YOLOv8量化探索

模型优化
,
1

openvino

  • Yolov8包含非Relu的激活函数，需要对激活层进行非对称量化
  • 对权重进行对称量化，对激活进行非对称量化
ignored_scope = nncf.IgnoredScope(
    types=["Multiply", "Subtract", "Sigmoid"],  # ignore operations
    names=[
        "/model.22/dfl/conv/Conv",           # in the post-processing subgraph
        "/model.22/Add",
        "/model.22/Add_1",
        "/model.22/Add_2",
        "/model.22/Add_3",
        "/model.22/Add_4",   
        "/model.22/Add_5",
        "/model.22/Add_6",
        "/model.22/Add_7",
        "/model.22/Add_8",
        "/model.22/Add_9",
        "/model.22/Add_10"
    ]
)

FP32 model accuracy
Boxes:
               Class      Images      Labels   Precision      Recall      mAP@.5  mAP@.5:.95
                 all         300        2145       0.594       0.543       0.579       0.417
INT8 model accuracy
Boxes:
               Class      Images      Labels   Precision      Recall      mAP@.5  mAP@.5:.95
                 all         300        2145       0.623       0.517       0.572       0.406

参考