mirror of https://github.com/JDAI-CV/fast-reid.git
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
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# encoding: utf-8
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"""
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@author: liaoxingyu
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@contact: sherlockliao01@gmail.com
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"""
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from torch import nn
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from .build import REID_HEADS_REGISTRY
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from ..losses import CrossEntropyLoss, TripletLoss
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from ..model_utils import weights_init_classifier, weights_init_kaiming
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from ...layers import bn_no_bias, Flatten
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@REID_HEADS_REGISTRY.register()
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class LinearHead(nn.Module):
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def __init__(self, cfg, in_feat, pool_layer=nn.AdaptiveAvgPool2d(1)):
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super().__init__()
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self._num_classes = cfg.MODEL.HEADS.NUM_CLASSES
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self.pool_layer = nn.Sequential(
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pool_layer,
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Flatten()
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)
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self.classifier = nn.Linear(in_feat, self._num_classes, bias=False)
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self.classifier.apply(weights_init_classifier)
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def forward(self, features, targets=None):
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"""
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See :class:`ReIDHeads.forward`.
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"""
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global_feat = self.pool_layer(features)
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if not self.training:
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return global_feat
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# training
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pred_class_logits = self.classifier(global_feat)
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return pred_class_logits, global_feat
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@classmethod
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def losses(cls, cfg, pred_class_logits, global_features, gt_classes, prefix='') -> dict:
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loss_dict = {}
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if "CrossEntropyLoss" in cfg.MODEL.LOSSES.NAME and pred_class_logits is not None:
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loss = CrossEntropyLoss(cfg)(pred_class_logits, gt_classes)
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loss_dict.update(loss)
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if "TripletLoss" in cfg.MODEL.LOSSES.NAME and global_features is not None:
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loss = TripletLoss(cfg)(global_features, gt_classes)
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loss_dict.update(loss)
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# rename
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name_loss_dict = {}
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for name in loss_dict.keys():
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name_loss_dict[prefix + name] = loss_dict[name]
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del loss_dict
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return name_loss_dict
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