(self, feat_dim=12, places365_model_path='')
| 69 | std = [0.229, 0.224, 0.225] |
| 70 | |
| 71 | def __init__(self, feat_dim=12, places365_model_path=''): |
| 72 | super(EfficientNetB3, self).__init__() |
| 73 | # Initialize architecture |
| 74 | self.backbone_net = EfficientNet.from_pretrained('efficientnet-b3') |
| 75 | self.feature_extractor = self.backbone_net.extract_endpoints |
| 76 | |
| 77 | # self.feature_block_index = [1, 3, 6] # same as the 'hypercolumn_layers' |
| 78 | self.feature_block_index = [1, 3, 5] # same as the 'hypercolumn_layers' |
| 79 | # self.feature_block_index = [2, 4, 6] # same as the 'hypercolumn_layers' |
| 80 | |
| 81 | ## adaptation layers, see off branches from fig.3 in S2DNet paper |
| 82 | self.adaptation_layers = AdaptLayers(self.default_conf['hypercolumn_layers'], self.default_conf['output_dim']) |
| 83 | |
| 84 | # pose regression layers |
| 85 | self.avgpool = nn.AdaptiveAvgPool2d(1) |
| 86 | self.fc_pose = nn.Linear(1536, feat_dim) |
| 87 | |
| 88 | def forward(self, x, return_feature=False, isSingleStream=False, upsampleH=120, upsampleW=213): |
| 89 | ''' |
nothing calls this directly
no test coverage detected