LianYi233 / Trans-DAT

Y. Wu, L. Jiao, X. Liu, F. Liu, S. Yang and L. Li, Domain Adaptation-aware Transformer for Hyperspectral Object Tracking. IEEE Transactions on Circuits and Systems for Video Technology, 2024.
DOI: 10.1109/TCSVT.2024.3385273
MIT License
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测试问题test_3_dataset.py #1

Closed Winkness closed 7 months ago

Winkness commented 7 months ago

我使用test_3_dataset.py测试结果,得到如下结果: 172.0 191.0 16 15 tensor(168.5649, device='cuda:0', grad_fn=) tensor(187.3681, device='cuda:0', grad_fn=) tensor(29.5128, device='cuda:0', grad_fn=) tensor(27.5543, device='cuda:0', grad_fn=) tensor(163.6086, device='cuda:0', grad_fn=) tensor(179.3883, device='cuda:0', grad_fn=) tensor(53.1051, device='cuda:0', grad_fn=) tensor(49.2499, device='cuda:0', grad_fn=) tensor(154.1581, device='cuda:0', grad_fn=) tensor(164.2183, device='cuda:0', grad_fn=) tensor(97.9674, device='cuda:0', grad_fn=) tensor(92.4567, device='cuda:0', grad_fn=) tensor(147.2324, device='cuda:0', grad_fn=) tensor(137.6403, device='cuda:0', grad_fn=) tensor(185.2234, device='cuda:0', grad_fn=) tensor(176.8567, device='cuda:0', grad_fn=) tensor(118.0862, device='cuda:0', grad_fn=) 124.0 tensor(353.2392, device='cuda:0', grad_fn=) 248 tensor(139.3141, device='cuda:0', grad_fn=) 124.0 473 248 tensor(230.0239, device='cuda:0', grad_fn=) 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 236.5 124.0 473 248 ... 请问这种是什么原因呢?

LianYi233 commented 7 months ago

每一帧坐标都是一样的,可能是加载了随机权重?先训练好网络再测试吧:)

Winkness commented 7 months ago

了解了,感谢!

Wei-Peng-fei commented 2 months ago

test_3_dataset.py的create_dataset里面的LaSOTDataset的json文件你有吗?