justchenhao / STANet

official implementation of the spatial-temporal attention neural network (STANet) for remote sensing image change detection
BSD 2-Clause "Simplified" License
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Inaccurate Results with PAM Pre-Trained Weights in demo.py #109

Open Keerthana-chinta opened 2 months ago

Keerthana-chinta commented 2 months ago

Hello,

I am experiencing issues with the accuracy of the results when using the PAM pre-trained weights while running demo.py. Despite following the instructions and loading the PAM pre-trained weights (pam_net_F.pth and pam_net_A.pth), the output does not seem to reflect the expected performance. Could you please verify whether the pre-trained weights are compatible with the current implementation in demo.py? Are there any known issues or additional steps required to get accurate results with the PAM pre-trained weights? Any guidance on improving the accuracy or resolving this issue would be greatly appreciated. Thank you for your support and for providing this valuable resource to the community!