c7c95a0af7d7a2d21bc1d90194e908e5a53698f7,chainercv/links/model/yolo/yolo_v2.py,YOLOv2,_decode,#YOLOv2#,188

Before Change

        raw_bbox[:, 2:] += raw_bbox[:, :2]
        raw_bbox *= self.insize / self.extractor.grid

        raw_score = self.xp.exp(conf[:, 1:])
        raw_score /= raw_score.sum(axis=1, keepdims=True)
        raw_score /= 1 + self.xp.exp(-conf[:, 0, None])

        bbox = []
        label = []
        score = []
        for l in range(self.n_fg_class):
            bbox_l = raw_bbox
            score_l = raw_score[:, l]

            mask = score_l >= self.score_thresh
            bbox_l = bbox_l[mask]
            score_l = score_l[mask]

            indices = utils.non_maximum_suppression(
                bbox_l, self.nms_thresh, score_l)
            bbox_l = bbox_l[indices]
            score_l = score_l[indices]

            bbox.append(cuda.to_cpu(bbox_l))

After Change

        raw_bbox[:, 2:] += raw_bbox[:, :2]
        raw_bbox *= self.insize / self.extractor.grid

        obj = 1 / (1 + self.xp.exp(-obj))
        conf = self.xp.exp(conf)
        conf /= conf.sum(axis=1, keepdims=True)
        raw_score = obj[:, None] * conf

        bbox = []
        label = []
        score = []
        for l in range(self.n_fg_class):
            bbox_l = raw_bbox
            score_l = raw_score[:, l]

            mask = score_l >= self.score_thresh
            bbox_l = bbox_l[mask]
            score_l = score_l[mask]

            indices = utils.non_maximum_suppression(
                bbox_l, self.nms_thresh, score_l)
            bbox_l = bbox_l[indices]
            score_l = score_l[indices]

            bbox.append(cuda.to_cpu(bbox_l))

Instances