CCNet_PyTorch
Implementation of CCNet: Criss-Cross Attention for Semantic Segmentation
Stars
38
Ecosystems:
Python
CCNet_PyTorch
- : Python3.6, Pytorch1.0
- : MyData_kfold.py, MIouv0217.py, predict.py
- CCNet0403: CC.py, ccnet.py, train_kfold.py
- CCNet0509: CC.py, ccnet.py, ccnet_v3_0509.py, train_cc_v3_0509.py
- label
- 320 x 320label
- MyData_kfold.pyk
- CC.pyCCNetCriss-Cross Attention
- ccnet.py: CCNetresnet
- ccnet_v3_0509.pyCCAasppCCAdeeplabv3
- train_kfold.pyCCNet04035
- train_cc_v3_0509.pyCCNet05095
- MIoUData.pyMIoUlabel
- MIouv0217.pyAccMIoUMIoUData.py
- predict.py
- CCNetlosslistloss
- psxx_dsncat
- CCNet_0403losscat
- CCNet_v3_0509CCAdeeplabv3asppcat
- CCNet0607: deeplabv3-ccnet-resnet152 + 5 + dataset3 + weight
| & | Acc | MIoU | Kappa | ||||
|---|---|---|---|---|---|---|---|
| CCnet0403 | 0.9412 | 0.6846 | 0.7845 | 0.9876 | 0.7803 | 0.9252 | 0.4353 |
| CCnet0509 | 0.9593 | 0.7947 | 0.8593 | 0.9863 | 0.8818 | 0.8856 | 0.6740 |
| CCNet0607 | 0.9603 | 0.8057 | 0.8684 | 0.9722 | 0.8907 | 0.9216 | 0.7745 |
GT
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CCNet0403GTpredict
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CCNet_v3_0509GTpredict
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- CCNet-v3-06070509
- CCNet-v3-06070509