eb737460e317877af263183245ebac792c02aa20,keras_retinanet/layers/_misc.py,NonMaximumSuppression,call,#NonMaximumSuppression#Any#,121

Before Change

        classification = keras.backend.gather(classification, indices)

        // TODO: find a way to avoid reshaping the detections.
        detections = keras.backend.reshape(detections, (-1, keras.backend.int_shape(detections)[2]))
        detections = keras.backend.gather(detections, indices)

        indices = keras_retinanet.backend.non_max_suppression(boxes, scores, max_output_size=self.max_boxes, iou_threshold=self.nms_threshold)

After Change

        boxes, classification, detections = inputs

        // TODO: support batch size > 1.
        boxes          = boxes[0]
        classification = classification[0]
        detections     = detections[0]

        scores  = keras.backend.max(classification, axis=1)

Instances