def decoded_output_boxes_class_agnostic(self):
""" Returns: Nx4 """
assert self._bbox_class_agnostic
box_logits = tf.reshape(self.box_logits, [-1, 4])
decoded = decode_bbox_target(box_logits / self.bbox_regression_weights,
self.proposals.boxes)
return decoded
def decoded_output_boxes(self):
""" Returns: N x #class x 4 """
anchors = tf.tile(tf.expand_dims(self.proposals.boxes, 1),
[1, cfg.DATA.NUM_CLASS, 1]) # N x #class x 4
decoded_boxes = decode_bbox_target(
self.box_logits / self.bbox_regression_weights, anchors)
return decoded_boxes
def decoded_output_boxes_for_label(self, labels):
assert not self._bbox_class_agnostic
indices = tf.stack(
[tf.range(tf.size(labels, out_type=tf.int64)), labels])
needed_logits = tf.gather_nd(self.box_logits, indices)
decoded = decode_bbox_target(
needed_logits / self.bbox_regression_weights, self.proposals.boxes)
return decoded