BoxRefinementNetwork.py 文件源码

def getBoxes(self, proposals, proposal_scores, maxOutputs=30, nmsThreshold=0.3, scoreThreshold=0.8):
        if scoreThreshold is None:
            scoreThreshold = 0

        with tf.name_scope("getBoxes"):
            scores = tf.nn.softmax(self.getBoxScores(proposals))

            classes = tf.argmax(scores, 1)
            scores = tf.reduce_max(scores, axis=1)
            posIndices = tf.cast(tf.where(tf.logical_and(classes > 0, scores>scoreThreshold)), tf.int32)

            positives, scores, classes = MultiGather.gather([proposals, scores, classes], posIndices)
            positives = self.refineBoxes(positives, False)

            #Final NMS
            posIndices = tf.image.non_max_suppression(positives, scores, iou_threshold=nmsThreshold, max_output_size=maxOutputs)
            posIndices = tf.expand_dims(posIndices, axis=-1)
            positives, scores, classes = MultiGather.gather([positives, scores, classes], posIndices)   

            classes = tf.cast(tf.cast(classes,tf.int32) - 1, tf.uint8)

            return positives, scores, classes