults):
            self.lvis_dt = lvis_dt
        elif isinstance(lvis_dt, (str, list)):
            # self.lvis_dt = LVISResults(self.lvis_gt, lvis_dt, max_dets=-1)
            self.lvis_dt = LVISResults(self.lvis_gt, lvis_dt)
        else:
            raise TypeError("Unsupported type {} of lvis_dt.".format(lvis_dt))

        if expand_pred_label:
            oid_hierarchy = json.load(open(oid_hierarchy_path, 'r'))
            cat_info = self.lvis_gt.dataset['categories']
            freebase2id = {x['freebase_id']: x['id'] for x in cat_info}
            id2freebase = {x['id']: x['freebase_id'] for x in cat_info}
            id2name = {x['id']: x['name'] for x in cat_info}
            
            fas = defaultdict(set)
            def dfs(hierarchy, cur_id):
                all_childs = set()
                all_keyed_child = {}
                if 'Subcategory' in hierarchy:
                    for x in hierarchy['Subcategory']:
                        childs = dfs(x, freebase2id[x['LabelName']])
                        all_childs.update(childs)
                if cur_id != -1:
                    for c in all_childs:
                        fas[c].add(cur_id)
                all_childs.add(cur_id)
                return all_childs
            dfs(oid_hierarchy, -1)
            
            expanded_pred = []
            id_count = 0
            for d in self.lvis_dt.dataset['annotations']:
                cur_id = d['category_id']
                ids = [cur_id] + [x for x in fas[cur_id]]
                for cat_id in ids:
                    new_box = copy.deepcopy(d)
                    id_count = id_count + 1
                    new_box['id'] = id_count
                    new_box['category_id'] = cat_id
                    expanded_pred.append(new_box)

            print('Expanding original {} preds to {} preds'.format(
                len(self.lvis_dt.dataset['annotations']),
                len(expanded_pred)
                ))
            self.lvis_dt.dataset['annotations'] = expanded_pred
            self.lvis_dt._create_index()
        
        # per-image per-category evaluation results
        self.eval_imgs = defaultdict(list)
        self.eval = {}  # accumulated evaluation results
        self._gts = defaultdict(list)  # gt for evaluation
        self._dts = defaultdict(list)  # dt for evaluation
        self.params = Params(iou_type=iou_type)  # parameters
        self.results = OrderedDict()
        self.ious = {}  # ious between all gts and dts

        self.params.img_ids = sorted(self.lvis_gt.get_img_ids())
        self.params.cat_ids = sorted(self.lvis_gt.get_cat_ids())