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大佬。我的数据集是特征比较少的图片，想用resnet18。 请问configs里 # model settings model = dict( type='PolarMask', pretrained='open-mmlab://resnet50_caffe', backbone=dict( type='ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=False), style='caffe'), pretrained='open-mmlab://resnet50_caffe',要改成pretrained='open-mmlab://resnet18_caffe'吗。好像没有这个。 要是光改depth，会有RuntimeError: Given groups=1, weight of size 256 512 1 1, expected input[4, 128, 64, 64] to have 512 channels, but got 128 channels instead这个错。实在是迷茫了。望大佬解答，谢谢
# model settings model = dict( type='PolarMask', pretrained='open-mmlab://resnet50_caffe', backbone=dict( type='ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=False), style='caffe'),
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大佬。我的数据集是特征比较少的图片，想用resnet18。
请问configs里
# model settings model = dict( type='PolarMask', pretrained='open-mmlab://resnet50_caffe', backbone=dict( type='ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=False), style='caffe'),pretrained='open-mmlab://resnet50_caffe',要改成pretrained='open-mmlab://resnet18_caffe'吗。好像没有这个。
要是光改depth，会有RuntimeError: Given groups=1, weight of size 256 512 1 1, expected input[4, 128, 64, 64] to have 512 channels, but got 128 channels instead这个错。实在是迷茫了。望大佬解答，谢谢
The text was updated successfully, but these errors were encountered: