0c82b690c6198917e21f74b5987369b50e53f5b2,chainercv/links/faster_rcnn/faster_rcnn.py,FasterRCNNBase,_suppress,#FasterRCNNBase#,142

Before Change

            label.append(i * np.ones((len(keep),)))
            score.append(prob_cls[keep])
        bbox = self.xp.asarray(np.concatenate(bbox, axis=0).astype(np.float32))
        label = self.xp.asarray(np.concatenate(label, axis=0).astype(np.int32))
        score = self.xp.asarray(
            np.concatenate(score, axis=0).astype(np.float32))
        return bbox, label, score

After Change

            label.append(i * np.ones((len(keep),)))
            score.append(prob_cls[keep])
        bbox = np.concatenate(bbox, axis=0).astype(np.float32)
        label = np.concatenate(label, axis=0).astype(np.int32)
        score = np.concatenate(score, axis=0).astype(np.float32)
        return bbox, label, score

    def predict(self, imgs):

Instances