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r""" Extracts intermediate features from given backbone network & layer ids """ |
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def extract_feat_vgg(img, backbone, feat_ids, bottleneck_ids=None, lids=None): |
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r""" Extract intermediate features from VGG """ |
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feats = [] |
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feat = img |
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for lid, module in enumerate(backbone.features): |
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feat = module(feat) |
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if lid in feat_ids: |
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feats.append(feat.clone()) |
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return feats |
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def extract_feat_res(img, backbone, feat_ids, bottleneck_ids, lids): |
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r""" Extract intermediate features from ResNet""" |
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feats = [] |
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feat = backbone.conv1.forward(img) |
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feat = backbone.bn1.forward(feat) |
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feat = backbone.relu.forward(feat) |
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feat = backbone.maxpool.forward(feat) |
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for hid, (bid, lid) in enumerate(zip(bottleneck_ids, lids)): |
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res = feat |
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feat = backbone.__getattr__('layer%d' % lid)[bid].conv1.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].bn1.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].relu.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].conv2.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].bn2.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].relu.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].conv3.forward(feat) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].bn3.forward(feat) |
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if bid == 0: |
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res = backbone.__getattr__('layer%d' % lid)[bid].downsample.forward(res) |
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feat += res |
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if hid + 1 in feat_ids: |
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feats.append(feat.clone()) |
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feat = backbone.__getattr__('layer%d' % lid)[bid].relu.forward(feat) |
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return feats |
