In MMYOLO, we can freeze some stages of the backbone network by setting frozen_stages parameters, so that these stage parameters do not participate in model updating.
It should be noted that frozen_stages = i means that all parameters from the initial stage to the ith stage will be frozen. The following is an example of YOLOv5. Other algorithms are the same logic.
_base_ = './yolov5_s-v61_syncbn_8xb16-300e_coco.py'
model = dict(
backbone=dict(
frozen_stages=1 # Indicates that the parameters in the first stage and all stages before it are frozen
))In addition, it's able to freeze the whole neck with the parameter freeze_all in MMYOLO. The following is an example of YOLOv5. Other algorithms are the same logic.
_base_ = './yolov5_s-v61_syncbn_8xb16-300e_coco.py'
model = dict(
neck=dict(
freeze_all=True # If freeze_all=True, all parameters of the neck will be frozen
))