RPN.py 文件源码

def filterOutputBoxes(self, boxes, scores, others=[], preNmsCount=6000, maxOutSize=300, nmsThreshold=0.7): 
        with tf.name_scope("filter_output_boxes"):
            scores = tf.nn.softmax(scores)[:,1]
            scores = tf.reshape(scores,[-1])

            #Clip boxes to edge
            boxes = self.clipBoxesToEdge(boxes)

            #Remove empty boxes
            boxes, scores = BoxUtils.filterSmallBoxes(boxes, [scores])
            scores, boxes = tf.cond(tf.shape(scores)[0] > preNmsCount , lambda: tf.tuple(MultiGather.gatherTopK(scores, preNmsCount, [boxes])), lambda: tf.tuple([scores, boxes]))

            #NMS filter
            nmsIndices = tf.image.non_max_suppression(boxes, scores, iou_threshold=nmsThreshold, max_output_size=maxOutSize)
            nmsIndices = tf.expand_dims(nmsIndices, axis=-1)

            return MultiGather.gather([boxes, scores]+others, nmsIndices)