How to modify layers in pretrained object detection model?

Gluon
2

You can iterate through the layers and replace them:

def replace_conv2D(net):
    for key, layer in net._children.items():
        if isinstance(layer, gluon.nn.Conv2D):
            new_conv = gluon.nn.Conv2D(
                channels=layer._channels // 2,
                kernel_size=layer._kwargs['kernel'],
                strides=layer._kwargs['stride'],
                padding=layer._kwargs['pad'],
                in_channels=layer._in_channels // 2)
            with net.name_scope():
                net.register_child(new_conv, key)
            new_conv.initialize(mx.init.Xavier())
        else:
            replace_conv2D(layer)
net = gluon.model_zoo.vision.get_model("resnet18_v1", pretrained=True)
replace_conv2D(net)

You can check these threads for more details: Modifying pre-trained gluon model zoo and Modify structure of loaded network

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