NimbusNet is cloud detection project powered by various state-of-the-art deep learning algorithms.
## File Descriptions
## Best Results
Our best results were obtained using a Dynamic UNet model based on ResNet-18 with Self Attention and Mish activation function. We combined spectral bands 2, 26, and 32 in the form of an RGB image and used about 52,000 blocks of 64 x 64 pixels for training. The code and results of using this model are present in `Dynamic_UNet` folder.
## File/Folder Descriptions
1.`count_blocks.py`
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7.`NCSA Hackathon III`
Final Presentation file
Folder `'Multi-band UNet` contains Non-dynamic UNet model base on band 2, 26 and 31, for more details check README in the folder.
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8.`Multi-band_UNet` contains Non-dynamic UNet model base on band 2, 26 and 31, for more details check README in the folder.
