As per the title mentioned, if I have already pretrained backbone, and I want to train only the RPN instead of the classifier using the Faster R-CNN from torchvision.
Is there any parameters I can pass in to the create_model function or would I stop the classifier training in my train() function?
I’m on mobile so olease excuse my editting
This is my create model function

Create your backbone from timm
backbone = timm.create_model(
“resnet50”,
pretrained=True,
num_classes=0,  # this is important to remove fc layers
global_pool=""  # this is important to remove fc layers
)
backbone.out_channels = backbone.feature_info[-1][“num_chs”]
anchor_generator = AnchorGenerator(
sizes=((16, 32, 64, 128, 256),), aspect_ratios=((0.25, 0.5, 1.0, 2.0),)
)
roi_pooler = torchvision.ops.MultiScaleRoIAlign(
featmap_names=[“0”], output_size=7, sampling_ratio=2
)
fastercnn_model = FasterRCNN(
backbone=backbone,
num_classes=1000,
rpn_anchor_generator=anchor_generator,
box_roi_pool=roi_pooler,
)