def compute_iou()

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

• 17 lines of code
• 12 McCabe index (conditional complexity)

    def compute_iou(self, img_id, cat_id):
        gt, dt = self._get_gt_dt(img_id, cat_id)

        if len(gt) == 0 and len(dt) == 0:
            return []

        # Sort detections in decreasing order of score.
        idx = np.argsort([-d["score"] for d in dt], kind="mergesort")
        dt = [dt[i] for i in idx]

        # iscrowd = [int(False)] * len(gt)
        iscrowd = [int('iscrowd' in g and g['iscrowd'] > 0) for g in gt]

        if self.params.iou_type == "segm":
            ann_type = "segmentation"
        elif self.params.iou_type == "bbox":
            ann_type = "bbox"
        else:
            raise ValueError("Unknown iou_type for iou computation.")
        gt = [g[ann_type] for g in gt]
        dt = [d[ann_type] for d in dt]

        # compute iou between each dt and gt region
        # will return array of shape len(dt), len(gt)
        ious = mask_utils.iou(dt, gt, iscrowd)
        return ious