427c890279004ecf6923e886baccf464af139945,mmdet/models/detectors/two_stage.py,TwoStageDetector,simple_test,#TwoStageDetector#Any#Any#Any#Any#,116

Before Change

        x = self.extract_feat(img)
        if proposals is None:
            proposals = self.simple_test_rpn(x, img_meta)
        if self.with_bbox:
            // BUG proposals shape?
            det_bboxes, det_labels = self.simple_test_bboxes(
                x, img_meta, [proposals], rescale=rescale)
            bbox_result = bbox2result(det_bboxes, det_labels,
                                      self.bbox_head.num_classes)
            return bbox_result
        else:
            proposals[:, :4] /= img_meta["scale_factor"].float()
            return proposals.cpu().numpy()

    def aug_test(self, imgs, img_metas, rescale=False):
        Test with augmentations.

        If rescale is False, then returned bboxes and masks will fit the scale

After Change

    def simple_test(self, img, img_meta, proposals=None, rescale=False):
        Test without augmentation.
        assert proposals == None, "Fast RCNN hasn"t been implemented."
        assert self.with_bbox, "Bbox head must be implemented."

        x = self.extract_feat(img)

        proposal_list = self.simple_test_rpn(

Instances