Comments (7)
On which dataset?
from u2pl.
Our checkpoints here for VOC and here for Cityscapes.
from u2pl.
Thanks for providing checkpoint, but I'm more concerned about whether the semi-supervised training can achieve the same accuracy through U2PL.
On which dataset?
Cityscapes.
from u2pl.
On Cityscapes dataset, we apply slide-window evaluation following AEL, which means we should run sh eval.sh
after training.
Therefore, the mIoU reported during training is not the final performance, which is quite different from VOC.
Did you run sh eval.sh
after training?
from u2pl.
For instance, under 1/2 partition protocol on Cityscapes, the final result is 79.12 with AEL, but the mIoU is around 75 during training.
from u2pl.
By the way, can you reproduce the results on VOC?
from u2pl.
For instance, under 1/2 partition protocol on Cityscapes, the final result is 79.12 with AEL, but the mIoU is around 75 during training.
Thanks. I'll try eval.sh.
from u2pl.
Related Issues (20)
- 对compute_unsupervised_loss计算thresh的疑惑 HOT 1
- DDP loss计算疑问 HOT 2
- 关于在val里使用center crop 的问题 HOT 2
- AEL分支中model_teacher.eval()疑惑 HOT 1
- 对比损失的变化 HOT 4
- Unsupervised loss is 0 HOT 4
- 方法同样适用于二分类任务吗? HOT 1
- sup loss逐渐为0,con loss一直为0
- GPU数量必须按你们的建议来吗? HOT 2
- train_semi.py报错,找不到一个方法 HOT 1
- 数据集疑问 HOT 6
- windows上运行
- 数据集问题 HOT 3
- 数据集 HOT 11
- 损失函数缺乏定义 HOT 2
- 关于两种数据集训练的差异问题 HOT 4
- 关于DPA与threshold的区别
- How to split the datasets (cityscapes) into labeled and unlabeled? HOT 2
- 请问 训练中带标签数据必须和无标签数据数量相等吗? HOT 1
- compute_binary_memobank_loss HOT 1
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from u2pl.