I want to use a ResNet-based LSeg and I did the following:
Generally, I added a elif branch in _make_encoder(), which returns a resnet101, and modified the dimension in _make_scratch as [256,512,1024,2048]. I also replaced the forward_vit in lseg_net.py with a vanilla ResNet forward (return 4-stage output). To this end, I could start training, but could not get expected performance .
I might plug in ResNet wrongly or miss some points. Is there any demos of ResNet-based LSeg and if there is any ResNet pre-trained weights of LSeg? Thanks!
I want to use a ResNet-based LSeg and I did the following:
Generally, I added a elif branch in _make_encoder(), which returns a resnet101, and modified the dimension in _make_scratch as [256,512,1024,2048]. I also replaced the forward_vit in lseg_net.py with a vanilla ResNet forward (return 4-stage output). To this end, I could start training, but could not get expected performance .
I might plug in ResNet wrongly or miss some points. Is there any demos of ResNet-based LSeg and if there is any ResNet pre-trained weights of LSeg? Thanks!