diff --git a/mmyolo/deploy/models/dense_heads/yolov5_head.py b/mmyolo/deploy/models/dense_heads/yolov5_head.py index 9e42126f..ac996ba4 100644 --- a/mmyolo/deploy/models/dense_heads/yolov5_head.py +++ b/mmyolo/deploy/models/dense_heads/yolov5_head.py @@ -48,8 +48,7 @@ def yolov5_bbox_decoder(priors: Tensor, bbox_preds: Tensor, @FUNCTION_REWRITER.register_rewriter( func_name='mmyolo.models.dense_heads.yolov5_head.' 'YOLOv5Head.predict_by_feat') -def yolov5_head__predict_by_feat(ctx, - self, +def yolov5_head__predict_by_feat(self, cls_scores: List[Tensor], bbox_preds: List[Tensor], objectnesses: Optional[List[Tensor]] = None, @@ -85,6 +84,7 @@ def yolov5_head__predict_by_feat(ctx, tensor in the tuple is (N, num_box), and each element represents the class label of the corresponding box. """ + ctx = FUNCTION_REWRITER.get_context() detector_type = type(self) deploy_cfg = ctx.cfg use_efficientnms = deploy_cfg.get('use_efficientnms', False) @@ -163,7 +163,7 @@ def yolov5_head__predict_by_feat(ctx, func_name='mmyolo.models.dense_heads.yolov5_head.' 'YOLOv5Head.predict', backend='rknn') -def yolov5_head__predict__rknn(ctx, self, x: Tuple[Tensor], *args, +def yolov5_head__predict__rknn(self, x: Tuple[Tensor], *args, **kwargs) -> Tuple[Tensor, Tensor, Tensor]: """Perform forward propagation of the detection head and predict detection results on the features of the upstream network. @@ -181,8 +181,7 @@ def yolov5_head__predict__rknn(ctx, self, x: Tuple[Tensor], *args, 'YOLOv5HeadModule.forward', backend='rknn') def yolov5_head_module__forward__rknn( - ctx, self, x: Tensor, *args, - **kwargs) -> Tuple[Tensor, Tensor, Tensor]: + self, x: Tensor, *args, **kwargs) -> Tuple[Tensor, Tensor, Tensor]: """Forward feature of a single scale level.""" out = [] for i, feat in enumerate(x):