Open alejopaullier96 opened 2 years ago
Is it possible to use an EfficientNet backbone in TSN? I mean something like this:
model = dict( type='Recognizer2D', backbone=dict( type='EfficientNetB4', pretrained='torchvision://efficientnet_b4', <------------- somehow change this depth=50, norm_eval=False), cls_head=dict( type='TSNHead', num_classes=3, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.4, init_std=0.01), train_cfg=None, test_cfg=dict(average_clips=None))
I dont know if this is possible. For sure there are no weights in the model zoo for this but maybe if this can be done it can be initialized with PyTorch EfficientNet's weights.
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Is it possible to use an EfficientNet backbone in TSN? I mean something like this:
I dont know if this is possible. For sure there are no weights in the model zoo for this but maybe if this can be done it can be initialized with PyTorch EfficientNet's weights.