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Pytorch implementation of "[PR2021] Boundary-induced and scene-aggregated network for monocular depth prediction"
想问下学长数据预处理具体做了什么。
20pth.rar file means the 20th epoch training results or the result of 0-20 epoches.?
hi,how do I get depth maps of test results.
Thanks!
当我尝试运行test_ibims1.py的时候,会出现如下错误:
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU
在colab上运行时,也是如此~~
Hello, when I run the code, loss changes from a positive value to a negative value, is it normal?
Epoch: [0][0/6336] Time 64.771 (64.771) Loss 2.4048 (2.4048)
Epoch: [0][1/6336] Time 2.296 (67.068) Loss 1.2893 (1.8471)
Epoch: [0][2/6336] Time 3.026 (70.094) Loss 0.6536 (1.4493)
Epoch: [0][3/6336] Time 2.855 (72.949) Loss 0.3161 (1.1660)
Epoch: [0][4/6336] Time 2.824 (75.774) Loss 0.0263 (0.9380)
Epoch: [0][5/6336] Time 2.840 (78.613) Loss 0.3054 (0.8326)
Epoch: [0][6/6336] Time 2.834 (81.447) Loss 0.0144 (0.7157)
Epoch: [0][7/6336] Time 2.820 (84.267) Loss 0.0115 (0.6277)
Epoch: [0][8/6336] Time 2.900 (87.167) Loss -0.2024 (0.5354)
Epoch: [0][9/6336] Time 2.758 (89.925) Loss -0.1402 (0.4679)
Epoch: [0][10/6336] Time 2.800 (92.724) Loss -0.3312 (0.3952)
Epoch: [0][11/6336] Time 2.877 (95.602) Loss 0.1015 (0.3708)
Epoch: [0][12/6336] Time 2.801 (98.403) Loss -0.3118 (0.3182)
Epoch: [0][13/6336] Time 2.786 (101.189) Loss 0.0319 (0.2978)
Epoch: [0][14/6336] Time 2.893 (104.082) Loss -0.3008 (0.2579)
Epoch: [0][15/6336] Time 2.789 (106.871) Loss -0.1524 (0.2322)
Epoch: [0][16/6336] Time 2.868 (109.739) Loss -0.2918 (0.2014)
Epoch: [0][17/6336] Time 2.898 (112.637) Loss 0.1009 (0.1958)
Epoch: [0][18/6336] Time 2.815 (115.452) Loss -0.3353 (0.1679)
Epoch: [0][19/6336] Time 2.818 (118.271) Loss -0.3844 (0.1403)
Epoch: [0][20/6336] Time 2.813 (121.083) Loss -0.1797 (0.1250)
Epoch: [0][21/6336] Time 2.866 (123.949) Loss -0.4487 (0.0989)
Cuda version is ?
CUDA版本是多少呢
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