Comments (2)
Hi @halbielee ,
The generated pseudo segmentation labels are evaluated on PASCAL VOC 2012 train set (pixel-level gt of train set are not available during training).
The segmentation model is retrained on these pseudo segmentation labels then evaluated on both validation and test set.
from seam.
Oh!
You are right.
I was confused that the result of Affinitynet was a segmentation result.
Thanks for the reply!
from seam.
Related Issues (20)
- cam multiplied by GT label? HOT 1
- why the final experiments result on test _set is better than it on val_set?
- Can u give some detail about training? HOT 3
- GPU and batch size? HOT 4
- Background threshold? HOT 2
- 关于CRF的参数设置
- training with my custom dataset HOT 6
- result images HOT 1
- Huge Time Cost When Running the Code HOT 1
- Confused about the code: "cam = np.flip(cam, axis=-1)"
- Exception during running train_SEAM.py
- Question about affinityNet Inference HOT 9
- 医学图像的分割 HOT 2
- infer_seam npy
- 如何利用自己的数据集进行训练
- .
- About code
- cam_full_arr[k+1] = v out of bounds HOT 2
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- The valuation problem of the pseudo label
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from seam.