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Boren
Boren
Deep Convolutional Neural Networks for Semantic Segmentation of Multi-Band Satellite Images
Deep Convolutional Neural Networks for Semantic Segmentation of Multi-Band Satellite Images
Preparation
- Download 3-band and 16-band from here and extract to data folders
- Install requirements by executing:
$ pip install -r requirements.txt
- In addition you need to install either tensorflow or tensorflow-gpu
Training
$ python train.py
| Argument | Description | Options |
|---|---|---|
--algorithm |
Algorithm to train | unet, fcn_densenet, tiramisu, pspnet |
--size |
Size of patches | int |
--epochs |
Epochs to train for | int |
--batch |
Samples per batch | int |
--channels |
Image channels | 3, 8, 16 |
--loss |
Loss function | crossentropy, jaccard, dice, cejaccard, cedice |
--verbose |
Print more information | bool |
--noaugment |
Turn off augmentation | bool |
--name |
Give run a custom name | str |
Testing
$ python train.py --test
| Argument | Description | Options |
|---|---|---|
--algorithm |
Algorithm to test | unet, fcn_densenet, tiramisu, pspnet |
--size |
Size of patches | int |
--channels |
Image channels | 3, 8, 16 |
--verbose |
Print more information | bool |
Visualization
It's possible to run some visualization of the data by running $ python visualize.py from the utils folder.
Boren