Closed SweepingMonkWWW closed 1 year ago
保证数据集一致,配置文件一致,利用其他模型训练时则正常,unet训练就不行。下图为其他模型评估时的结果。
相关配置文件如下 base: '../base/cityscapes.yml'
batch_size: 2 iters: 1000
model: type: UNetPlusPlus in_channels: 3 num_classes: 2 use_deconv: False align_corners: False pretrained: Null is_ds: True
batch_size: 2 iters: 80000
train_dataset: type: Dataset dataset_root: data/positive_data train_path: data/positive_data/train_list.txt num_classes: 2 mode: train transforms:
val_dataset: type: Dataset dataset_root: data/positive_data val_path: data/positive_data/val_list.txt num_classes: 2 mode: val transforms:
optimizer: type: sgd momentum: 0.9 weight_decay: 4.0e-5
lr_scheduler: type: PolynomialDecay learning_rate: 0.01 end_lr: 0 power: 0.9
loss: types:
只训练了1000iter,太短了,模型还不能收敛,训练长一些
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当使用unet模型训练验证时,MIOU为0,precission为0,recall为0,Kappa为0。配置文件相同,其他模型均正常,请问是什么原因?